Detailed Description

methods and files provided by the default constraint handlers of SCIP

A detailed description what a constraint handler does and how to add a constraint handler to SCIP can be found here.

Data Structures
struct	SCIP_QuadVarTerm

struct	SCIP_BilinTerm

struct	SCIP_RowPrep

Modules
	Inclusion methods
	methods to include specific constraint handlers into SCIP

Files
file	cons_abspower.h
	Constraint handler for absolute power constraints \(\textrm{lhs} \leq \textrm{sign}(x+a) \|x+a\|^n + c z \leq \textrm{rhs}\).

file	cons_and.h
	Constraint handler for AND constraints, \(r = x_1 \wedge x_2 \wedge \dots \wedge x_n\).

file	cons_benders.h
	constraint handler for Benders' decomposition

file	cons_benderslp.h
	constraint handler for benderslp decomposition

file	cons_bivariate.h
	constraint handler for bivariate nonlinear constraints \(\textrm{lhs} \leq f(x,y) + c z \leq \textrm{rhs}\)

file	cons_bounddisjunction.h
	constraint handler for bound disjunction constraints \((x_1 \{\leq,\geq\} b_1) \vee \ldots \vee (x_n \{\leq,\geq\} b_n)\)

file	cons_cardinality.h
	constraint handler for cardinality constraints

file	cons_conjunction.h
	constraint handler for conjunction constraints

file	cons_countsols.h
	Constraint handler for counting feasible solutions.

file	cons_cumulative.h
	constraint handler for cumulative constraints

file	cons_disjunction.h
	constraint handler for disjunction constraints

file	cons_indicator.h
	constraint handler for indicator constraints

file	cons_integral.h
	constraint handler for the integrality constraint

file	cons_knapsack.h
	Constraint handler for knapsack constraints of the form \(a^T x \le b\), x binary and \(a \ge 0\).

file	cons_linear.h
	Constraint handler for linear constraints in their most general form, \(lhs <= a^T x <= rhs\).

file	cons_linking.h
	constraint handler for linking binary variables to an integer variable

file	cons_logicor.h
	Constraint handler for logicor constraints \(1^T x \ge 1\) (equivalent to set covering, but algorithms are suited for depth first search).

file	cons_nonlinear.h
	constraint handler for nonlinear constraints \(\textrm{lhs} \leq \sum_{i=1}^n a_ix_i + \sum_{j=1}^m c_jf_j(x) \leq \textrm{rhs}\)

file	cons_or.h
	Constraint handler for "or" constraints, \(r = x_1 \vee x_2 \vee \dots \vee x_n\).

file	cons_orbisack.h
	constraint handler for orbisack constraints

file	cons_orbitope.h
	constraint handler for (partitioning/packing/full) orbitope constraints w.r.t. the full symmetric group

file	cons_pseudoboolean.h
	constraint handler for pseudoboolean constraints

file	cons_quadratic.h
	constraint handler for quadratic constraints \(\textrm{lhs} \leq \sum_{i,j=1}^n a_{i,j} x_ix_j + \sum_{i=1}^n b_i x_i \leq \textrm{rhs}\)

file	cons_setppc.h
	Constraint handler for the set partitioning / packing / covering constraints \(1^T x\ \{=, \le, \ge\}\ 1\).

file	cons_soc.h
	constraint handler for second order cone constraints \(\sqrt{\gamma + \sum_{i=1}^{n} (\alpha_i\, (x_i + \beta_i))^2} \leq \alpha_{n+1}\, (x_{n+1}+\beta_{n+1})\)

file	cons_sos1.h
	constraint handler for SOS type 1 constraints

file	cons_sos2.h
	constraint handler for SOS type 2 constraints

file	cons_superindicator.h
	constraint handler for indicator constraints over arbitrary constraint types

file	cons_symresack.h
	constraint handler for symresack constraints

file	cons_varbound.h
	Constraint handler for variable bound constraints \(lhs \leq x + c y \leq rhs\).

file	cons_xor.h
	Constraint handler for XOR constraints, \(rhs = x_1 \oplus x_2 \oplus \dots \oplus x_n\).

file	cons_rpa.h
	constraint handler for ringpacking

file	cons_optcumulative.c
	constraint handler for cumulative constraints with optional activities

Absolute Power Constraints
This constraint handler handles constraints of the form \[ \textrm{lhs} \leq \textrm{sign}(x+a) \|x+a\|^n + c z \leq \textrm{rhs} \] for \(n > 1.0\) a rational number, \(a\) and \(c\) arbitrary, and \(x\) and \(z\) variables. Note that \(x\) can have \(-a\) in the interior of its domain. Constraints are enforced by separation, domain propagation, and spatial branching. Cuts that separate on the convex hull of the graph of \(\textrm{sign}(x+a) \|x+a\|^n\) are generated as long as they separate the relaxation solution. Otherwise, spatial branching on \(x\) is applied. Further, domain propagation is implemented to propagate bound changes on \(x\) onto \(z\), and vice versa, and repropagation is implemented to allow for conflict analysis. During presolve, a pairwise comparison of absolute power constraints may allow to fix or aggregate some variables. See also Stefan Vigerske Decomposition of Multistage Stochastic Programs and a Constraint Integer Programming Approach to Mixed-Integer Nonlinear Programming PhD Thesis, Humboldt-University Berlin, 2012, submitted.
SCIP_RETCODE	SCIPcreateConsAbspower (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR x, SCIP_VAR z, SCIP_Real exponent, SCIP_Real xoffset, SCIP_Real zcoef, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicAbspower (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR x, SCIP_VAR z, SCIP_Real exponent, SCIP_Real xoffset, SCIP_Real zcoef, SCIP_Real lhs, SCIP_Real rhs)

SCIP_RETCODE	SCIPgetNlRowAbspower (SCIP scip, SCIP_CONS cons, SCIP_NLROW **nlrow)

SCIP_VAR *	SCIPgetNonlinearVarAbspower (SCIP scip, SCIP_CONS cons)

SCIP_VAR *	SCIPgetLinearVarAbspower (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetExponentAbspower (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetOffsetAbspower (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetCoefLinearAbspower (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetLhsAbspower (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetRhsAbspower (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetViolationAbspower (SCIP scip, SCIP_CONS cons, SCIP_SOL *sol)

AND Constraints
This constraint handler deals with AND-constraints. These are constraint of the form: \[ r = x_1 \wedge x_2 \wedge \dots \wedge x_n \] where \(x_i\) is a binary variable for all \(i\). Hence, \(r\) is also of binary type. The variable \(r\) is called resultant and the \(x\)'s operators.
SCIP_RETCODE	SCIPcreateConsAnd (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR resvar, int nvars, SCIP_VAR *vars, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicAnd (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR resvar, int nvars, SCIP_VAR *vars)

int	SCIPgetNVarsAnd (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsAnd (SCIP scip, SCIP_CONS cons)

SCIP_VAR *	SCIPgetResultantAnd (SCIP scip, SCIP_CONS cons)

SCIP_Bool	SCIPisAndConsSorted (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPsortAndCons (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPchgAndConsCheckFlagWhenUpgr (SCIP scip, SCIP_CONS cons, SCIP_Bool flag)

SCIP_RETCODE	SCIPchgAndConsRemovableFlagWhenUpgr (SCIP scip, SCIP_CONS cons, SCIP_Bool flag)

Benders Constraints
Two constraint handlers are implemented for the generation of Benders' decomposition cuts. When included in a problem, the Benders' decomposition constraint handlers generate cuts during the enforcement of LP and relaxation solutions. Additionally, Benders' decomposition cuts can be generated when checking the feasibility of solutions with respect to the subproblem constraints. This constraint handler has an enforcement priority that is less than the integer constraint handler. This means that only integer feasible solutions from the LP solver are enforced by this constraint handler. This is the traditional behaviour of the branch-and-check approach to Benders' decomposition. Additionally, the check priority is set low, such that this expensive constraint handler is only called as a final check on primal feasible solutions. This constraint handler in the standard constraint handler that should be added when using Benders' decomposition. Additionally, there is a flag in SCIPincludeConshdlrBenders that permits the addition of the LP constraint handler, cons_benderslp. The use of both cons_benders and cons_benderslp allows the user to perform a multiphase Benders' decomposition algorithm.
SCIP_RETCODE	SCIPconsBendersEnforceSolution (SCIP scip, SCIP_SOL sol, SCIP_CONSHDLR conshdlr, SCIP_RESULT result, SCIP_BENDERSENFOTYPE type, SCIP_Bool checkint)

Bivariate Constraints
This constraint handler handles constraints of the form \[ \textrm{lhs} \leq f(x,y) + c z \leq \textrm{rhs} \] for a bivariate nonlinear function \(f(x,y)\) (given as expression tree) that has a fixed convexity behaviour, that is, \(f(x,y)\) has to be either jointly convex in \((x,y)\), or convex in \(x\) and concave in \(y\), or convex in \(x\) and convex in \(y\), but indefinite w.r.t. \((x,y)\). See also Martin Ballerstein, Dennis Michaels, and Stefan Vigerske Linear Underestimators for bivariate functions with a fixed convexity behavior ZIB Report 13-02, 2013. http://opus4.kobv.de/opus4-zib/frontdoor/index/index/docId/1764
enum	SCIP_BIVAR_CONVEXITY { SCIP_BIVAR_ALLCONVEX = 0, SCIP_BIVAR_1CONVEX_INDEFINITE = 1, SCIP_BIVAR_CONVEX_CONCAVE = 2, SCIP_BIVAR_UNKNOWN = 3 }

SCIP_RETCODE	SCIPcreateConsBivariate (SCIP scip, SCIP_CONS cons, const char name, SCIP_EXPRTREE f, SCIP_BIVAR_CONVEXITY convextype, SCIP_VAR z, SCIP_Real zcoef, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicBivariate (SCIP scip, SCIP_CONS cons, const char name, SCIP_EXPRTREE f, SCIP_BIVAR_CONVEXITY convextype, SCIP_VAR z, SCIP_Real zcoef, SCIP_Real lhs, SCIP_Real rhs)

SCIP_VAR *	SCIPgetLinearVarBivariate (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetLinearCoefBivariate (SCIP scip, SCIP_CONS cons)

SCIP_EXPRTREE *	SCIPgetExprtreeBivariate (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetLhsBivariate (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetRhsBivariate (SCIP scip, SCIP_CONS cons)

Bound Disjunction Constraints
This constraint handler handles bound disjunction constraints of the form \[ (x_1 \{\leq,\geq\} b_1) \vee \ldots \vee (x_n \{\leq,\geq\} b_n) \] with bounds \(b_i \in Q\), decision variables \(x_i\), which can be of any type, and bound types \(\leq\) or \(\geq\).
SCIP_RETCODE	SCIPcreateConsBounddisjunction (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_BOUNDTYPE boundtypes, SCIP_Real *bounds, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicBounddisjunction (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_BOUNDTYPE boundtypes, SCIP_Real *bounds)

int	SCIPgetNVarsBounddisjunction (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsBounddisjunction (SCIP scip, SCIP_CONS cons)

SCIP_BOUNDTYPE *	SCIPgetBoundtypesBounddisjunction (SCIP scip, SCIP_CONS cons)

SCIP_Real *	SCIPgetBoundsBounddisjunction (SCIP scip, SCIP_CONS cons)

Cardinality Constraints
This constraint handler handles cardinality constraints of the form \[ \|\mbox{supp}(x)\| \leq b \] with integer right-hand side \(b\). Here, \(\|\mbox{supp}(x)\|\) denotes the number of nonzero entries of the vector \(x\). Cardinality constraints generalize special ordered set of type one (SOS1) constraints in which \(b = 1\).
SCIP_RETCODE	SCIPcreateConsCardinality (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR vars, int cardval, SCIP_VAR indvars, SCIP_Real *weights, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicCardinality (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR vars, int cardval, SCIP_VAR indvars, SCIP_Real *weights)

SCIP_RETCODE	SCIPchgCardvalCardinality (SCIP scip, SCIP_CONS cons, int cardval)

SCIP_RETCODE	SCIPaddVarCardinality (SCIP scip, SCIP_CONS cons, SCIP_VAR var, SCIP_VAR indvar, SCIP_Real weight)

SCIP_RETCODE	SCIPappendVarCardinality (SCIP scip, SCIP_CONS cons, SCIP_VAR var, SCIP_VAR indvar)

int	SCIPgetNVarsCardinality (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsCardinality (SCIP scip, SCIP_CONS cons)

int	SCIPgetCardvalCardinality (SCIP scip, SCIP_CONS cons)

SCIP_Real *	SCIPgetWeightsCardinality (SCIP scip, SCIP_CONS cons)

Conjunction Constraints
A conjunction constraint \( C \) is a constraint of the form \[ C = C_1 \wedge \dots \wedge C_n \] where all the \( C_i \) are individual constraints themselves.
SCIP_RETCODE	SCIPcreateConsConjunction (SCIP scip, SCIP_CONS cons, const char name, int nconss, SCIP_CONS **conss, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic)

SCIP_RETCODE	SCIPcreateConsBasicConjunction (SCIP scip, SCIP_CONS cons, const char name, int nconss, SCIP_CONS **conss)

SCIP_RETCODE	SCIPaddConsElemConjunction (SCIP scip, SCIP_CONS cons, SCIP_CONS *addcons)

Constraint Handler for counting solutions
If this constraint handler is activated than it counts or collects all feasible solutions. We refer to How to use SCIP to count/enumerate feasible solutions for more details about using SCIP for counting feasible solutions.
	SCIP_DECL_DIALOGEXEC (SCIPdialogExecCountPresolve)

	SCIP_DECL_DIALOGEXEC (SCIPdialogExecCount)

	SCIP_DECL_DIALOGEXEC (SCIPdialogExecWriteAllsolutions)

SCIP_RETCODE	SCIPcount (SCIP *scip)

SCIP_Longint	SCIPgetNCountedSols (SCIP scip, SCIP_Bool valid)

void	SCIPgetNCountedSolsstr (SCIP scip, char buffer, int buffersize, int requiredsize)

SCIP_Longint	SCIPgetNCountedFeasSubtrees (SCIP *scip)

void	SCIPgetCountedSparseSols (SCIP scip, SCIP_VAR *vars, int nvars, SCIP_SPARSESOL **sols, int nsols)

SCIP_RETCODE	SCIPsetParamsCountsols (SCIP *scip)

Cumulative Constraints
Given: a set of jobs, represented by their integer start time variables \(S_j\), their array of processing times \(p_j\) and of their demands \(d_j\). an integer resource capacity \(C\) The cumulative constraint ensures that for each point in time \(t\) \(\sum_{j: S_j \leq t < S_j + p_j} d_j \leq C\) holds. Separation: can be done using binary start time model, see Pritskers, Watters and Wolfe or by just separating relatively weak cuts on the start time variables Propagation: time tabling, Klein & Scholl (1999) Edge-finding from Petr Vilim, adjusted and simplified for dynamic repropagation (2009) energetic reasoning, see Baptiste, Le Pape, Nuijten (2001)
SCIP_RETCODE	SCIPcreateConsCumulative (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, int durations, int *demands, int capacity, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicCumulative (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, int durations, int *demands, int capacity)

SCIP_RETCODE	SCIPsetHminCumulative (SCIP scip, SCIP_CONS cons, int hmin)

int	SCIPgetHminCumulative (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPsetHmaxCumulative (SCIP scip, SCIP_CONS cons, int hmax)

int	SCIPgetHmaxCumulative (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsCumulative (SCIP scip, SCIP_CONS cons)

int	SCIPgetNVarsCumulative (SCIP scip, SCIP_CONS cons)

int	SCIPgetCapacityCumulative (SCIP scip, SCIP_CONS cons)

int *	SCIPgetDurationsCumulative (SCIP scip, SCIP_CONS cons)

int *	SCIPgetDemandsCumulative (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPcheckCumulativeCondition (SCIP scip, SCIP_SOL sol, int nvars, SCIP_VAR *vars, int durations, int demands, int capacity, int hmin, int hmax, SCIP_Bool violated, SCIP_CONS *cons, SCIP_Bool printreason)

SCIP_RETCODE	SCIPnormalizeCumulativeCondition (SCIP scip, int nvars, SCIP_VAR vars, int durations, int demands, int capacity, int nchgcoefs, int nchgsides)

SCIP_RETCODE	SCIPsplitCumulativeCondition (SCIP scip, int nvars, SCIP_VAR vars, int durations, int demands, int capacity, int hmin, int hmax, int split)

SCIP_RETCODE	SCIPpresolveCumulativeCondition (SCIP scip, int nvars, SCIP_VAR vars, int durations, int hmin, int hmax, SCIP_Bool downlocks, SCIP_Bool uplocks, SCIP_CONS cons, SCIP_Bool delvars, int nfixedvars, int nchgsides, SCIP_Bool *cutoff)

SCIP_RETCODE	SCIPpropCumulativeCondition (SCIP scip, SCIP_PRESOLTIMING presoltiming, int nvars, SCIP_VAR vars, int durations, int demands, int capacity, int hmin, int hmax, SCIP_CONS cons, int nchgbds, SCIP_Bool initialized, SCIP_Bool explanation, SCIP_Bool cutoff)

SCIP_RETCODE	SCIPrespropCumulativeCondition (SCIP scip, int nvars, SCIP_VAR vars, int durations, int demands, int capacity, int hmin, int hmax, SCIP_VAR infervar, int inferinfo, SCIP_BOUNDTYPE boundtype, SCIP_BDCHGIDX bdchgidx, SCIP_Real relaxedbd, SCIP_Bool explanation, SCIP_RESULT *result)

SCIP_RETCODE	SCIPvisualizeConsCumulative (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPsetSolveCumulative (SCIP scip, SCIP_DECL_SOLVECUMULATIVE((solveCumulative)))

SCIP_RETCODE	SCIPsolveCumulative (SCIP scip, int njobs, SCIP_Real ests, SCIP_Real lsts, SCIP_Real objvals, int durations, int demands, int capacity, int hmin, int hmax, SCIP_Real timelimit, SCIP_Real memorylimit, SCIP_Longint maxnodes, SCIP_Bool solved, SCIP_Bool infeasible, SCIP_Bool unbounded, SCIP_Bool error)

SCIP_RETCODE	SCIPcreateWorstCaseProfile (SCIP scip, SCIP_PROFILE profile, int nvars, SCIP_VAR *vars, int durations, int *demands)

int	SCIPcomputeHmin (SCIP scip, SCIP_PROFILE profile, int capacity)

int	SCIPcomputeHmax (SCIP scip, SCIP_PROFILE profile, int capacity)

#define	SCIP_DECL_SOLVECUMULATIVE(x)

Disjunction Constraints
A disjunction constraint \( C \) is a constraint of the form \[ C = C_1 \vee \dots \vee C_n \] where all the \( C_i \) are individual constraints themselves.
SCIP_RETCODE	SCIPcreateConsDisjunction (SCIP scip, SCIP_CONS cons, const char name, int nconss, SCIP_CONS *conss, SCIP_CONS relaxcons, SCIP_Bool initial, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic)

SCIP_RETCODE	SCIPcreateConsBasicDisjunction (SCIP scip, SCIP_CONS cons, const char name, int nconss, SCIP_CONS *conss, SCIP_CONS relaxcons)

SCIP_RETCODE	SCIPaddConsElemDisjunction (SCIP scip, SCIP_CONS cons, SCIP_CONS *addcons)

Indicator Constraints
An indicator constraint is given by a binary variable \(z\) and an inequality \(ax \leq b\). It states that if \(z = 1\) then \(ax \leq b\) holds. This constraint is handled by adding a slack variable \(s:\; ax - s \leq b\) with \(s \geq 0\). The constraint is enforced by fixing \(s\) to 0 if \(z = 1\). Note The constraint only implements an implication not an equivalence, i.e., it does not ensure that \(z = 1\) if \(ax \leq b\) or equivalently if \(s = 0\) holds. This constraint is equivalent to a linear constraint \(ax - s \leq b\) and an SOS1 constraint on \(z\) and \(s\) (at most one should be nonzero). In the indicator context we can, however, separate more inequalities.
SCIP_RETCODE	SCIPcreateConsIndicator (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR binvar, int nvars, SCIP_VAR vars, SCIP_Real vals, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicIndicator (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR binvar, int nvars, SCIP_VAR vars, SCIP_Real vals, SCIP_Real rhs)

SCIP_RETCODE	SCIPcreateConsIndicatorLinCons (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR binvar, SCIP_CONS lincons, SCIP_VAR *slackvar, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicIndicatorLinCons (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR binvar, SCIP_CONS lincons, SCIP_VAR *slackvar)

SCIP_RETCODE	SCIPaddVarIndicator (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real val)

SCIP_CONS *	SCIPgetLinearConsIndicator (SCIP_CONS *cons)

SCIP_RETCODE	SCIPsetLinearConsIndicator (SCIP scip, SCIP_CONS cons, SCIP_CONS *lincons)

SCIP_RETCODE	SCIPsetBinaryVarIndicator (SCIP scip, SCIP_CONS cons, SCIP_VAR *binvar)

SCIP_VAR *	SCIPgetBinaryVarIndicator (SCIP_CONS *cons)

SCIP_VAR *	SCIPgetSlackVarIndicator (SCIP_CONS *cons)

SCIP_RETCODE	SCIPsetSlackVarUb (SCIP scip, SCIP_CONS cons, SCIP_Real ub)

SCIP_Bool	SCIPisViolatedIndicator (SCIP scip, SCIP_CONS cons, SCIP_SOL *sol)

SCIP_RETCODE	SCIPmakeIndicatorFeasible (SCIP scip, SCIP_CONS cons, SCIP_SOL sol, SCIP_Bool changed)

SCIP_RETCODE	SCIPmakeIndicatorsFeasible (SCIP scip, SCIP_CONSHDLR conshdlr, SCIP_SOL sol, SCIP_Bool changed)

SCIP_RETCODE	SCIPaddLinearConsIndicator (SCIP scip, SCIP_CONSHDLR conshdlr, SCIP_CONS *lincons)

SCIP_RETCODE	SCIPaddRowIndicator (SCIP scip, SCIP_CONSHDLR conshdlr, SCIP_ROW *row)

Knapsack Constraints
This constraint handler handles a special type of linear constraints, namely knapsack constraints. A knapsack constraint has the form \[ \sum_{i=1}^n a_i x_i \leq b \] with non-negative integer coefficients \(a_i\), integer right-hand side \(b\), and binary variables \(x_i\).
SCIP_RETCODE	SCIPcreateConsKnapsack (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_Longint weights, SCIP_Longint capacity, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicKnapsack (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_Longint weights, SCIP_Longint capacity)

SCIP_RETCODE	SCIPaddCoefKnapsack (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Longint weight)

SCIP_Longint	SCIPgetCapacityKnapsack (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPchgCapacityKnapsack (SCIP scip, SCIP_CONS cons, SCIP_Longint capacity)

int	SCIPgetNVarsKnapsack (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsKnapsack (SCIP scip, SCIP_CONS cons)

SCIP_Longint *	SCIPgetWeightsKnapsack (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetDualsolKnapsack (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetDualfarkasKnapsack (SCIP scip, SCIP_CONS cons)

SCIP_ROW *	SCIPgetRowKnapsack (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPsolveKnapsackExactly (SCIP scip, int nitems, SCIP_Longint weights, SCIP_Real profits, SCIP_Longint capacity, int items, int solitems, int nonsolitems, int nsolitems, int nnonsolitems, SCIP_Real solval, SCIP_Bool success)

SCIP_RETCODE	SCIPsolveKnapsackApproximately (SCIP scip, int nitems, SCIP_Longint weights, SCIP_Real profits, SCIP_Longint capacity, int items, int solitems, int nonsolitems, int nsolitems, int nnonsolitems, SCIP_Real *solval)

SCIP_RETCODE	SCIPseparateKnapsackCuts (SCIP scip, SCIP_CONS cons, SCIP_SEPA sepa, SCIP_VAR vars, int nvars, SCIP_Longint weights, SCIP_Longint capacity, SCIP_SOL sol, SCIP_Bool usegubs, SCIP_Bool cutoff, int *ncuts)

SCIP_RETCODE	SCIPseparateRelaxedKnapsack (SCIP scip, SCIP_CONS cons, SCIP_SEPA sepa, int nknapvars, SCIP_VAR knapvars, SCIP_Real knapvals, SCIP_Real valscale, SCIP_Real rhs, SCIP_SOL sol, SCIP_Bool cutoff, int *ncuts)

Linear Constraints
This constraint handler handles linear constraints in their most general form. That is, \[ lhs \leq \sum_{i=1}^n a_i x_i \leq rhs \] with \(a_i \in Q, i = 1,\dots,n\), \(lhs\in Q \cup \{-\infty\}\), \(rhs\in Q \cup \{\infty\}\), and decision variables \(x_i, i = 1,\dots,n\) which can be binary, integer, or continuous. Furthermore, this header offers the upgrade functionality of a general linear constraint into a more specific constraint, such as a knapsack constraint, via SCIP_DECL_LINCONSUPGD() and SCIPincludeLinconsUpgrade()
typedef struct SCIP_LinConsUpgrade	SCIP_LINCONSUPGRADE

SCIP_RETCODE	SCIPincludeLinconsUpgrade (SCIP scip, SCIP_DECL_LINCONSUPGD((linconsupgd)), int priority, const char *conshdlrname)

SCIP_RETCODE	SCIPcreateConsLinear (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_Real vals, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicLinear (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_Real vals, SCIP_Real lhs, SCIP_Real rhs)

SCIP_RETCODE	SCIPcopyConsLinear (SCIP scip, SCIP_CONS cons, SCIP sourcescip, const char name, int nvars, SCIP_VAR sourcevars, SCIP_Real sourcecoefs, SCIP_Real lhs, SCIP_Real rhs, SCIP_HASHMAP varmap, SCIP_HASHMAP consmap, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode, SCIP_Bool global, SCIP_Bool *valid)

SCIP_RETCODE	SCIPaddCoefLinear (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real val)

SCIP_RETCODE	SCIPchgCoefLinear (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real val)

SCIP_RETCODE	SCIPdelCoefLinear (SCIP scip, SCIP_CONS cons, SCIP_VAR *var)

SCIP_Real	SCIPgetLhsLinear (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetRhsLinear (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPchgLhsLinear (SCIP scip, SCIP_CONS cons, SCIP_Real lhs)

SCIP_RETCODE	SCIPchgRhsLinear (SCIP scip, SCIP_CONS cons, SCIP_Real rhs)

int	SCIPgetNVarsLinear (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsLinear (SCIP scip, SCIP_CONS cons)

SCIP_Real *	SCIPgetValsLinear (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetActivityLinear (SCIP scip, SCIP_CONS cons, SCIP_SOL *sol)

SCIP_Real	SCIPgetFeasibilityLinear (SCIP scip, SCIP_CONS cons, SCIP_SOL *sol)

SCIP_Real	SCIPgetDualsolLinear (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetDualfarkasLinear (SCIP scip, SCIP_CONS cons)

SCIP_ROW *	SCIPgetRowLinear (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPupgradeConsLinear (SCIP scip, SCIP_CONS cons, SCIP_CONS **upgdcons)

SCIP_RETCODE	SCIPclassifyConstraintTypesLinear (SCIP scip, SCIP_LINCONSSTATS linconsstats)

#define	SCIP_DECL_LINCONSUPGD(x)

Linking Constraints
The constraints handler stores linking constraints between an integer variable and an array of binary variables. Such a linking constraint has the form: \[ y = \sum_{i=1}^n {c_i * x_i} \] with integer variable \( y \), binary variables \( x_1, \dots, x_n \) and offset \(b \in Q\), and with the additional side condition that exactly one binary variable has to be one (set partitioning condition). This constraint can be created only with the integer variable. In this case the binary variables are only created on demand. That is, whenever someone asks for the binary variables. Therefore, such constraints can be used to get a "binary representation" of the domain of the integer variable which will be dynamically created.
SCIP_RETCODE	SCIPcreateConsLinking (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR intvar, SCIP_VAR binvars, int vals, int nbinvars, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicLinking (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR intvar, SCIP_VAR binvars, int vals, int nbinvars)

SCIP_Bool	SCIPexistsConsLinking (SCIP scip, SCIP_VAR intvar)

SCIP_CONS *	SCIPgetConsLinking (SCIP scip, SCIP_VAR intvar)

SCIP_VAR *	SCIPgetIntvarLinking (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPgetBinvarsLinking (SCIP scip, SCIP_CONS cons, SCIP_VAR **binvars, int nbinvars)

int	SCIPgetNBinvarsLinking (SCIP scip, SCIP_CONS cons)

int *	SCIPgetValsLinking (SCIP scip, SCIP_CONS cons)

Logicor Constraints
This constraint handler handles a special type of linear constraints, namely logic or constraints. These are equivalent to set covering constraints, but are handled by special algorithms which are better suited for depth first search. For a set of binary variables \(x_i, i=1,\dots,n\), a logic or constraint has the form \[ \sum_{i=1}^n x_i \ge 1. \]
SCIP_RETCODE	SCIPcreateConsLogicor (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR **vars, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicLogicor (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR **vars)

SCIP_RETCODE	SCIPaddCoefLogicor (SCIP scip, SCIP_CONS cons, SCIP_VAR *var)

int	SCIPgetNVarsLogicor (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsLogicor (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetDualsolLogicor (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetDualfarkasLogicor (SCIP scip, SCIP_CONS cons)

SCIP_ROW *	SCIPgetRowLogicor (SCIP scip, SCIP_CONS cons)

Nonlinear Constraints
This constraint handler handles constraints of the form \[ \textrm{lhs} \leq \sum_{i=1}^n a_ix_i + \sum_{j=1}^m c_jf_j(x) \leq \textrm{rhs}, \] where \(a_i\) and \(c_j\) are coefficients and \(f_j(x)\) are nonlinear functions (given as expression tree). Constraints are enforced by separation, domain propagation, and spatial branching. For convex or concave \(f_j(x)\), cuts that separate on the convex hull of the function graph are implemented. For \(f_j(x)\) that are not known to be convex or concave, a simple variant of linear estimation based on interval gradients is implemented. Branching is performed for variables in nonconvex terms, if the relaxation solution cannot be separated. This header offers the upgrade functionality to upgrade a general nonlinear constraint into a more specific constraint via SCIP_DECL_NONLINCONSUPGD(). Furthermore, the definition of callbacks used to reformulate an expression graph is offered by SCIP_DECL_EXPRGRAPHNODEREFORM(). Further, the function representation is stored in an expression graph, which allows to propagate variable domains and constraint sides and offers a simple convexity check. During presolve, the expression graph is reformulated, whereby new variables and constraints are created such that for the remaining nonlinear constraints the functions \(f_j(x)\) are known to be convex or concave. See also Stefan Vigerske Decomposition of Multistage Stochastic Programs and a Constraint Integer Programming Approach to Mixed-Integer Nonlinear Programming PhD Thesis, Humboldt-University Berlin, 2012, submitted.
SCIP_RETCODE	SCIPincludeNonlinconsUpgrade (SCIP scip, SCIP_DECL_NONLINCONSUPGD((nonlinconsupgd)), SCIP_DECL_EXPRGRAPHNODEREFORM((nodereform)), int priority, SCIP_Bool active, const char conshdlrname)

SCIP_RETCODE	SCIPcreateConsNonlinear (SCIP scip, SCIP_CONS cons, const char name, int nlinvars, SCIP_VAR *linvars, SCIP_Real lincoefs, int nexprtrees, SCIP_EXPRTREE *exprtrees, SCIP_Real nonlincoefs, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicNonlinear (SCIP scip, SCIP_CONS cons, const char name, int nlinvars, SCIP_VAR *linvars, SCIP_Real lincoefs, int nexprtrees, SCIP_EXPRTREE *exprtrees, SCIP_Real nonlincoefs, SCIP_Real lhs, SCIP_Real rhs)

SCIP_RETCODE	SCIPcreateConsNonlinear2 (SCIP scip, SCIP_CONS cons, const char name, int nlinvars, SCIP_VAR *linvars, SCIP_Real lincoefs, SCIP_EXPRGRAPHNODE *exprgraphnode, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicNonlinear2 (SCIP scip, SCIP_CONS cons, const char name, int nlinvars, SCIP_VAR *linvars, SCIP_Real lincoefs, SCIP_EXPRGRAPHNODE *exprgraphnode, SCIP_Real lhs, SCIP_Real rhs)

SCIP_RETCODE	SCIPaddLinearVarNonlinear (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real coef)

SCIP_RETCODE	SCIPsetExprtreesNonlinear (SCIP scip, SCIP_CONS cons, int nexprtrees, SCIP_EXPRTREE *exprtrees, SCIP_Real coefs)

SCIP_RETCODE	SCIPaddExprtreesNonlinear (SCIP scip, SCIP_CONS cons, int nexprtrees, SCIP_EXPRTREE *exprtrees, SCIP_Real coefs)

SCIP_RETCODE	SCIPgetNlRowNonlinear (SCIP scip, SCIP_CONS cons, SCIP_NLROW **nlrow)

int	SCIPgetNLinearVarsNonlinear (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetLinearVarsNonlinear (SCIP scip, SCIP_CONS cons)

SCIP_Real *	SCIPgetLinearCoefsNonlinear (SCIP scip, SCIP_CONS cons)

int	SCIPgetNExprtreesNonlinear (SCIP scip, SCIP_CONS cons)

SCIP_EXPRTREE **	SCIPgetExprtreesNonlinear (SCIP scip, SCIP_CONS cons)

SCIP_Real *	SCIPgetExprtreeCoefsNonlinear (SCIP scip, SCIP_CONS cons)

SCIP_EXPRGRAPHNODE *	SCIPgetExprgraphNodeNonlinear (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetLhsNonlinear (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetRhsNonlinear (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPcheckCurvatureNonlinear (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPgetCurvatureNonlinear (SCIP scip, SCIP_CONS cons, SCIP_Bool checkcurv, SCIP_EXPRCURV *curvature)

SCIP_RETCODE	SCIPgetExprtreeCurvaturesNonlinear (SCIP scip, SCIP_CONS cons, SCIP_Bool checkcurv, SCIP_EXPRCURV **curvatures)

SCIP_RETCODE	SCIPgetViolationNonlinear (SCIP scip, SCIP_CONS cons, SCIP_SOL sol, SCIP_Real violation)

int	SCIPgetLinvarMayDecreaseNonlinear (SCIP scip, SCIP_CONS cons)

int	SCIPgetLinvarMayIncreaseNonlinear (SCIP scip, SCIP_CONS cons)

SCIP_EXPRGRAPH *	SCIPgetExprgraphNonlinear (SCIP scip, SCIP_CONSHDLR conshdlr)

SCIP_RETCODE	SCIPcomputeHyperplaneThreePoints (SCIP scip, SCIP_Real a1, SCIP_Real a2, SCIP_Real a3, SCIP_Real b1, SCIP_Real b2, SCIP_Real b3, SCIP_Real c1, SCIP_Real c2, SCIP_Real c3, SCIP_Real alpha, SCIP_Real beta, SCIP_Real gamma_, SCIP_Real *delta)

OR Constraints
This constraint handler deals with OR constraint. These are constraint of the form: \[ r = x_1 \vee x_2 \vee \dots \vee x_n \] where \(x_i\) is a binary variable for all \(i\). Hence, \(r\) is also of binary type. The variable \(r\) is called resultant and the \(x\)'s operators.
SCIP_RETCODE	SCIPcreateConsOr (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR resvar, int nvars, SCIP_VAR *vars, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicOr (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR resvar, int nvars, SCIP_VAR *vars)

int	SCIPgetNVarsOr (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsOr (SCIP scip, SCIP_CONS cons)

SCIP_VAR *	SCIPgetResultantOr (SCIP scip, SCIP_CONS cons)

Orbisack Constraints
This constraint handler can be used to handle symmetries in certain 0/1-programs. The principle structure is that some variables can be ordered in matrix form with two columns, such that permuting both columns does not change the validity and objective function value of a solution. That is, there exists a permutation symmetry of the program that permutes the variables of the first and second column row-wise. In more mathematical terms the structure has to be as follows: There are 0/1-variables \(x_{ij}\), \(i \in \{1, \dots, n\}\), \(j \in \{1, 2\}\). Permuting columns of \(x\) does not change the validity and objective function value of any feasible solution.
SCIP_RETCODE	SCIPseparateCoversOrbisack (SCIP scip, SCIP_CONS cons, SCIP_SOL sol, SCIP_VAR vars1, SCIP_VAR vars2, int nrows, SCIP_Bool infeasible, int *ngen)

SCIP_RETCODE	SCIPcheckSolutionOrbisack (SCIP scip, SCIP_SOL sol, SCIP_VAR vars1, SCIP_VAR vars2, int nrows, SCIP_Bool printreason, SCIP_Bool *feasible)

SCIP_RETCODE	SCIPcreateConsOrbisack (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR const vars1, SCIP_VAR const vars2, int nrows, SCIP_Bool ispporbisack, SCIP_Bool isparttype, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicOrbisack (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR vars1, SCIP_VAR vars2, int nrows, SCIP_Bool ispporbisack, SCIP_Bool isparttype)

Orbitope Constraints
This constraint handler can be used to handle symmetries in certain 0/1-programs. The principle structure is that some variables can be ordered in matrix form, such that permuting columns does not change the validity and objective function value of a solution. That is, the symmetry group of the program contains the full symmetric group obtained by permuting the columns of this matrix. These symmetries can be handled by so-called full orbitopes. Moreover, if the variables in each row are contained in set packing or partitioning constraint, these symmetries can be handled by specialized packing or partitioning orbitopes. In more mathematical terms the structure has to be as follows: There are 0/1-variables \(x_{ij}\), \(i \in \{1, \dots, p\}\), \(j \in \{1, \dots, q\}\). The variables may be coupled through set packing or partitioning constraints: \[ \sum_{j = 1}^q x_{ij} \leq 1 \quad \mbox{or} \quad \sum_{j = 1}^q x_{ij} = 1 \quad \mbox{for all }i = 1, \ldots, p. \] Permuting columns of \(x\) does not change the validity and objective function value of any feasible solution.
enum	SCIP_OrbitopeType { SCIP_ORBITOPETYPE_FULL = 0, SCIP_ORBITOPETYPE_PARTITIONING = 1, SCIP_ORBITOPETYPE_PACKING = 2 }

typedef enum SCIP_OrbitopeType	SCIP_ORBITOPETYPE

SCIP_RETCODE	SCIPcreateConsOrbitope (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR ***vars, SCIP_ORBITOPETYPE orbitopetype, int nspcons, int nblocks, SCIP_Bool resolveprop, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicOrbitope (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR ***vars, SCIP_ORBITOPETYPE orbitopetype, int nspcons, int nblocks, SCIP_Bool resolveprop)

Pseudoboolean Constraints
The constraint handler deals with pseudo boolean constraints. These are constraints of the form \[ \mbox{lhs} \leq \sum_{k=0}^m c_k \cdot x_k + \sum_{i=0}^n c_i \cdot \prod_{j \in I_i} x_j \leq \mbox{rhs} \] where all \(x\) are binary and all \(c\) are integer.
enum	SCIP_LinearConsType { SCIP_LINEARCONSTYPE_INVALIDCONS = -1, SCIP_LINEARCONSTYPE_LINEAR = 0, SCIP_LINEARCONSTYPE_LOGICOR = 1, SCIP_LINEARCONSTYPE_KNAPSACK = 2, SCIP_LINEARCONSTYPE_SETPPC = 3 }

typedef enum SCIP_LinearConsType	SCIP_LINEARCONSTYPE

SCIP_RETCODE	SCIPcreateConsPseudobooleanWithConss (SCIP scip, SCIP_CONS cons, const char name, SCIP_CONS lincons, SCIP_LINEARCONSTYPE linconstype, SCIP_CONS andconss, SCIP_Real andcoefs, int nandconss, SCIP_VAR indvar, SCIP_Real weight, SCIP_Bool issoftcons, SCIP_VAR intvar, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsPseudoboolean (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR *linvars, int nlinvars, SCIP_Real linvals, SCIP_VAR **terms, int nterms, int ntermvars, SCIP_Real termvals, SCIP_VAR indvar, SCIP_Real weight, SCIP_Bool issoftcons, SCIP_VAR *intvar, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicPseudoboolean (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR *linvars, int nlinvars, SCIP_Real linvals, SCIP_VAR **terms, int nterms, int ntermvars, SCIP_Real termvals, SCIP_VAR indvar, SCIP_Real weight, SCIP_Bool issoftcons, SCIP_VAR *intvar, SCIP_Real lhs, SCIP_Real rhs)

SCIP_RETCODE	SCIPaddCoefPseudoboolean (SCIP const scip, SCIP_CONS const cons, SCIP_VAR *const var, SCIP_Real const val)

SCIP_RETCODE	SCIPaddTermPseudoboolean (SCIP const scip, SCIP_CONS const cons, SCIP_VAR **const vars, int const nvars, SCIP_Real const val)

SCIP_VAR *	SCIPgetIndVarPseudoboolean (SCIP const scip, SCIP_CONS const cons)

SCIP_CONS *	SCIPgetLinearConsPseudoboolean (SCIP const scip, SCIP_CONS const cons)

SCIP_LINEARCONSTYPE	SCIPgetLinearConsTypePseudoboolean (SCIP const scip, SCIP_CONS const cons)

int	SCIPgetNLinVarsWithoutAndPseudoboolean (SCIP const scip, SCIP_CONS const cons)

SCIP_RETCODE	SCIPgetLinDatasWithoutAndPseudoboolean (SCIP const scip, SCIP_CONS const cons, SCIP_VAR *const linvars, SCIP_Real const lincoefs, int *const nlinvars)

SCIP_RETCODE	SCIPgetAndDatasPseudoboolean (SCIP const scip, SCIP_CONS const cons, SCIP_CONS *const andconss, SCIP_Real const andcoefs, int *const nandconss)

int	SCIPgetNAndsPseudoboolean (SCIP const scip, SCIP_CONS const cons)

SCIP_RETCODE	SCIPchgLhsPseudoboolean (SCIP const scip, SCIP_CONS const cons, SCIP_Real const lhs)

SCIP_RETCODE	SCIPchgRhsPseudoboolean (SCIP const scip, SCIP_CONS const cons, SCIP_Real const rhs)

SCIP_Real	SCIPgetLhsPseudoboolean (SCIP const scip, SCIP_CONS const cons)

SCIP_Real	SCIPgetRhsPseudoboolean (SCIP const scip, SCIP_CONS const cons)

Quadratic Constraints
This constraint handler handles constraints of the form \[ \textrm{lhs} \leq \sum_{i,j=1}^n a_{i,j} x_ix_j + \sum_{i=1}^n b_i x_i \leq \textrm{rhs} \] Constraints are enforced by separation, domain propagation, and spatial branching. For semidefinite matrices \(A=(a_{i,j})_{i,j}\), cuts based on linearization of \(\langle x, Ax\rangle\) are implemented. For underestimating a non-convex term, McCormick underestimators and secants for univariate concave quadratic terms are implemented. If \(\langle x, Ax\rangle\) is factorable (i.e., can be written as product of two linear functions), specialized separation techniques (e.g., lifted tangent inequalities) that take the constraint sides into account are applied. Branching is performed for variables in nonconvex terms, if the relaxation solution cannot be separated. Further, domain propagation is applied. During presolve, variable products which contain binary variables may be reformulated into linear constraints, thereby introducing new variables. See also Timo Berthold and Stefan Heinz and Stefan Vigerske Extending a CIP framework to solve MIQCPs In: Jon Lee and Sven Leyffer (eds.), Mixed-integer nonlinear optimization: Algorithmic advances and applications, IMA volumes in Mathematics and its Applications, volume 154, 427-444, 2012. Stefan Vigerske Decomposition of Multistage Stochastic Programs and a Constraint Integer Programming Approach to Mixed-Integer Nonlinear Programming PhD Thesis, Humboldt-University Berlin, 2012, submitted. Pietro Belotti and Andrew J. Miller and Mahdi Namazifar Linear inequalities for bounded products of variables SIAG/OPT Views-and-News 22:1, 1-8, 2011.
typedef struct SCIP_QuadVarEventData	SCIP_QUADVAREVENTDATA

typedef struct SCIP_QuadVarTerm	SCIP_QUADVARTERM

typedef struct SCIP_BilinTerm	SCIP_BILINTERM

typedef struct SCIP_RowPrep	SCIP_ROWPREP

SCIP_RETCODE	SCIPincludeQuadconsUpgrade (SCIP scip, SCIP_DECL_QUADCONSUPGD((quadconsupgd)), int priority, SCIP_Bool active, const char *conshdlrname)

SCIP_RETCODE	SCIPcreateConsQuadratic (SCIP scip, SCIP_CONS cons, const char name, int nlinvars, SCIP_VAR *linvars, SCIP_Real lincoefs, int nquadterms, SCIP_VAR quadvars1, SCIP_VAR quadvars2, SCIP_Real *quadcoeffs, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable)

SCIP_RETCODE	SCIPcreateConsBasicQuadratic (SCIP scip, SCIP_CONS cons, const char name, int nlinvars, SCIP_VAR *linvars, SCIP_Real lincoefs, int nquadterms, SCIP_VAR quadvars1, SCIP_VAR quadvars2, SCIP_Real *quadcoefs, SCIP_Real lhs, SCIP_Real rhs)

SCIP_RETCODE	SCIPcreateConsQuadratic2 (SCIP scip, SCIP_CONS cons, const char name, int nlinvars, SCIP_VAR *linvars, SCIP_Real lincoefs, int nquadvarterms, SCIP_QUADVARTERM quadvarterms, int nbilinterms, SCIP_BILINTERM bilinterms, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable)

SCIP_RETCODE	SCIPcreateConsBasicQuadratic2 (SCIP scip, SCIP_CONS cons, const char name, int nlinvars, SCIP_VAR *linvars, SCIP_Real lincoefs, int nquadvarterms, SCIP_QUADVARTERM quadvarterms, int nbilinterms, SCIP_BILINTERM bilinterms, SCIP_Real lhs, SCIP_Real rhs)

void	SCIPaddConstantQuadratic (SCIP scip, SCIP_CONS cons, SCIP_Real constant)

SCIP_RETCODE	SCIPaddLinearVarQuadratic (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real coef)

SCIP_RETCODE	SCIPaddQuadVarQuadratic (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real lincoef, SCIP_Real sqrcoef)

SCIP_RETCODE	SCIPaddQuadVarLinearCoefQuadratic (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real coef)

SCIP_RETCODE	SCIPaddSquareCoefQuadratic (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real coef)

SCIP_RETCODE	SCIPaddBilinTermQuadratic (SCIP scip, SCIP_CONS cons, SCIP_VAR var1, SCIP_VAR var2, SCIP_Real coef)

SCIP_RETCODE	SCIPgetNlRowQuadratic (SCIP scip, SCIP_CONS cons, SCIP_NLROW **nlrow)

int	SCIPgetNLinearVarsQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetLinearVarsQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_Real *	SCIPgetCoefsLinearVarsQuadratic (SCIP scip, SCIP_CONS cons)

int	SCIPgetNQuadVarTermsQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_QUADVARTERM *	SCIPgetQuadVarTermsQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPsortQuadVarTermsQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPfindQuadVarTermQuadratic (SCIP scip, SCIP_CONS cons, SCIP_VAR var, int pos)

int	SCIPgetNBilinTermsQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_BILINTERM *	SCIPgetBilinTermsQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetLhsQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetRhsQuadratic (SCIP scip, SCIP_CONS cons)

int	SCIPgetLinvarMayDecreaseQuadratic (SCIP scip, SCIP_CONS cons)

int	SCIPgetLinvarMayIncreaseQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPcheckCurvatureQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_Bool	SCIPisConvexQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_Bool	SCIPisConcaveQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPgetViolationQuadratic (SCIP scip, SCIP_CONS cons, SCIP_SOL sol, SCIP_Real violation)

SCIP_Bool	SCIPisLinearLocalQuadratic (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPaddToNlpiProblemQuadratic (SCIP scip, SCIP_CONS cons, SCIP_NLPI nlpi, SCIP_NLPIPROBLEM nlpiprob, SCIP_HASHMAP *scipvar2nlpivar, SCIP_Bool names)

SCIP_RETCODE	SCIPchgLhsQuadratic (SCIP scip, SCIP_CONS cons, SCIP_Real lhs)

SCIP_RETCODE	SCIPchgRhsQuadratic (SCIP scip, SCIP_CONS cons, SCIP_Real rhs)

SCIP_RETCODE	SCIPgetFeasibilityQuadratic (SCIP scip, SCIP_CONS cons, SCIP_SOL sol, SCIP_Real feasibility)

SCIP_RETCODE	SCIPgetActivityQuadratic (SCIP scip, SCIP_CONS cons, SCIP_SOL sol, SCIP_Real activity)

SCIP_RETCODE	SCIPchgLinearCoefQuadratic (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real coef)

SCIP_RETCODE	SCIPchgSquareCoefQuadratic (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real coef)

SCIP_RETCODE	SCIPchgBilinCoefQuadratic (SCIP scip, SCIP_CONS cons, SCIP_VAR var1, SCIP_VAR var2, SCIP_Real coef)

int	SCIPgetNAllBilinearTermsQuadratic (SCIP *scip)

SCIP_RETCODE	SCIPgetAllBilinearTermsQuadratic (SCIP scip, SCIP_VAR RESTRICT x, SCIP_VAR RESTRICT y, int RESTRICT nbilinterms, int RESTRICT nunderests, int RESTRICT noverests, SCIP_Real *maxnonconvexity)

SCIP_RETCODE	SCIPaddBilinearIneqQuadratic (SCIP scip, SCIP_VAR x, SCIP_VAR y, int idx, SCIP_Real xcoef, SCIP_Real ycoef, SCIP_Real constant, SCIP_Bool success)

#define	SCIP_DECL_QUADCONSUPGD(x)

Set Packing/Partitioning/Covering Constraints
This constraint handler handles three special classes of linear constraints, namely set partitioning, set packing, and set covering constraints. For a set of binary variables \(x_i, i=1,\dots,n\), a set partitioning constraint has the form \[ \sum_{i=1}^n x_i = 1, \] a set packing constraint has the form \[ \sum_{i=1}^n x_i \le 1, \] and a set covering constraint has the form \[ \sum_{i=1}^n x_i \ge 1. \]
enum	SCIP_SetppcType { SCIP_SETPPCTYPE_PARTITIONING = 0, SCIP_SETPPCTYPE_PACKING = 1, SCIP_SETPPCTYPE_COVERING = 2 }

typedef enum SCIP_SetppcType	SCIP_SETPPCTYPE

SCIP_RETCODE	SCIPcreateConsSetpart (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR **vars, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicSetpart (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR **vars)

SCIP_RETCODE	SCIPcreateConsSetpack (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR **vars, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicSetpack (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR **vars)

SCIP_RETCODE	SCIPcreateConsSetcover (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR **vars, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicSetcover (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR **vars)

SCIP_RETCODE	SCIPaddCoefSetppc (SCIP scip, SCIP_CONS cons, SCIP_VAR *var)

int	SCIPgetNVarsSetppc (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsSetppc (SCIP scip, SCIP_CONS cons)

SCIP_SETPPCTYPE	SCIPgetTypeSetppc (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetDualsolSetppc (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetDualfarkasSetppc (SCIP scip, SCIP_CONS cons)

SCIP_ROW *	SCIPgetRowSetppc (SCIP scip, SCIP_CONS cons)

int	SCIPgetNFixedonesSetppc (SCIP scip, SCIP_CONS cons)

int	SCIPgetNFixedzerosSetppc (SCIP scip, SCIP_CONS cons)

Second Order Cone Constraints
This constraint handler implements second order cone constraints of the form \[ \sqrt{\gamma + \sum_{i=1}^{n} (\alpha_i\, (x_i + \beta_i))^2} \leq \alpha_{n+1}\, (x_{n+1}+\beta_{n+1}) \] Here, \(\gamma \geq 0\) and either \(x_{n+1} \geq -\beta_{n+1}, \alpha_{n+1} \geq 0\) or \(x_{n+1} \leq -\beta_{n+1}, \alpha_{n+1} \leq 0\). Constraints are enforced by separation, where cuts are generated by linearizing the (convex) nonlinear function on the left-hand-side of the constraint. Further, a linear outer-approximation (which includes new variables) based on Ben-Tal & Nemirovski or Glineur can be added. See also Timo Berthold and Stefan Heinz and Stefan Vigerske Extending a CIP framework to solve MIQCPs In: Jon Lee and Sven Leyffer (eds.), Mixed-integer nonlinear optimization: Algorithmic advances and applications, IMA volumes in Mathematics and its Applications, volume 154, 427-444, 2012. Aharon Ben-Tal and Arkadi Nemirovski On Polyhedral Approximations of the Second-order Cone Mathematics of Operations Research 26:2, 193-205, 2001 François Glineur Computational experiments with a linear approximation of second order cone optimization Technical Report 2000:1, Faculté Polytechnique de Mons, Belgium
SCIP_RETCODE	SCIPcreateConsSOC (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_Real coefs, SCIP_Real offsets, SCIP_Real constant, SCIP_VAR rhsvar, SCIP_Real rhscoeff, SCIP_Real rhsoffset, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable)

SCIP_RETCODE	SCIPcreateConsBasicSOC (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_Real coefs, SCIP_Real offsets, SCIP_Real constant, SCIP_VAR rhsvar, SCIP_Real rhscoeff, SCIP_Real rhsoffset)

SCIP_RETCODE	SCIPgetNlRowSOC (SCIP scip, SCIP_CONS cons, SCIP_NLROW **nlrow)

int	SCIPgetNLhsVarsSOC (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetLhsVarsSOC (SCIP scip, SCIP_CONS cons)

SCIP_Real *	SCIPgetLhsCoefsSOC (SCIP scip, SCIP_CONS cons)

SCIP_Real *	SCIPgetLhsOffsetsSOC (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetLhsConstantSOC (SCIP scip, SCIP_CONS cons)

SCIP_VAR *	SCIPgetRhsVarSOC (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetRhsCoefSOC (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetRhsOffsetSOC (SCIP scip, SCIP_CONS cons)

SCIP_RETCODE	SCIPaddToNlpiProblemSOC (SCIP scip, SCIP_CONS cons, SCIP_NLPI nlpi, SCIP_NLPIPROBLEM nlpiprob, SCIP_HASHMAP *scipvar2nlpivar, SCIP_Bool names)

Specially Ordered Set (SOS) Type 1 Constraints
A specially ordered set of type 1 (SOS1) is a sequence of variables such that at most one variable is nonzero. The special case of two variables arises, for instance, from equilibrium or complementary conditions like \(x \cdot y = 0\). Note that it is in principle allowed that a variable appears twice, but it then can be fixed to 0.
SCIP_RETCODE	SCIPcreateConsSOS1 (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_Real weights, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicSOS1 (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_Real weights)

SCIP_RETCODE	SCIPaddVarSOS1 (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real weight)

SCIP_RETCODE	SCIPappendVarSOS1 (SCIP scip, SCIP_CONS cons, SCIP_VAR *var)

int	SCIPgetNVarsSOS1 (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsSOS1 (SCIP scip, SCIP_CONS cons)

SCIP_Real *	SCIPgetWeightsSOS1 (SCIP scip, SCIP_CONS cons)

SCIP_DIGRAPH *	SCIPgetConflictgraphSOS1 (SCIP_CONSHDLR *conshdlr)

int	SCIPgetNSOS1Vars (SCIP_CONSHDLR *conshdlr)

SCIP_Bool	SCIPvarIsSOS1 (SCIP_CONSHDLR conshdlr, SCIP_VAR var)

int	SCIPvarGetNodeSOS1 (SCIP_CONSHDLR conshdlr, SCIP_VAR var)

SCIP_VAR *	SCIPnodeGetVarSOS1 (SCIP_DIGRAPH *conflictgraph, int node)

SCIP_RETCODE	SCIPmakeSOS1sFeasible (SCIP scip, SCIP_CONSHDLR conshdlr, SCIP_SOL sol, SCIP_Bool changed, SCIP_Bool *success)

Specially Ordered Set (SOS) Type 2 Constraints
A specially ordered set of type 2 (SOS2) is a sequence of variables such that at most two variables are nonzero and if two variables are nonzero they must be adjacent in the specified sequence. Note that it is in principle allowed that a variable appears twice, but it then can be fixed to 0 if it is at least two apart in the sequence.
SCIP_RETCODE	SCIPcreateConsSOS2 (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_Real weights, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicSOS2 (SCIP scip, SCIP_CONS cons, const char name, int nvars, SCIP_VAR *vars, SCIP_Real weights)

SCIP_RETCODE	SCIPaddVarSOS2 (SCIP scip, SCIP_CONS cons, SCIP_VAR *var, SCIP_Real weight)

SCIP_RETCODE	SCIPappendVarSOS2 (SCIP scip, SCIP_CONS cons, SCIP_VAR *var)

int	SCIPgetNVarsSOS2 (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsSOS2 (SCIP scip, SCIP_CONS cons)

SCIP_Real *	SCIPgetWeightsSOS2 (SCIP scip, SCIP_CONS cons)

Superindicator Constraints
Superindicator constraints are constraints of the form \[ x_i = 1 \Rightarrow C(x) \] where \( x_i \) is a binary variable and \( C(\dot) \) a constraint. The superindicator constraint is satisfied if and only if x_i is zero or C is satisfied.
SCIP_RETCODE	SCIPcreateConsSuperindicator (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR binvar, SCIP_CONS slackcons, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicSuperindicator (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR binvar, SCIP_CONS slackcons)

SCIP_VAR *	SCIPgetBinaryVarSuperindicator (SCIP_CONS *cons)

SCIP_CONS *	SCIPgetSlackConsSuperindicator (SCIP_CONS *cons)

SCIP_RETCODE	SCIPtransformMinUC (SCIP scip, SCIP_Bool success)

	SCIP_DECL_DIALOGEXEC (SCIPdialogExecChangeMinUC)

Symresack Constraints
Given a permutation that acts on the order of the variables of a (mixed) 0/1-program such that the permutation is a symmetry of the program, this constraint handler can be used to handle the symmetries corresponding to the permutation. The symmetries are handled by enforcing that a binary solution is lexicographically not smaller than its permutation. In a presolving step, we check whether the permutation acts only on binary points. Otherwise, we eliminate the non-binary variables from the permutation. Furthermore, we delete fixed points from the permutation. Moreover, the constraint handler checks whether each cycle of the permutation is contained in a set packing or partitioning constraint. In this case, the symresack is strengthened to a ppsymresack and strong symmetry handling inequalities are added during the initialization of the constraint handler. Precondition The permutation is encoded by an array perm for which perm[i] = j if and only if the image of i under the permutation is j. The permutation given to the constraint handler has to be a symmetry of the underlying problem. This is NOT checked by the constraint handler.
SCIP_RETCODE	SCIPcreateSymbreakCons (SCIP scip, SCIP_CONS cons, const char name, int perm, SCIP_VAR *vars, int nvars, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsSymresack (SCIP scip, SCIP_CONS cons, const char name, int perm, SCIP_VAR *vars, int nvars, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicSymresack (SCIP scip, SCIP_CONS cons, const char name, int perm, SCIP_VAR *vars, int nvars)

Variable Bound Constraints
This constraint handler handles a special type of linear constraints, namely variable bound constraints. A variable bound constraint has the form \[ lhs \leq x + c y \leq rhs \] with coefficient \(c \in Q\), \(lhs\in Q \cup \{-\infty\}\), \(rhs\in Q \cup \{\infty\}\), and decision variables \(x\) (non-binary) and \(y\) (binary or integer).
SCIP_RETCODE	SCIPcreateConsVarbound (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR var, SCIP_VAR vbdvar, SCIP_Real vbdcoef, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicVarbound (SCIP scip, SCIP_CONS cons, const char name, SCIP_VAR var, SCIP_VAR vbdvar, SCIP_Real vbdcoef, SCIP_Real lhs, SCIP_Real rhs)

SCIP_Real	SCIPgetLhsVarbound (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetRhsVarbound (SCIP scip, SCIP_CONS cons)

SCIP_VAR *	SCIPgetVarVarbound (SCIP scip, SCIP_CONS cons)

SCIP_VAR *	SCIPgetVbdvarVarbound (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetVbdcoefVarbound (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetDualsolVarbound (SCIP scip, SCIP_CONS cons)

SCIP_Real	SCIPgetDualfarkasVarbound (SCIP scip, SCIP_CONS cons)

SCIP_ROW *	SCIPgetRowVarbound (SCIP scip, SCIP_CONS cons)

XOR Constraints
This constraint handler deals with "xor" constraint. These are constraint of the form: \[ rhs = x_1 \oplus x_2 \oplus \dots \oplus x_n \] where \(x_i\) is a binary variable for all \(i\) and \(rhs\) is bool. The variables \(x\)'s are called operators. This constraint is satisfied if \(rhs\) is TRUE and an odd number of the operators are TRUE or if the \(rhs\) is FALSE and a even number of operators are TRUE. Hence, if the sum of \(rhs\) and operators is even.
SCIP_RETCODE	SCIPcreateConsXor (SCIP scip, SCIP_CONS cons, const char name, SCIP_Bool rhs, int nvars, SCIP_VAR **vars, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable, SCIP_Bool stickingatnode)

SCIP_RETCODE	SCIPcreateConsBasicXor (SCIP scip, SCIP_CONS cons, const char name, SCIP_Bool rhs, int nvars, SCIP_VAR **vars)

int	SCIPgetNVarsXor (SCIP scip, SCIP_CONS cons)

SCIP_VAR **	SCIPgetVarsXor (SCIP scip, SCIP_CONS cons)

SCIP_VAR *	SCIPgetIntVarXor (SCIP scip, SCIP_CONS cons)

SCIP_Bool	SCIPgetRhsXor (SCIP scip, SCIP_CONS cons)

Macro Definition Documentation

◆ SCIP_DECL_SOLVECUMULATIVE

#define SCIP_DECL_SOLVECUMULATIVE ( x )

Value:

SCIP_RETCODE x (int njobs, SCIP_Real* ests, SCIP_Real* lsts, SCIP_Real* objvals, \
      int* durations, int* demands, int capacity, int hmin, int hmax, \
      SCIP_Real timelimit, SCIP_Real memorylimit, SCIP_Longint maxnodes, \
      SCIP_Bool* solved, SCIP_Bool* infeasible, SCIP_Bool* unbounded, SCIP_Bool* error)

solves given cumulative condition as independent sub problem

Note: The time and memory limit should be respected.; If the problem was solved to the earliest start times (ests) and latest start times (lsts) array contain the solution values; If the problem was not solved these two arrays contain the global bounds at the time the sub solver was interrupted.

input:

njobs : number of jobs (activities)
objvals : array of objective coefficients for each job (linear objective function), or NULL if none
durations : array of durations
demands : array of demands
capacity : cumulative capacity
hmin : left bound of time axis to be considered (including hmin)
hmax : right bound of time axis to be considered (not including hmax)
timelimit : time limit for solving in seconds
memorylimit : memory limit for solving in mega bytes (MB)
maxnodes : maximum number of branch-and-bound nodes to solve the single cumulative constraint (-1: no limit)

input/output:

ests : array of earliest start times for each job
lsts : array of latest start times for each job

output:

solved : pointer to store if the problem is solved (to optimality)
infeasible : pointer to store if the problem is infeasible
unbounded : pointer to store if the problem is unbounded
error : pointer to store if an error occurred

Definition at line 347 of file cons_cumulative.h.

◆ SCIP_DECL_LINCONSUPGD

#define SCIP_DECL_LINCONSUPGD ( x )

Value:

SCIP_RETCODE x (SCIP* scip, SCIP_CONS* cons, int nvars, SCIP_VAR** vars, SCIP_Real* vals, SCIP_Real lhs, SCIP_Real rhs, \
      int nposbin, int nnegbin, int nposint, int nnegint, int nposimpl, int nnegimpl, int nposimplbin, int nnegimplbin, int nposcont, int nnegcont, \
      int ncoeffspone, int ncoeffsnone, int ncoeffspint, int ncoeffsnint, int ncoeffspfrac, int ncoeffsnfrac, \
      SCIP_Real poscoeffsum, SCIP_Real negcoeffsum, SCIP_Bool integral, SCIP_CONS** upgdcons)

upgrading method for linear constraints into more specific constraints

input:

scip : SCIP main data structure
cons : the linear constraint to upgrade
nvars : number of variables in the constraint
vars : array with constraint variables
vals : array with constraint coefficients
lhs : left hand side of linear constraint
rhs : right hand side of linear constraint
nposbin : number of binary variables with positive coefficient
nnegbin : number of binary variables with negative coefficient
nposint : number of integer variables with positive coefficient
nnegint : number of integer variables with negative coefficient
nposimpl : number of implicit integer variables with positive coefficient (including implicit binary variables)
nnegimpl : number of implicit integer variables with negative coefficient (including implicit binary variables)
nposimplbin : number of implicit binary variables with positive coefficient
nnegimplbin : number of implicit binary variables with negative coefficient
nposcont : number of continuous variables with positive coefficient
nnegcont : number of continuous variables with negative coefficient
ncoeffspone : number of +1 coefficients
ncoeffsnone : number of -1 coefficients
ncoeffspint : number of positive integral coefficients other than +1
ncoeffsnint : number of negative integral coefficients other than -1
ncoeffspfrac : number of positive fractional coefficients
ncoeffsnfrac : number of negative fractional coefficients
poscoeffsum : sum of all positive coefficients
negcoeffsum : sum of all negative coefficients
integral : TRUE iff constraints activity value is always integral
upgdcons : pointer to store the upgraded constraint

Definition at line 111 of file cons_linear.h.

Referenced by consdataEnsureVarsSize().

◆ SCIP_DECL_QUADCONSUPGD

#define SCIP_DECL_QUADCONSUPGD ( x )

Value:

SCIP_RETCODE x (SCIP* scip, SCIP_CONS* cons, \
      int nbinlin, int nbinquad, int nintlin, int nintquad, int nimpllin, int nimplquad, int ncontlin, int ncontquad, \
      SCIP_Bool integral, int* nupgdconss, SCIP_CONS** upgdconss, int upgdconsssize, SCIP_PRESOLTIMING presoltiming)

upgrading method for quadratic constraints into more specific constraints

the method might upgrade a quadratic constraint into a set of quadratic constraints the caller provided an array upgdconss to store upgrade constraints the length of upgdconss is given by upgdconsssize if an upgrade is not possible, set *nupgdconss to zero if more than upgdconsssize many constraints shall replace cons, the function should return the required number as negated value in *nupgdconss i.e., if cons should be replaced by 3 constraints, the function should set *nupgdconss to -3 and return with SCIP_OKAY

input:

scip : SCIP main data structure
cons : the quadratic constraint to upgrade
nbinlin : number of binary variables in linear part
nbinquad : number of binary variables in quadratic part
nintlin : number of integer variables in linear part
nintquad : number of integer variables in quadratic part
nimpllin : number of implicit integer variables in linear part
nimplquad : number of implicit integer variables in quadratic part
ncontlin : number of continuous variables in linear part
ncontquad : number of continuous variables in quadratic part
integral : TRUE iff constraints activity value is always integral
nupgdconss : pointer to store number of constraints that replace this constraint
upgdconss : array to store constraints that replace this constraint
upgdconsssize : length of the provided upgdconss array
presoltiming : current presolve timing

Definition at line 175 of file cons_quadratic.h.

Typedef Documentation

◆ SCIP_LINCONSUPGRADE

typedef struct SCIP_LinConsUpgrade SCIP_LINCONSUPGRADE

linear constraint update method

Definition at line 78 of file cons_linear.h.

◆ SCIP_ORBITOPETYPE

typedef enum SCIP_OrbitopeType SCIP_ORBITOPETYPE

Definition at line 82 of file cons_orbitope.h.

◆ SCIP_LINEARCONSTYPE

typedef enum SCIP_LinearConsType SCIP_LINEARCONSTYPE

Definition at line 81 of file cons_pseudoboolean.h.

◆ SCIP_QUADVAREVENTDATA

typedef struct SCIP_QuadVarEventData SCIP_QUADVAREVENTDATA

event data for variable bound changes in quadratic constraints

Definition at line 100 of file cons_quadratic.h.

◆ SCIP_QUADVARTERM

typedef struct SCIP_QuadVarTerm SCIP_QUADVARTERM

Definition at line 116 of file cons_quadratic.h.

◆ SCIP_BILINTERM

typedef struct SCIP_BilinTerm SCIP_BILINTERM

Definition at line 127 of file cons_quadratic.h.

◆ SCIP_ROWPREP

typedef struct SCIP_RowPrep SCIP_ROWPREP

Definition at line 145 of file cons_quadratic.h.

◆ SCIP_SETPPCTYPE

typedef enum SCIP_SetppcType SCIP_SETPPCTYPE

Definition at line 82 of file cons_setppc.h.

Enumeration Type Documentation

◆ SCIP_BIVAR_CONVEXITY

enum SCIP_BIVAR_CONVEXITY

Enumerator
SCIP_BIVAR_ALLCONVEX
SCIP_BIVAR_1CONVEX_INDEFINITE
SCIP_BIVAR_CONVEX_CONCAVE
SCIP_BIVAR_UNKNOWN

Definition at line 74 of file cons_bivariate.h.

◆ SCIP_OrbitopeType

enum SCIP_OrbitopeType

type of orbitope constraint: full, packing, or partitioning orbitope

Enumerator
SCIP_ORBITOPETYPE_FULL	constraint is a full orbitope constraint: rowsum(x) unrestricted
SCIP_ORBITOPETYPE_PARTITIONING	constraint is a partitioning orbitope constraint: rowsum(x) == 1
SCIP_ORBITOPETYPE_PACKING	constraint is a packing orbitope constraint: rowsum(x) <= 1

Definition at line 76 of file cons_orbitope.h.

◆ SCIP_LinearConsType

enum SCIP_LinearConsType

solution status after solving LP

Enumerator
SCIP_LINEARCONSTYPE_INVALIDCONS	this is no valid linear constraint type
SCIP_LINEARCONSTYPE_LINEAR	this is the common linear constraint
SCIP_LINEARCONSTYPE_LOGICOR	this is a logicor constraint
SCIP_LINEARCONSTYPE_KNAPSACK	this is a knapsack constraint
SCIP_LINEARCONSTYPE_SETPPC	this is a setppc constraint

Definition at line 68 of file cons_pseudoboolean.h.

◆ SCIP_SetppcType

enum SCIP_SetppcType

type of setppc constraint: set partitioning, set packing, or set covering

Enumerator
SCIP_SETPPCTYPE_PARTITIONING	constraint is a set partitioning constraint: sum(x) == 1
SCIP_SETPPCTYPE_PACKING	constraint is a set packing constraint: sum(x) <= 1
SCIP_SETPPCTYPE_COVERING	constraint is a set covering constraint: sum(x) >= 1

Definition at line 76 of file cons_setppc.h.

Function Documentation

◆ SCIPcreateConsAbspower()

SCIP_RETCODE SCIPcreateConsAbspower	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	x,
		SCIP_VAR *	z,
		SCIP_Real	exponent,
		SCIP_Real	xoffset,
		SCIP_Real	zcoef,
		SCIP_Real	lhs,
		SCIP_Real	rhs,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a absolute power constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
x	nonlinear variable x in constraint
z	linear variable z in constraint
exponent	exponent n of \|x+offset\|^n term in constraint
xoffset	offset in \|x+offset\|^n term in constraint
zcoef	coefficient of z in constraint
lhs	left hand side of constraint
rhs	right hand side of constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are seperated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 7172 of file cons_abspower.c.

References BMSclearMemory, CONSHDLR_NAME, NULL, pow(), REALABS, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPallocBlockMemory, SCIPcreateCons(), SCIPcreateConsBasicAbspower(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPisEQ(), SCIPisInfinity(), SCIPisZero(), SCIPmarkDoNotMultaggrVar(), SCIPvarIsActive(), square(), and x.

Referenced by presolveFindDuplicates(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIP_DECL_EXPRGRAPHNODEREFORM(), SCIP_DECL_NONLINCONSUPGD(), SCIP_DECL_QUADCONSUPGD(), SCIPcreateConsBasicAbspower(), and SCIPincludeConshdlrAbspower().

◆ SCIPcreateConsBasicAbspower()

SCIP_RETCODE SCIPcreateConsBasicAbspower	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	x,
		SCIP_VAR *	z,
		SCIP_Real	exponent,
		SCIP_Real	xoffset,
		SCIP_Real	zcoef,
		SCIP_Real	lhs,
		SCIP_Real	rhs
	)

creates and captures an absolute power constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsAbspower(); all flags can be set via SCIPconsSetFLAGNAME-methods in scip.h

See also: SCIPcreateConsAbspower() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures an absolute power constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsAbspower(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsAbspower() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
x	nonlinear variable x in constraint
z	linear variable z in constraint
exponent	exponent n of \|x+offset\|^n term in constraint
xoffset	offset in \|x+offset\|^n term in constraint
zcoef	coefficient of z in constraint
lhs	left hand side of constraint
rhs	right hand side of constraint

Definition at line 7273 of file cons_abspower.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPcreateConsAbspower(), SCIPgetNlRowAbspower(), and TRUE.

Referenced by SCIPcreateConsAbspower(), and setupProblem().

◆ SCIPgetNlRowAbspower()

SCIP_RETCODE SCIPgetNlRowAbspower	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_NLROW **	nlrow
	)

gets the absolute power constraint as a nonlinear row representation

Parameters

scip	SCIP data structure
cons	constraint
nlrow	a buffer where to store pointer to nonlinear row

Definition at line 7295 of file cons_abspower.c.

References CONSHDLR_NAME, createNlRow(), NULL, SCIP_CALL, SCIP_OKAY, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPgetNonlinearVarAbspower().

Referenced by SCIPcreateConsBasicAbspower().

◆ SCIPgetNonlinearVarAbspower()

SCIP_VAR* SCIPgetNonlinearVarAbspower	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets nonlinear variable x in absolute power constraint

Parameters

scip	SCIP data structure
cons	absolute power constraint

Definition at line 7321 of file cons_abspower.c.

References CONSHDLR_NAME, NULL, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPgetLinearVarAbspower().

Referenced by SCIPgetNlRowAbspower(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetLinearVarAbspower()

SCIP_VAR* SCIPgetLinearVarAbspower	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets linear variable z in absolute power constraint

Parameters

scip	SCIP data structure
cons	absolute power constraint

Definition at line 7338 of file cons_abspower.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPgetExponentAbspower().

Referenced by SCIPgetNonlinearVarAbspower(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetExponentAbspower()

SCIP_Real SCIPgetExponentAbspower	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets exponent in power term in absolute power constraint

Parameters

scip	SCIP data structure
cons	absolute power constraint

Definition at line 7355 of file cons_abspower.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPgetOffsetAbspower().

Referenced by SCIPgetLinearVarAbspower(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetOffsetAbspower()

SCIP_Real SCIPgetOffsetAbspower	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets offset in power term in absolute power constraint

Parameters

scip	SCIP data structure
cons	absolute power constraint

Definition at line 7372 of file cons_abspower.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPgetCoefLinearAbspower().

Referenced by SCIPgetExponentAbspower(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetCoefLinearAbspower()

SCIP_Real SCIPgetCoefLinearAbspower	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets coefficient of linear variable in absolute power constraint

Parameters

scip	SCIP data structure
cons	absolute power constraint

Definition at line 7389 of file cons_abspower.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPgetLhsAbspower().

Referenced by SCIPgetOffsetAbspower(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetLhsAbspower()

SCIP_Real SCIPgetLhsAbspower	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets left hand side in absolute power constraint

Parameters

scip	SCIP data structure
cons	absolute power constraint

Definition at line 7406 of file cons_abspower.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPgetRhsAbspower().

Referenced by SCIPgetCoefLinearAbspower(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetRhsAbspower()

SCIP_Real SCIPgetRhsAbspower	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets right hand side in absolute power constraint

Parameters

scip	SCIP data structure
cons	absolute power constraint

Definition at line 7423 of file cons_abspower.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPgetViolationAbspower().

Referenced by SCIPgetLhsAbspower(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetViolationAbspower()

SCIP_Real SCIPgetViolationAbspower	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SOL *	sol
	)

gets the absolute violation of a absolute power constraint by a solution

Parameters

scip	SCIP data structure
cons	absolute power constraint
sol	LP solution

Definition at line 7440 of file cons_abspower.c.

References CONSHDLR_NAME, NULL, pow(), REALABS, SCIP_Real, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPdebugMsg, SCIPgetSolVal(), and SIGN.

Referenced by SCIPgetRhsAbspower().

◆ SCIPcreateConsAnd()

SCIP_RETCODE SCIPcreateConsAnd	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	resvar,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures an and constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a AND-constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
resvar	resultant variable of the operation
nvars	number of operator variables in the constraint
vars	array with operator variables of constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 5008 of file cons_and.c.

References ARTIFICIALVARNAMEPREFIX, consdataCreate(), CONSHDLR_NAME, FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIP_VARTYPE_BINARY, SCIP_VARTYPE_IMPLINT, SCIPchgVarType(), SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicAnd(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPisTransformed(), SCIPvarGetName(), SCIPvarGetProbvar(), and SCIPvarGetType().

Referenced by CREATE_CONSTRAINT(), createAndAddAndCons(), extractGates(), findAggregation(), presolveTryAddAND(), presolveTryAddLinearReform(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIP_DECL_EXPRGRAPHNODEREFORM(), SCIPcreateConsBasicAnd(), SCIPincludeConshdlrAnd(), setObjective(), and upgradeCons().

◆ SCIPcreateConsBasicAnd()

SCIP_RETCODE SCIPcreateConsBasicAnd	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	resvar,
		int	nvars,
		SCIP_VAR **	vars
	)

creates and captures an and constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsAnd(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsAnd() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures an AND-constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsAnd(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsAnd() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
resvar	resultant variable of the operation
nvars	number of operator variables in the constraint
vars	array with operator variables of constraint

Definition at line 5118 of file cons_and.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPcreateConsAnd(), SCIPgetNVarsAnd(), and TRUE.

Referenced by SCIPcreateConsAnd().

◆ SCIPgetNVarsAnd()

int SCIPgetNVarsAnd	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets number of variables in and constraint

gets number of variables in AND-constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5137 of file cons_and.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVarsAnd().

Referenced by checkAndConss(), checkOrigPbCons(), chgLhs(), chgRhs(), computeAndConstraintInfos(), computeConsAndDataChanges(), computeSymmetryGroup(), consdataFree(), consdataPrint(), countNonlinearities(), createCoveringProblem(), printAndCons(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSGETNVARS(), SCIP_DECL_CONSGETVARS(), SCIPcreateConsBasicAnd(), SCIPcreateConsPseudobooleanWithConss(), SCIPwriteMps(), SCIPwritePip(), transformToOrig(), and writeOpbConstraints().

◆ SCIPgetVarsAnd()

SCIP_VAR** SCIPgetVarsAnd	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of variables in and constraint

gets array of variables in AND-constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5161 of file cons_and.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetResultantAnd().

Referenced by checkAndConss(), checkOrigPbCons(), chgLhs(), chgRhs(), computeAndConstraintInfos(), computeConsAndDataChanges(), computeSymmetryGroup(), consdataFree(), consdataPrint(), countNonlinearities(), createCoveringProblem(), printAndCons(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSGETVARS(), SCIPcreateConsPseudobooleanWithConss(), SCIPgetNVarsAnd(), SCIPwriteMps(), SCIPwritePip(), transformToOrig(), and writeOpbConstraints().

◆ SCIPgetResultantAnd()

SCIP_VAR* SCIPgetResultantAnd	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the resultant variable in and constraint

gets the resultant variable in AND-constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5186 of file cons_and.c.

References CONSHDLR_NAME, NULL, SCIP_Bool, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPisAndConsSorted().

Referenced by addCliques(), addCoefTerm(), checkAndConss(), checkOrigPbCons(), computeAndConstraintInfos(), computeSymmetryGroup(), consdataCreate(), consdataFree(), copyConsPseudoboolean(), correctConshdlrdata(), correctLocksAndCaptures(), countNonlinearities(), createAndAddAndCons(), createCoveringProblem(), getLinVarsAndAndRess(), lockRoundingAndCons(), printAndCons(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSINIT(), SCIP_DECL_CONSLOCK(), SCIP_DECL_SORTPTRCOMP(), SCIPcreateConsPseudoboolean(), SCIPcreateConsPseudobooleanWithConss(), SCIPgetVarsAnd(), SCIPwriteMps(), SCIPwritePip(), transformToOrig(), tryUpgradingSetppc(), unlockRoundingAndCons(), and updateConsanddataUses().

◆ SCIPisAndConsSorted()

SCIP_Bool SCIPisAndConsSorted	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

return if the variables of the AND-constraint are sorted with respect to their indices

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5209 of file cons_and.c.

References CONSHDLR_NAME, FALSE, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPsortAndCons().

Referenced by computeConsAndDataChanges(), and SCIPgetResultantAnd().

◆ SCIPsortAndCons()

SCIP_RETCODE SCIPsortAndCons	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

sort the variables of the AND-constraint with respect to their indices

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5233 of file cons_and.c.

References consdataSort(), CONSHDLR_NAME, NULL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPABORT, SCIPchgAndConsCheckFlagWhenUpgr(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by computeConsAndDataChanges(), and SCIPisAndConsSorted().

◆ SCIPchgAndConsCheckFlagWhenUpgr()

SCIP_RETCODE SCIPchgAndConsCheckFlagWhenUpgr	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_Bool	flag
	)

when 'upgrading' the given AND-constraint, should the check flag for the upgraded constraint be set to TRUE, even if the check flag of this AND-constraint is set to FALSE?

Parameters

scip	SCIP data structure
cons	constraint data
flag	should an arising constraint from the given AND-constraint be checked, even if the check flag of the AND-constraint is set to FALSE

Definition at line 5262 of file cons_and.c.

References CONSHDLR_NAME, NULL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPABORT, SCIPchgAndConsRemovableFlagWhenUpgr(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by createAndAddAndCons(), and SCIPsortAndCons().

◆ SCIPchgAndConsRemovableFlagWhenUpgr()

SCIP_RETCODE SCIPchgAndConsRemovableFlagWhenUpgr	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_Bool	flag
	)

when 'upgrading' the given AND-constraint, should the removable flag for the upgraded constraint be set to FALSE, even if the removable flag of this AND-constraint is set to TRUE?

Parameters

scip	SCIP data structure
cons	constraint data
flag	should an arising constraint from the given AND-constraint be not removable, even if the removable flag of the AND-constraint is set to TRUE

Definition at line 5293 of file cons_and.c.

References CONSHDLR_NAME, NULL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by createAndAddAndCons(), and SCIPchgAndConsCheckFlagWhenUpgr().

◆ SCIPconsBendersEnforceSolution()

SCIP_RETCODE SCIPconsBendersEnforceSolution	(	SCIP *	scip,
		SCIP_SOL *	sol,
		SCIP_CONSHDLR *	conshdlr,
		SCIP_RESULT *	result,
		SCIP_BENDERSENFOTYPE	type,
		SCIP_Bool	checkint
	)

enforces Benders' constraints for given solution

This method is called from cons_benderslp and cons_benders. If the method is called from cons_benderslp, then the solutions are not guaranteed to be integer feasible. This is because the default priority is set greater than the integer constraint handler. If this method is called from cons_benders, then, because the default enforcement priority is set less than that of the integer constraint handler, then it can be assumed that the solutions are integer feasible.

The checkint flag indicates whether integer feasibility can be assumed. If it is not assumed, i.e. checkint == FALSE, then only the convex relaxations of the subproblems are solved. If integer feasibility is assumed, i.e. checkint == TRUE, then the convex relaxations and the full CIP are solved to generate Benders' cuts and check solution feasibility.

Parameters

scip	the SCIP instance
sol	the primal solution to enforce, or NULL for the current LP/pseudo sol
conshdlr	the constraint handler
result	the result of the enforcement
type	the type of solution being enforced
checkint	should integrality be considered when checking the subproblems

Definition at line 222 of file cons_benders.c.

References constructValidSolution(), FALSE, NULL, SCIP_BENDERSENFOTYPE_CHECK, SCIP_BENDERSENFOTYPE_LP, SCIP_BENDERSENFOTYPE_PSEUDO, SCIP_BENDERSENFOTYPE_RELAX, SCIP_Bool, SCIP_CALL, SCIP_DECL_CONSHDLRCOPY(), SCIP_DIDNOTRUN, SCIP_FEASIBLE, SCIP_INFEASIBLE, SCIP_OKAY, SCIPbendersCutLP(), SCIPbendersCutPseudo(), SCIPbendersCutRelaxation(), SCIPgetBenders(), SCIPgetNActiveBenders(), SCIPsolveBendersSubproblems(), and SCIPwarningMessage().

Referenced by constructValidSolution(), SCIP_DECL_CONSENFOLP(), SCIP_DECL_CONSENFOPS(), and SCIP_DECL_CONSENFORELAX().

◆ SCIPcreateConsBivariate()

SCIP_RETCODE SCIPcreateConsBivariate	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_EXPRTREE *	f,
		SCIP_BIVAR_CONVEXITY	convextype,
		SCIP_VAR *	z,
		SCIP_Real	zcoef,
		SCIP_Real	lhs,
		SCIP_Real	rhs,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a bivariate constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
f	expression tree specifying bivariate function f(x,y)
convextype	kind of convexity of f(x,y)
z	linear variable in constraint
zcoef	coefficient of linear variable
lhs	left hand side of constraint
rhs	right hand side of constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are seperated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 7953 of file cons_bivariate.c.

References BMSclearMemory, CONSHDLR_NAME, FALSE, NULL, REALABS, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPallocBlockMemory, SCIPblkmem(), SCIPcreateCons(), SCIPcreateConsBasicBivariate(), SCIPerrorMessage, SCIPexprtreeCopy(), SCIPexprtreeGetNVars(), SCIPexprtreeGetVars(), SCIPfindConshdlr(), and SCIPisInfinity().

Referenced by createConsFromMonomial(), createConsFromQuadTerm(), SCIP_DECL_CONSCOPY(), SCIPcreateConsBasicBivariate(), and SCIPincludeConshdlrBivariate().

◆ SCIPcreateConsBasicBivariate()

SCIP_RETCODE SCIPcreateConsBasicBivariate	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_EXPRTREE *	f,
		SCIP_BIVAR_CONVEXITY	convextype,
		SCIP_VAR *	z,
		SCIP_Real	zcoef,
		SCIP_Real	lhs,
		SCIP_Real	rhs
	)

creates and captures an absolute power constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsBivariate(); all flags can be set via SCIPconsSetFLAGNAME-methods in cons.h

See also: SCIPcreateConsBivariate() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures an absolute power constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsBivariate(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsBivariate() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
f	expression tree specifying bivariate function f(x,y)
convextype	kind of convexity of f(x,y)
z	linear variable in constraint
zcoef	coefficient of linear variable
lhs	left hand side of constraint
rhs	right hand side of constraint

Definition at line 8037 of file cons_bivariate.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPcreateConsBivariate(), SCIPgetLinearVarBivariate(), and TRUE.

Referenced by SCIPcreateConsBivariate().

◆ SCIPgetLinearVarBivariate()

SCIP_VAR* SCIPgetLinearVarBivariate	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the linear variable of a bivariate constraint, or NULL if no such variable

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 8058 of file cons_bivariate.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetLinearCoefBivariate().

Referenced by SCIPcreateConsBasicBivariate(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetLinearCoefBivariate()

SCIP_Real SCIPgetLinearCoefBivariate	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the coefficients of the linear variable of a bivariate constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 8070 of file cons_bivariate.c.

References NULL, SCIPconsGetData(), and SCIPgetExprtreeBivariate().

Referenced by SCIPgetLinearVarBivariate(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetExprtreeBivariate()

SCIP_EXPRTREE* SCIPgetExprtreeBivariate	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the expression tree of a bivariate constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 8082 of file cons_bivariate.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetLhsBivariate().

Referenced by SCIPgetLinearCoefBivariate(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetLhsBivariate()

SCIP_Real SCIPgetLhsBivariate	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the left hand side of a bivariate constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 8094 of file cons_bivariate.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetRhsBivariate().

Referenced by SCIPgetExprtreeBivariate(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetRhsBivariate()

SCIP_Real SCIPgetRhsBivariate	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the right hand side of a bivariate constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 8106 of file cons_bivariate.c.

References NULL, and SCIPconsGetData().

Referenced by SCIPgetLhsBivariate(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPcreateConsBounddisjunction()

SCIP_RETCODE SCIPcreateConsBounddisjunction	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_BOUNDTYPE *	boundtypes,
		SCIP_Real *	bounds,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a bound disjunction constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	variables of the literals in the constraint
boundtypes	types of bounds of the literals (lower or upper bounds)
bounds	bounds of the literals
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 3339 of file cons_bounddisjunction.c.

References consdataCreate(), CONSHDLR_NAME, isOverlapping(), NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPboundtypeOpposite(), SCIPcreateCons(), SCIPcreateConsBasicBounddisjunction(), SCIPerrorMessage, and SCIPfindConshdlr().

Referenced by addLocalConss(), addLowerboundCons(), addSplitcons(), adjustOversizedJobBounds(), createConflict(), CUTOFF_CONSTRAINT(), forbidFixation(), readBounds(), readSemicontinuous(), readVariables(), SCIP_DECL_CONFLICTEXEC(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIP_DECL_CONSPRESOL(), SCIP_DECL_QUADCONSUPGD(), SCIPcreateConsBasicBounddisjunction(), and SCIPincludeConshdlrBounddisjunction().

◆ SCIPcreateConsBasicBounddisjunction()

SCIP_RETCODE SCIPcreateConsBasicBounddisjunction	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_BOUNDTYPE *	boundtypes,
		SCIP_Real *	bounds
	)

creates and captures an and constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsBounddisjunction(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsBounddisjunction() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a bound disjunction constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsBounddisjunction(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsBounddisjunction() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	variables of the literals in the constraint
boundtypes	types of bounds of the literals (lower or upper bounds)
bounds	bounds of the literals

Definition at line 3419 of file cons_bounddisjunction.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPcreateConsBounddisjunction(), SCIPgetNVarsBounddisjunction(), and TRUE.

Referenced by createBounddisjunctionCons(), SCIPcreateConsBounddisjunction(), and SCIPreoptApplyGlbConss().

◆ SCIPgetNVarsBounddisjunction()

int SCIPgetNVarsBounddisjunction	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets number of variables in bound disjunction constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 3438 of file cons_bounddisjunction.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVarsBounddisjunction().

Referenced by checkBounddisjunction(), createCoveringProblem(), SCIP_DECL_CONSCOPY(), and SCIPcreateConsBasicBounddisjunction().

◆ SCIPgetVarsBounddisjunction()

SCIP_VAR** SCIPgetVarsBounddisjunction	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of variables in bound disjunction constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 3459 of file cons_bounddisjunction.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetBoundtypesBounddisjunction().

Referenced by checkBounddisjunction(), createCoveringProblem(), saveConsBounddisjuction(), SCIP_DECL_CONSCOPY(), and SCIPgetNVarsBounddisjunction().

◆ SCIPgetBoundtypesBounddisjunction()

SCIP_BOUNDTYPE* SCIPgetBoundtypesBounddisjunction	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of bound types in bound disjunction constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 3480 of file cons_bounddisjunction.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetBoundsBounddisjunction().

Referenced by checkBounddisjunction(), saveConsBounddisjuction(), SCIP_DECL_CONSCOPY(), and SCIPgetVarsBounddisjunction().

◆ SCIPgetBoundsBounddisjunction()

SCIP_Real* SCIPgetBoundsBounddisjunction	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of bounds in bound disjunction constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 3501 of file cons_bounddisjunction.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by checkBounddisjunction(), saveConsBounddisjuction(), SCIP_DECL_CONSCOPY(), and SCIPgetBoundtypesBounddisjunction().

◆ SCIPcreateConsCardinality()

SCIP_RETCODE SCIPcreateConsCardinality	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		int	cardval,
		SCIP_VAR **	indvars,
		SCIP_Real *	weights,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures an cardinality constraint

We set the constraint to not be modifable. If the weights are non NULL, the variables are ordered according to these weights (in ascending order).

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a cardinality constraint

We set the constraint to not be modifable. If the weights are non NULL, the variables are ordered according to these weights (in ascending order).

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries
cardval	number of variables allowed to be nonzero
indvars	indicator variables indicating which variables may be treated as nonzero in cardinality constraint, or NULL if new indicator variables should be introduced automatically
weights	weights determining the variable order, or NULL if variables should be ordered in the same way they were added to the constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 3296 of file cons_cardinality.c.

References CONSHDLR_NAME, FALSE, handleNewVariableCardinality(), NULL, SCIP_Bool, SCIP_CALL, SCIP_MAXSTRLEN, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIP_STAGE_TRANSFORMED, SCIP_VARTYPE_BINARY, SCIPaddVar(), SCIPallocBlockMemory, SCIPallocBlockMemoryArray, SCIPallocBufferArray, SCIPblkmem(), SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicCardinality(), SCIPcreateVar(), SCIPduplicateBlockMemoryArray, SCIPerrorMessage, SCIPfindConshdlr(), SCIPfreeBufferArray, SCIPgetNTotalVars(), SCIPgetStage(), SCIPgetTransformedVar(), SCIPhashmapCreate(), SCIPhashmapExists(), SCIPhashmapGetImage(), SCIPhashmapInsert(), SCIPreleaseVar(), SCIPsnprintf(), SCIPsortRealPtrPtrInt(), SCIPvarGetName(), SCIPvarIsBinary(), and SCIPvarIsTransformed().

Referenced by branchBalancedCardinality(), SCIPcreateConsBasicCardinality(), and SCIPincludeConshdlrCardinality().

◆ SCIPcreateConsBasicCardinality()

SCIP_RETCODE SCIPcreateConsBasicCardinality	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		int	cardval,
		SCIP_VAR **	indvars,
		SCIP_Real *	weights
	)

creates and captures an cardinality constraint in its most basic variant, i. e., with all constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h

See also: SCIPcreateConsCardinality() for the default constraint flag configuration

Warning: Do NOT set the constraint to be modifiable manually, because this might lead to wrong results as the variable array will not be resorted

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a cardinality constraint with all constraint flags set to their default values.

Warning: Do NOT set the constraint to be modifiable manually, because this might lead to wrong results as the variable array will not be resorted

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries
cardval	number of variables allowed to be nonzero
indvars	indicator variables indicating which variables may be treated as nonzero in cardinality constraint, or NULL if new indicator variables should be introduced automatically
weights	weights determining the variable order, or NULL if variables should be ordered in the same way they were added to the constraint

Definition at line 3496 of file cons_cardinality.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIPchgCardvalCardinality(), SCIPcreateConsCardinality(), and TRUE.

Referenced by SCIPcreateConsCardinality().

◆ SCIPchgCardvalCardinality()

SCIP_RETCODE SCIPchgCardvalCardinality	(	SCIP *	scip,
		SCIP_CONS *	cons,
		int	cardval
	)

changes cardinality value of cardinality constraint (i.e., right hand side of cardinality constraint)

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
cardval	number of variables allowed to be nonzero

Definition at line 3517 of file cons_cardinality.c.

References CONSHDLR_NAME, NULL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPaddVarCardinality(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPdebugMsg, and SCIPerrorMessage.

Referenced by SCIPcreateConsBasicCardinality().

◆ SCIPaddVarCardinality()

SCIP_RETCODE SCIPaddVarCardinality	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_VAR *	indvar,
		SCIP_Real	weight
	)

adds variable to cardinality constraint, the position is determined by the given weight

Parameters

scip	SCIP data structure
cons	constraint
var	variable to add to the constraint
indvar	indicator variable indicating whether variable may be treated as nonzero in cardinality constraint (or NULL if this variable should be created automatically)
weight	weight determining position of variable

Definition at line 3546 of file cons_cardinality.c.

References addVarCardinality(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPappendVarCardinality(), SCIPconsGetHdlr(), SCIPconsGetName(), SCIPconshdlrGetData(), SCIPconshdlrGetName(), SCIPdebugMsg, SCIPerrorMessage, and SCIPvarGetName().

Referenced by SCIPchgCardvalCardinality().

◆ SCIPappendVarCardinality()

SCIP_RETCODE SCIPappendVarCardinality	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_VAR *	indvar
	)

appends variable to cardinality constraint

Parameters

scip	SCIP data structure
cons	constraint
var	variable to add to the constraint
indvar	indicator variable indicating whether variable may be treated as nonzero in cardinality constraint (or NULL if this variable should be created automatically)

Definition at line 3583 of file cons_cardinality.c.

References appendVarCardinality(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPconsGetHdlr(), SCIPconsGetName(), SCIPconshdlrGetData(), SCIPconshdlrGetName(), SCIPdebugMsg, SCIPerrorMessage, SCIPgetNVarsCardinality(), and SCIPvarGetName().

Referenced by SCIPaddVarCardinality().

◆ SCIPgetNVarsCardinality()

int SCIPgetNVarsCardinality	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets number of variables in cardinality constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 3618 of file cons_cardinality.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVarsCardinality().

Referenced by SCIPappendVarCardinality().

◆ SCIPgetVarsCardinality()

SCIP_VAR** SCIPgetVarsCardinality	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of variables in cardinality constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 3642 of file cons_cardinality.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetCardvalCardinality().

Referenced by SCIPgetNVarsCardinality().

◆ SCIPgetCardvalCardinality()

int SCIPgetCardvalCardinality	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets cardinality value of cardinality constraint (i.e., right hand side of cardinality constraint)

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 3666 of file cons_cardinality.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetWeightsCardinality().

Referenced by SCIPgetVarsCardinality().

◆ SCIPgetWeightsCardinality()

SCIP_Real* SCIPgetWeightsCardinality	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of weights in cardinality constraint (or NULL if not existent)

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 3689 of file cons_cardinality.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPgetCardvalCardinality().

◆ SCIPcreateConsConjunction()

SCIP_RETCODE SCIPcreateConsConjunction	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nconss,
		SCIP_CONS **	conss,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic
	)

creates and captures a conjunction constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nconss	number of initial constraints in conjunction
conss	initial constraint in conjunction
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.

Definition at line 798 of file cons_conjunction.c.

References consdataCreate(), CONSHDLR_NAME, FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPcreateCons(), SCIPcreateConsBasicConjunction(), SCIPerrorMessage, and SCIPfindConshdlr().

Referenced by SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIPcreateConsBasicConjunction(), and SCIPincludeConshdlrConjunction().

◆ SCIPcreateConsBasicConjunction()

SCIP_RETCODE SCIPcreateConsBasicConjunction	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nconss,
		SCIP_CONS **	conss
	)

creates and captures an and constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsConjunction(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsConjunction() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nconss	number of initial constraints in conjunction
conss	initial constraint in conjunction

Definition at line 847 of file cons_conjunction.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPaddConsElemConjunction(), SCIPcreateConsConjunction(), and TRUE.

Referenced by SCIPcreateConsConjunction().

◆ SCIPaddConsElemConjunction()

SCIP_RETCODE SCIPaddConsElemConjunction	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_CONS *	addcons
	)

adds constraint to the conjunction of constraints

Parameters

scip	SCIP data structure
cons	conjunction constraint
addcons	additional constraint in conjunction

Definition at line 864 of file cons_conjunction.c.

References consdataAddCons(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPcreateConsBasicConjunction().

◆ SCIP_DECL_DIALOGEXEC() [1/4]

SCIP_DECL_DIALOGEXEC ( SCIPdialogExecCountPresolve )

dialog execution method for the count command

Definition at line 1840 of file cons_countsols.c.

References active, CONSHDLR_NAME, FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_DECL_DIALOGEXEC(), SCIP_INVALIDCALL, SCIP_OKAY, SCIP_STAGE_EXITPRESOLVE, SCIP_STAGE_EXITSOLVE, SCIP_STAGE_FREE, SCIP_STAGE_FREETRANS, SCIP_STAGE_INIT, SCIP_STAGE_INITPRESOLVE, SCIP_STAGE_INITSOLVE, SCIP_STAGE_PRESOLVED, SCIP_STAGE_PRESOLVING, SCIP_STAGE_PROBLEM, SCIP_STAGE_SOLVED, SCIP_STAGE_SOLVING, SCIP_STAGE_TRANSFORMED, SCIP_STAGE_TRANSFORMING, SCIPdialoghdlrAddHistory(), SCIPdialoghdlrGetRoot(), SCIPdialogMessage(), SCIPerrorMessage, SCIPgetBoolParam(), SCIPgetIntParam(), SCIPgetStage(), SCIPpresolve(), SCIPsetBoolParam(), SCIPsetIntParam(), SCIPwarningMessage(), and TRUE.

Referenced by SCIP_DECL_CONSLOCK(), SCIP_DECL_DIALOGEXEC(), and writeExpandedSolutions().

◆ SCIP_DECL_DIALOGEXEC() [2/4]

SCIP_DECL_DIALOGEXEC ( SCIPdialogExecCount )

dialog execution method for the count command

Definition at line 1930 of file cons_countsols.c.

References active, CONSHDLR_NAME, FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_DECL_SORTPTRCOMP(), SCIP_INVALIDCALL, SCIP_Longint, SCIP_LONGINT_FORMAT, SCIP_MAXSTRLEN, SCIP_OKAY, SCIP_STAGE_EXITPRESOLVE, SCIP_STAGE_EXITSOLVE, SCIP_STAGE_FREE, SCIP_STAGE_FREETRANS, SCIP_STAGE_INIT, SCIP_STAGE_INITPRESOLVE, SCIP_STAGE_INITSOLVE, SCIP_STAGE_PRESOLVED, SCIP_STAGE_PRESOLVING, SCIP_STAGE_PROBLEM, SCIP_STAGE_SOLVED, SCIP_STAGE_SOLVING, SCIP_STAGE_TRANSFORMED, SCIP_STAGE_TRANSFORMING, SCIP_VERBLEVEL_FULL, SCIPallocBufferArray, SCIPcount(), SCIPdialoghdlrAddHistory(), SCIPdialoghdlrGetRoot(), SCIPdialogMessage(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPfreeBufferArray, SCIPgetBoolParam(), SCIPgetIntParam(), SCIPgetNContVars(), SCIPgetNCountedFeasSubtrees(), SCIPgetNCountedSols(), SCIPgetNCountedSolsstr(), SCIPgetStage(), SCIPisParamFixed(), SCIPpresolve(), SCIPreallocBufferArray, SCIPsetBoolParam(), SCIPsetIntParam(), SCIPunfixParam(), SCIPverbMessage(), SCIPwarningMessage(), and TRUE.

◆ SCIP_DECL_DIALOGEXEC() [3/4]

SCIP_DECL_DIALOGEXEC ( SCIPdialogExecWriteAllsolutions )

execution method of dialog for writing all solutions

Definition at line 2271 of file cons_countsols.c.

References CONSHDLR_NAME, createCountDialog(), FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_ERROR, SCIP_Longint, SCIP_LONGINT_FORMAT, SCIP_MAXSTRLEN, SCIP_OKAY, SCIP_STAGE_EXITPRESOLVE, SCIP_STAGE_EXITSOLVE, SCIP_STAGE_FREE, SCIP_STAGE_FREETRANS, SCIP_STAGE_INIT, SCIP_STAGE_INITPRESOLVE, SCIP_STAGE_INITSOLVE, SCIP_STAGE_PRESOLVED, SCIP_STAGE_PRESOLVING, SCIP_STAGE_PROBLEM, SCIP_STAGE_SOLVED, SCIP_STAGE_SOLVING, SCIP_STAGE_TRANSFORMED, SCIP_STAGE_TRANSFORMING, SCIP_VARTYPE_CONTINUOUS, SCIPallocBufferArray, SCIPconshdlrGetData(), SCIPdialoghdlrAddHistory(), SCIPdialoghdlrClearBuffer(), SCIPdialoghdlrGetRoot(), SCIPdialoghdlrGetWord(), SCIPdialogMessage(), SCIPduplicateBufferArray, SCIPerrorMessage, SCIPfindConshdlr(), SCIPfreeBufferArray, SCIPgetNCountedSols(), SCIPgetNCountedSolsstr(), SCIPgetNOrigVars(), SCIPgetOrigVars(), SCIPgetStage(), SCIPgetTransformedVar(), SCIPinfoMessage(), SCIPreallocBufferArray, SCIPsortDownPtrPtr(), SCIPvarGetName(), SCIPvarGetType(), TRUE, and writeExpandedSolutions().

◆ SCIPcount()

SCIP_RETCODE SCIPcount ( SCIP * scip )

execute counting

Parameters

scip	SCIP data structure

Definition at line 2702 of file cons_countsols.c.

References active, checkParameters(), CONSHDLR_NAME, FALSE, SCIP_Bool, SCIP_CALL, SCIP_Longint, SCIP_OKAY, SCIPgetBoolParam(), SCIPgetNCountedSols(), SCIPsetBoolParam(), SCIPsolve(), and TRUE.

Referenced by SCIP_DECL_DIALOGEXEC(), and SCIPincludeConshdlrCountsols().

◆ SCIPgetNCountedSols()

SCIP_Longint SCIPgetNCountedSols	(	SCIP *	scip,
		SCIP_Bool *	valid
	)

returns number of feasible solutions found as SCIP_Longint; if the number does not fit into a SCIP_Longint the valid flag is set to FALSE

Parameters

scip	SCIP data structure
valid	pointer to store if the return value is valid

Definition at line 2734 of file cons_countsols.c.

References CONSHDLR_NAME, getNCountedSols(), NULL, SCIPconshdlrGetData(), SCIPfindConshdlr(), and SCIPgetNCountedSolsstr().

Referenced by SCIP_DECL_DIALOGEXEC(), SCIP_DECL_DISPOUTPUT(), and SCIPcount().

◆ SCIPgetNCountedSolsstr()

void SCIPgetNCountedSolsstr	(	SCIP *	scip,
		char **	buffer,
		int	buffersize,
		int *	requiredsize
	)

returns number of counted solutions as string

puts the number of counted solutions in the given char* buffer

Parameters

scip	SCIP data structure
buffer	buffer to store the number for counted solutions
buffersize	buffer size
requiredsize	pointer to store the required size

Definition at line 2754 of file cons_countsols.c.

References CONSHDLR_NAME, NULL, pow(), SCIP_Longint, SCIPconshdlrGetData(), SCIPfindConshdlr(), SCIPgetNCountedFeasSubtrees(), and toString().

Referenced by SCIP_DECL_DIALOGEXEC(), and SCIPgetNCountedSols().

◆ SCIPgetNCountedFeasSubtrees()

SCIP_Longint SCIPgetNCountedFeasSubtrees ( SCIP * scip )

returns number of counted feasible subtrees

returns number of counted non trivial feasible subtrees

Parameters

scip	SCIP data structure

Definition at line 2792 of file cons_countsols.c.

References CONSHDLR_NAME, NULL, SCIPconshdlrGetData(), SCIPfindConshdlr(), and SCIPgetCountedSparseSols().

Referenced by SCIP_DECL_DIALOGEXEC(), SCIP_DECL_DISPOUTPUT(), and SCIPgetNCountedSolsstr().

◆ SCIPgetCountedSparseSols()

void SCIPgetCountedSparseSols	(	SCIP *	scip,
		SCIP_VAR ***	vars,
		int *	nvars,
		SCIP_SPARSESOL ***	sols,
		int *	nsols
	)

Method to get the sparse solution.

Note: You get the pointer to the sparse solutions stored in the constraint handler (not a copy).; The sparse solutions are stored w.r.t. the active variables. This are the variables which got not removed during presolving. For none active variables the value has to be computed depending on their aggregation type. See for more details about that Collect all feasible solution.

Parameters

scip	SCIP data structure
vars	pointer to active variable array defining to variable order
nvars	number of active variables
sols	pointer to the solutions
nsols	pointer to number of solutions

Definition at line 2820 of file cons_countsols.c.

References CONSHDLR_NAME, NULL, SCIPconshdlrGetData(), SCIPfindConshdlr(), and SCIPsetParamsCountsols().

Referenced by SCIPgetNCountedFeasSubtrees().

◆ SCIPsetParamsCountsols()

SCIP_RETCODE SCIPsetParamsCountsols ( SCIP * scip )

setting SCIP parameters for such that a valid counting process is possible

Parameters

scip	SCIP data structure

Definition at line 2847 of file cons_countsols.c.

References SCIP_CALL, SCIP_OKAY, SCIP_PARAMEMPHASIS_COUNTER, SCIPsetEmphasis(), and TRUE.

Referenced by SCIPgetCountedSparseSols().

◆ SCIPcreateConsCumulative()

SCIP_RETCODE SCIPcreateConsCumulative	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		int *	durations,
		int *	demands,
		int	capacity,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a cumulative constraint

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables (jobs)
vars	array of integer variable which corresponds to starting times for a job
durations	array containing corresponding durations
demands	array containing corresponding demands
capacity	available cumulative capacity
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are seperated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 13707 of file cons_cumulative.c.

References consdataCatchEvents(), consdataCreate(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIP_STAGE_PROBLEM, SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicCumulative(), SCIPdebugMsg, SCIPerrorMessage, SCIPfindConshdlr(), and SCIPgetStage().

Referenced by CREATE_CONSTRAINT(), createConsCumulative(), createCumulativeCons(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIPcreateConsBasicCumulative(), SCIPcreateSchedulingProblem(), SCIPincludeConshdlrCumulative(), and upgradeCons().

◆ SCIPcreateConsBasicCumulative()

SCIP_RETCODE SCIPcreateConsBasicCumulative	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		int *	durations,
		int *	demands,
		int	capacity
	)

creates and captures an absolute power constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsCumulative(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsCumulative() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a cumulative constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsCumulative(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsCumulative() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables (jobs)
vars	array of integer variable which corresponds to starting times for a job
durations	array containing corresponding durations
demands	array containing corresponding demands
capacity	available cumulative capacity

Definition at line 13788 of file cons_cumulative.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPcreateConsCumulative(), SCIPsetHminCumulative(), and TRUE.

Referenced by SCIPcreateConsCumulative(), and setupAndSolveCumulativeSubscip().

◆ SCIPsetHminCumulative()

SCIP_RETCODE SCIPsetHminCumulative	(	SCIP *	scip,
		SCIP_CONS *	cons,
		int	hmin
	)

set the left bound of effective horizon

set the left bound of the time axis to be considered (including hmin)

Parameters

scip	SCIP data structure
cons	constraint data
hmin	left bound of time axis to be considered

Definition at line 13808 of file cons_cumulative.c.

References CONSHDLR_NAME, NULL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetHminCumulative().

Referenced by createConsCumulative(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIPcreateConsBasicCumulative(), setupAndSolveCumulativeSubscip(), and upgradeCons().

◆ SCIPgetHminCumulative()

int SCIPgetHminCumulative	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the left bound of the effective horizon

returns the left bound of the time axis to be considered

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 13832 of file cons_cumulative.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPsetHmaxCumulative().

Referenced by SCIP_DECL_CONSRESPROP(), and SCIPsetHminCumulative().

◆ SCIPsetHmaxCumulative()

SCIP_RETCODE SCIPsetHmaxCumulative	(	SCIP *	scip,
		SCIP_CONS *	cons,
		int	hmax
	)

set the right bound of the effective horizon

set the right bound of the time axis to be considered (not including hmax)

Parameters

scip	SCIP data structure
cons	constraint data
hmax	right bound of time axis to be considered

Definition at line 13852 of file cons_cumulative.c.

References CONSHDLR_NAME, NULL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetHmaxCumulative().

Referenced by createConsCumulative(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIPgetHminCumulative(), setupAndSolveCumulativeSubscip(), and upgradeCons().

◆ SCIPgetHmaxCumulative()

int SCIPgetHmaxCumulative	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the right bound of effective horizon

returns the right bound of the time axis to be considered

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 13876 of file cons_cumulative.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVarsCumulative().

Referenced by SCIP_DECL_CONSRESPROP(), and SCIPsetHmaxCumulative().

◆ SCIPgetVarsCumulative()

SCIP_VAR** SCIPgetVarsCumulative	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the start time variables of the cumulative constraint

returns the activities of the cumulative constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13896 of file cons_cumulative.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetNVarsCumulative().

Referenced by SCIPgetHmaxCumulative(), and writeFzn().

◆ SCIPgetNVarsCumulative()

int SCIPgetNVarsCumulative	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the number of start time variables of the cumulative constraint

returns the activities of the cumulative constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13917 of file cons_cumulative.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetCapacityCumulative().

Referenced by SCIPgetVarsCumulative(), and writeFzn().

◆ SCIPgetCapacityCumulative()

int SCIPgetCapacityCumulative	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the capacity of the cumulative constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13938 of file cons_cumulative.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetDurationsCumulative().

Referenced by SCIPgetNVarsCumulative(), and writeFzn().

◆ SCIPgetDurationsCumulative()

int* SCIPgetDurationsCumulative	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the durations of the cumulative constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13959 of file cons_cumulative.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetDemandsCumulative().

Referenced by SCIPgetCapacityCumulative(), and writeFzn().

◆ SCIPgetDemandsCumulative()

int* SCIPgetDemandsCumulative	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the demands of the cumulative constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13980 of file cons_cumulative.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPcheckCumulativeCondition(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPgetDurationsCumulative(), and writeFzn().

◆ SCIPcheckCumulativeCondition()

SCIP_RETCODE SCIPcheckCumulativeCondition	(	SCIP *	scip,
		SCIP_SOL *	sol,
		int	nvars,
		SCIP_VAR **	vars,
		int *	durations,
		int *	demands,
		int	capacity,
		int	hmin,
		int	hmax,
		SCIP_Bool *	violated,
		SCIP_CONS *	cons,
		SCIP_Bool	printreason
	)

check for the given starting time variables with their demands and durations if the cumulative conditions for the given solution is satisfied

Parameters

scip	SCIP data structure
sol	primal solution, or NULL for current LP/pseudo solution
nvars	number of variables (jobs)
vars	array of integer variable which corresponds to starting times for a job
durations	array containing corresponding durations
demands	array containing corresponding demands
capacity	available cumulative capacity
hmin	left bound of time axis to be considered (including hmin)
hmax	right bound of time axis to be considered (not including hmax)
violated	pointer to store if the cumulative condition is violated
cons	constraint which is checked
printreason	should the reason for the violation be printed?

Definition at line 14003 of file cons_cumulative.c.

References checkCumulativeCondition(), NULL, SCIP_CALL, SCIP_OKAY, and SCIPnormalizeCumulativeCondition().

Referenced by checkCons(), enfopsCons(), and SCIPgetDemandsCumulative().

◆ SCIPnormalizeCumulativeCondition()

SCIP_RETCODE SCIPnormalizeCumulativeCondition	(	SCIP *	scip,
		int	nvars,
		SCIP_VAR **	vars,
		int *	durations,
		int *	demands,
		int *	capacity,
		int *	nchgcoefs,
		int *	nchgsides
	)

normalize cumulative condition

Parameters

scip	SCIP data structure
nvars	number of start time variables (activities)
vars	array of start time variables
durations	array of durations
demands	array of demands
capacity	pointer to store the changed cumulative capacity
nchgcoefs	pointer to count total number of changed coefficients
nchgsides	pointer to count number of side changes

Definition at line 14028 of file cons_cumulative.c.

References normalizeCumulativeCondition(), SCIP_CALL, SCIP_OKAY, and SCIPsplitCumulativeCondition().

Referenced by SCIP_DECL_CONSPRESOL(), and SCIPcheckCumulativeCondition().

◆ SCIPsplitCumulativeCondition()

SCIP_RETCODE SCIPsplitCumulativeCondition	(	SCIP *	scip,
		int	nvars,
		SCIP_VAR **	vars,
		int *	durations,
		int *	demands,
		int	capacity,
		int *	hmin,
		int *	hmax,
		int *	split
	)

searches for a time point within the cumulative condition were the cumulative condition can be split

Parameters

scip	SCIP data structure
nvars	number of variables (jobs)
vars	array of integer variable which corresponds to starting times for a job
durations	array containing corresponding durations
demands	array containing corresponding demands
capacity	available cumulative capacity
hmin	pointer to store the left bound of the effective horizon
hmax	pointer to store the right bound of the effective horizon
split	point were the cumulative condition can be split

Definition at line 14046 of file cons_cumulative.c.

References computeEffectiveHorizonCumulativeCondition(), SCIP_CALL, SCIP_OKAY, and SCIPpresolveCumulativeCondition().

Referenced by SCIP_DECL_CONSPRESOL(), and SCIPnormalizeCumulativeCondition().

◆ SCIPpresolveCumulativeCondition()

SCIP_RETCODE SCIPpresolveCumulativeCondition	(	SCIP *	scip,
		int	nvars,
		SCIP_VAR **	vars,
		int *	durations,
		int	hmin,
		int	hmax,
		SCIP_Bool *	downlocks,
		SCIP_Bool *	uplocks,
		SCIP_CONS *	cons,
		SCIP_Bool *	irrelevants,
		int *	nfixedvars,
		int *	nchgsides,
		SCIP_Bool *	cutoff
	)

presolve cumulative condition w.r.t. effective horizon by detecting irrelevant variables

Parameters

scip	SCIP data structure
nvars	number of start time variables (activities)
vars	array of start time variables
durations	array of durations
hmin	left bound of time axis to be considered
hmax	right bound of time axis to be considered (not including hmax)
downlocks	array storing if the variable has a down lock, or NULL
uplocks	array storing if the variable has an up lock, or NULL
cons	constraint which gets propagated, or NULL
irrelevants	array mark those variables which are irrelevant for the cumulative condition
nfixedvars	pointer to store the number of fixed variables
nchgsides	pointer to store the number of changed sides
cutoff	buffer to store whether a cutoff is detected

Definition at line 14065 of file cons_cumulative.c.

References presolveConsEst(), presolveConsLct(), SCIP_CALL, SCIP_OKAY, and SCIPpropCumulativeCondition().

Referenced by presolveCumulativeCondition(), and SCIPsplitCumulativeCondition().

◆ SCIPpropCumulativeCondition()

SCIP_RETCODE SCIPpropCumulativeCondition	(	SCIP *	scip,
		SCIP_PRESOLTIMING	presoltiming,
		int	nvars,
		SCIP_VAR **	vars,
		int *	durations,
		int *	demands,
		int	capacity,
		int	hmin,
		int	hmax,
		SCIP_CONS *	cons,
		int *	nchgbds,
		SCIP_Bool *	initialized,
		SCIP_Bool *	explanation,
		SCIP_Bool *	cutoff
	)

propagate the given cumulative condition

Parameters

scip	SCIP data structure
presoltiming	current presolving timing
nvars	number of variables (jobs)
vars	array of integer variable which corresponds to starting times for a job
durations	array containing corresponding durations
demands	array containing corresponding demands
capacity	available cumulative capacity
hmin	left bound of time axis to be considered (including hmin)
hmax	right bound of time axis to be considered (not including hmax)
cons	constraint which gets propagated
nchgbds	pointer to store the number of variable bound changes
initialized	was conflict analysis initialized
explanation	bool array which marks the variable which are part of the explanation if a cutoff was detected, or NULL
cutoff	pointer to store if the cumulative condition is violated

Definition at line 14096 of file cons_cumulative.c.

References CONSHDLR_NAME, FALSE, NULL, propagateCumulativeCondition(), SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPconshdlrGetData(), SCIPerrorMessage, SCIPfindConshdlr(), and SCIPrespropCumulativeCondition().

Referenced by propagateCons(), and SCIPpresolveCumulativeCondition().

◆ SCIPrespropCumulativeCondition()

SCIP_RETCODE SCIPrespropCumulativeCondition	(	SCIP *	scip,
		int	nvars,
		SCIP_VAR **	vars,
		int *	durations,
		int *	demands,
		int	capacity,
		int	hmin,
		int	hmax,
		SCIP_VAR *	infervar,
		int	inferinfo,
		SCIP_BOUNDTYPE	boundtype,
		SCIP_BDCHGIDX *	bdchgidx,
		SCIP_Real	relaxedbd,
		SCIP_Bool *	explanation,
		SCIP_RESULT *	result
	)

resolve propagation w.r.t. the cumulative condition

Parameters

scip	SCIP data structure
nvars	number of start time variables (activities)
vars	array of start time variables
durations	array of durations
demands	array of demands
capacity	cumulative capacity
hmin	left bound of time axis to be considered (including hmin)
hmax	right bound of time axis to be considered (not including hmax)
infervar	the conflict variable whose bound change has to be resolved
inferinfo	the user information
boundtype	the type of the changed bound (lower or upper bound)
bdchgidx	the index of the bound change, representing the point of time where the change took place
relaxedbd	the relaxed bound which is sufficient to be explained
explanation	bool array which marks the variable which are part of the explanation if a cutoff was detected, or NULL
result	pointer to store the result of the propagation conflict resolving call

Definition at line 14145 of file cons_cumulative.c.

References intToInferInfo(), respropCumulativeCondition(), SCIP_CALL, SCIP_OKAY, SCIPvisualizeConsCumulative(), and TRUE.

Referenced by SCIP_DECL_CONSRESPROP(), and SCIPpropCumulativeCondition().

◆ SCIPvisualizeConsCumulative()

SCIP_RETCODE SCIPvisualizeConsCumulative	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

this method visualizes the cumulative structure in GML format

Parameters

scip	SCIP data structure
cons	cumulative constraint

Definition at line 14170 of file cons_cumulative.c.

References b, NULL, SCIP_CALL_TERMINATE, SCIP_FILECREATEERROR, SCIP_MAXSTRLEN, SCIP_OKAY, SCIPblkmem(), SCIPconsGetData(), SCIPconsGetName(), SCIPerrorMessage, SCIPgmlWriteArc(), SCIPgmlWriteClosing(), SCIPgmlWriteNode(), SCIPgmlWriteOpening(), SCIPhashtableCreate(), SCIPhashtableExists(), SCIPhashtableFree(), SCIPhashtableInsert(), SCIPprintSysError(), SCIPsetSolveCumulative(), SCIPsnprintf(), SCIPvarGetLbGlobal(), SCIPvarGetName(), SCIPvarGetNVlbs(), SCIPvarGetNVubs(), SCIPvarGetUbGlobal(), SCIPvarGetVlbVars(), SCIPvarGetVubVars(), and TRUE.

Referenced by SCIP_DECL_CONSINITPRE(), and SCIPrespropCumulativeCondition().

◆ SCIPsetSolveCumulative()

SCIP_RETCODE SCIPsetSolveCumulative	(	SCIP *	scip,
		SCIP_DECL_SOLVECUMULATIVE((*solveCumulative))
	)

sets method to solve an individual cumulative condition

Parameters

scip	SCIP data structure

Definition at line 14273 of file cons_cumulative.c.

References CONSHDLR_NAME, NULL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPconshdlrGetData(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPsolveCumulative(), and solveCumulative().

Referenced by runShell(), and SCIPvisualizeConsCumulative().

◆ SCIPsolveCumulative()

SCIP_RETCODE SCIPsolveCumulative	(	SCIP *	scip,
		int	njobs,
		SCIP_Real *	ests,
		SCIP_Real *	lsts,
		SCIP_Real *	objvals,
		int *	durations,
		int *	demands,
		int	capacity,
		int	hmin,
		int	hmax,
		SCIP_Real	timelimit,
		SCIP_Real	memorylimit,
		SCIP_Longint	maxnodes,
		SCIP_Bool *	solved,
		SCIP_Bool *	infeasible,
		SCIP_Bool *	unbounded,
		SCIP_Bool *	error
	)

solves given cumulative condition as independent sub problem

Note: If the problem was solved to the earliest start times (ests) and latest start times (lsts) array contain the solution values; If the problem was not solved these two arrays contain the global bounds at the time the sub solver was interrupted.

Parameters

scip	SCIP data structure
njobs	number of jobs (activities)
ests	array with the earlier start time for each job
lsts	array with the latest start time for each job
objvals	array of objective coefficients for each job (linear objective function), or NULL if none
durations	array of durations
demands	array of demands
capacity	cumulative capacity
hmin	left bound of time axis to be considered (including hmin)
hmax	right bound of time axis to be considered (not including hmax)
timelimit	time limit for solving in seconds
memorylimit	memory limit for solving in mega bytes (MB)
maxnodes	maximum number of branch-and-bound nodes to solve the single cumulative constraint (-1: no limit)
solved	pointer to store if the problem is solved (to optimality)
infeasible	pointer to store if the problem is infeasible
unbounded	pointer to store if the problem is unbounded
error	pointer to store if an error occurred

Definition at line 14303 of file cons_cumulative.c.

References CONSHDLR_NAME, FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPconshdlrGetData(), SCIPcreateWorstCaseProfile(), SCIPerrorMessage, SCIPfindConshdlr(), and TRUE.

Referenced by applyOptcumulative(), SCIPsetSolveCumulative(), solveCumulative(), and solveIndependentCons().

◆ SCIPcreateWorstCaseProfile()

SCIP_RETCODE SCIPcreateWorstCaseProfile	(	SCIP *	scip,
		SCIP_PROFILE *	profile,
		int	nvars,
		SCIP_VAR **	vars,
		int *	durations,
		int *	demands
	)

creates the worst case resource profile, that is, all jobs are inserted with the earliest start and latest completion time

Parameters

scip	SCIP data structure
profile	resource profile
nvars	number of variables (jobs)
vars	array of integer variable which corresponds to starting times for a job
durations	array containing corresponding durations
demands	array containing corresponding demands

Definition at line 14359 of file cons_cumulative.c.

References computeImpliedEst(), computeImpliedLct(), NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIPallocBufferArray, SCIPblkmem(), SCIPcomputeHmin(), SCIPconvertRealToInt(), SCIPfreeBufferArray, SCIPhashmapCreate(), SCIPhashmapFree(), SCIPhashmapInsertInt(), SCIPprofileInsertCore(), SCIPsortDownIntInt(), SCIPvarGetLbLocal(), and SCIPvarGetUbLocal().

Referenced by computeAlternativeBounds(), computeEffectiveHorizonCumulativeCondition(), propagateCons(), and SCIPsolveCumulative().

◆ SCIPcomputeHmin()

int SCIPcomputeHmin	(	SCIP *	scip,
		SCIP_PROFILE *	profile,
		int	capacity
	)

computes w.r.t. the given worst case resource profile the first time point where the given capacity can be violated

Parameters

scip	SCIP data structure
profile	worst case resource profile
capacity	capacity to check

Definition at line 14438 of file cons_cumulative.c.

References SCIPcomputeHmax(), SCIPprofileGetLoads(), SCIPprofileGetNTimepoints(), and SCIPprofileGetTimepoints().

Referenced by computeAlternativeBounds(), computeEffectiveHorizonCumulativeCondition(), propagateCons(), and SCIPcreateWorstCaseProfile().

◆ SCIPcomputeHmax()

int SCIPcomputeHmax	(	SCIP *	scip,
		SCIP_PROFILE *	profile,
		int	capacity
	)

computes w.r.t. the given worst case resource profile the first time point where the given capacity is satisfied for sure

Parameters

scip	SCIP data structure
profile	worst case profile
capacity	capacity to check

Definition at line 14468 of file cons_cumulative.c.

References SCIPprofileGetLoads(), SCIPprofileGetNTimepoints(), and SCIPprofileGetTimepoints().

Referenced by computeAlternativeBounds(), computeEffectiveHorizonCumulativeCondition(), and SCIPcomputeHmin().

◆ SCIPcreateConsDisjunction()

SCIP_RETCODE SCIPcreateConsDisjunction	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nconss,
		SCIP_CONS **	conss,
		SCIP_CONS *	relaxcons,
		SCIP_Bool	initial,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic
	)

creates and captures a disjunction constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nconss	number of initial constraints in disjunction
conss	initial constraint in disjunction
relaxcons	a conjunction constraint containing the linear relaxation of the disjunction constraint, or NULL
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.

Definition at line 1068 of file cons_disjunction.c.

References consdataCreate(), CONSHDLR_NAME, FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPcreateCons(), SCIPcreateConsBasicDisjunction(), SCIPerrorMessage, and SCIPfindConshdlr().

Referenced by SCIPcreateConsBasicDisjunction(), and SCIPincludeConshdlrDisjunction().

◆ SCIPcreateConsBasicDisjunction()

SCIP_RETCODE SCIPcreateConsBasicDisjunction	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nconss,
		SCIP_CONS **	conss,
		SCIP_CONS *	relaxcons
	)

creates and captures a cumulative constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsDisjunction(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsDisjunction() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nconss	number of initial constraints in disjunction
conss	initial constraint in disjunction
relaxcons	a conjunction constraint containing the linear relaxation of the disjunction constraint, or NULL

Definition at line 1120 of file cons_disjunction.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPaddConsElemDisjunction(), SCIPcreateConsDisjunction(), and TRUE.

Referenced by SCIPcreateConsDisjunction().

◆ SCIPaddConsElemDisjunction()

SCIP_RETCODE SCIPaddConsElemDisjunction	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_CONS *	addcons
	)

adds constraint to the disjunction of constraints

Parameters

scip	SCIP data structure
cons	disjunction constraint
addcons	additional constraint in disjunction

Definition at line 1139 of file cons_disjunction.c.

References consdataAddCons(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPcreateConsBasicDisjunction().

◆ SCIPcreateConsIndicator()

SCIP_RETCODE SCIPcreateConsIndicator	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	binvar,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Real *	vals,
		SCIP_Real	rhs,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures an indicator constraint

Note: binvar is checked to be binary only later. This enables a change of the type in procedures reading an instance.; the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint (indicator or quadratic)
name	name of constraint
binvar	binary indicator variable (or NULL)
nvars	number of variables in the inequality
vars	array with variables of inequality (or NULL)
vals	values of variables in inequality (or NULL)
rhs	rhs of the inequality
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 7309 of file cons_indicator.c.

References consdataCreate(), CONSHDLR_NAME, FALSE, NULL, REALABS, SCIP_Bool, SCIP_CALL, SCIP_INVALIDDATA, SCIP_MAXSTRLEN, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIP_Real, SCIP_VARTYPE_CONTINUOUS, SCIP_VARTYPE_IMPLINT, SCIPaddCoefLinear(), SCIPaddCons(), SCIPaddVar(), SCIPblkmem(), SCIPceil(), SCIPconsAddUpgradeLocks(), SCIPconsGetNUpgradeLocks(), SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicIndicator(), SCIPcreateConsLinear(), SCIPcreateConsQuadratic(), SCIPcreateVar(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPgetNOrigVars(), SCIPhashmapCreate(), SCIPhashmapExists(), SCIPhashmapInsert(), SCIPinfinity(), SCIPisIntegral(), SCIPisTransformed(), SCIPisZero(), SCIPmarkDoNotMultaggrVar(), SCIPsnprintf(), SCIPvarGetType(), SCIPvarIsIntegral(), and TRUE.

Referenced by createIndicatorConstraint(), readIndicators(), SCIP_DECL_CONSINITPRE(), SCIP_DECL_LINCONSUPGD(), SCIPcreateConsBasicIndicator(), SCIPincludeConshdlrIndicator(), and upgradeIndicatorSuperindicator().

◆ SCIPcreateConsBasicIndicator()

SCIP_RETCODE SCIPcreateConsBasicIndicator	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	binvar,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Real *	vals,
		SCIP_Real	rhs
	)

creates and captures an indicator constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsIndicator(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsIndicator() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint (indicator or quadratic)
name	name of constraint
binvar	binary indicator variable (or NULL)
nvars	number of variables in the inequality
vars	array with variables of inequality (or NULL)
vals	values of variables in inequality (or NULL)
rhs	rhs of the inequality

Definition at line 7519 of file cons_indicator.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPcreateConsIndicator(), SCIPcreateConsIndicatorLinCons(), and TRUE.

Referenced by SCIPcreateConsIndicator().

◆ SCIPcreateConsIndicatorLinCons()

SCIP_RETCODE SCIPcreateConsIndicatorLinCons	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	binvar,
		SCIP_CONS *	lincons,
		SCIP_VAR *	slackvar,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures an indicator constraint with given linear constraint and slack variable

Note: binvar is checked to be binary only later. This enables a change of the type in procedures reading an instance.; we assume that slackvar actually appears in lincons and we also assume that it takes the role of a slack variable!; the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
binvar	binary indicator variable (or NULL)
lincons	linear constraint
slackvar	slack variable
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 7548 of file cons_indicator.c.

References consdataCreate(), CONSHDLR_NAME, FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIP_Real, SCIP_VARTYPE_CONTINUOUS, SCIP_VARTYPE_IMPLINT, SCIPcaptureCons(), SCIPcaptureVar(), SCIPconsAddUpgradeLocks(), SCIPconsGetHdlr(), SCIPconsGetNUpgradeLocks(), SCIPconshdlrGetData(), SCIPconshdlrGetName(), SCIPcreateCons(), SCIPcreateConsBasicIndicatorLinCons(), SCIPcreateConsQuadratic(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPgetNVarsLinear(), SCIPgetVarsLinear(), SCIPmarkDoNotMultaggrVar(), SCIPvarGetType(), and TRUE.

Referenced by createSubSCIP(), readIndicators(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIPcreateConsBasicIndicator(), and SCIPcreateConsBasicIndicatorLinCons().

◆ SCIPcreateConsBasicIndicatorLinCons()

SCIP_RETCODE SCIPcreateConsBasicIndicatorLinCons	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	binvar,
		SCIP_CONS *	lincons,
		SCIP_VAR *	slackvar
	)

creates and captures an indicator constraint with given linear constraint and slack variable in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsIndicator(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

Note: binvar is checked to be binary only later. This enables a change of the type in procedures reading an instance.; we assume that slackvar actually appears in lincons and we also assume that it takes the role of a slack variable!; the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

See also: SCIPcreateConsIndicatorLinCons() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
binvar	binary indicator variable (or NULL)
lincons	linear constraint
slackvar	slack variable

Definition at line 7690 of file cons_indicator.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPaddVarIndicator(), SCIPcreateConsIndicatorLinCons(), and TRUE.

Referenced by SCIPcreateConsIndicatorLinCons().

◆ SCIPaddVarIndicator()

SCIP_RETCODE SCIPaddVarIndicator	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	val
	)

adds variable to the inequality of the indicator constraint

Parameters

scip	SCIP data structure
cons	indicator constraint
var	variable to add to the inequality
val	value of variable

Definition at line 7709 of file cons_indicator.c.

References CONSHDLR_NAME, NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIP_VARTYPE_CONTINUOUS, SCIPaddCoefLinear(), SCIPchgVarType(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPgetLinearConsIndicator(), SCIPisIntegral(), SCIPvarGetType(), and SCIPvarIsIntegral().

Referenced by SCIPcreateConsBasicIndicatorLinCons().

◆ SCIPgetLinearConsIndicator()

SCIP_CONS* SCIPgetLinearConsIndicator ( SCIP_CONS * cons )

gets the linear constraint corresponding to the indicator constraint (may be NULL)

Parameters

cons	indicator constraint

Definition at line 7740 of file cons_indicator.c.

References CONSHDLR_NAME, NULL, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPsetLinearConsIndicator().

Referenced by computeRanks(), createSubSCIP(), SCIP_DECL_LINCONSUPGD(), SCIPaddVarIndicator(), SCIPwriteLp(), SCIPwriteMps(), and writeOpbConstraints().

◆ SCIPsetLinearConsIndicator()

SCIP_RETCODE SCIPsetLinearConsIndicator	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_CONS *	lincons
	)

sets the linear constraint corresponding to the indicator constraint (may be NULL)

Parameters

scip	SCIP data structure
cons	indicator constraint
lincons	linear constraint

Definition at line 7757 of file cons_indicator.c.

References CONSHDLR_NAME, FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIP_STAGE_PROBLEM, SCIP_VARTYPE_CONTINUOUS, SCIP_VARTYPE_IMPLINT, SCIPcaptureCons(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetData(), SCIPconshdlrGetName(), SCIPdelCons(), SCIPerrorMessage, SCIPgetBinaryVarIndicator(), SCIPgetNVarsLinear(), SCIPgetStage(), SCIPgetVarsLinear(), SCIPreleaseCons(), SCIPvarGetType(), and TRUE.

Referenced by SCIPgetLinearConsIndicator().

◆ SCIPsetBinaryVarIndicator()

SCIP_RETCODE SCIPsetBinaryVarIndicator	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	binvar
	)

sets binary indicator variable for indicator constraint

Parameters

scip	SCIP data structure
cons	indicator constraint
binvar	binary variable to add to the inequality

Definition at line 7845 of file cons_indicator.c.

References CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_ERROR, SCIP_EVENTTYPE_BOUNDCHANGED, SCIP_EVENTTYPE_GBDCHANGED, SCIP_INVALIDCALL, SCIP_OKAY, SCIP_VARTYPE_BINARY, SCIPcatchVarEvent(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconsGetName(), SCIPconshdlrGetData(), SCIPconshdlrGetName(), SCIPconsIsTransformed(), SCIPerrorMessage, SCIPgetSlackVarIndicator(), SCIPgetTransformedVar(), SCIPvarGetLbLocal(), SCIPvarGetName(), and SCIPvarGetType().

Referenced by SCIPgetBinaryVarIndicator().

◆ SCIPgetBinaryVarIndicator()

SCIP_VAR* SCIPgetBinaryVarIndicator ( SCIP_CONS * cons )

gets binary variable corresponding to indicator constraint

Parameters

cons	indicator constraint

Definition at line 7828 of file cons_indicator.c.

References CONSHDLR_NAME, NULL, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPsetBinaryVarIndicator().

Referenced by computeRanks(), createCoveringProblem(), createSubSCIP(), SCIP_DECL_CONFLICTEXEC(), SCIP_DECL_CONSGETDIVEBDCHGS(), SCIP_DECL_HEUREXEC(), SCIPsetLinearConsIndicator(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), tryOneOpt(), trySolCandidate(), and writeOpbConstraints().

◆ SCIPgetSlackVarIndicator()

SCIP_VAR* SCIPgetSlackVarIndicator ( SCIP_CONS * cons )

gets slack variable corresponding to indicator constraint

Parameters

cons	indicator constraint

Definition at line 7919 of file cons_indicator.c.

References CONSHDLR_NAME, NULL, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPsetSlackVarUb().

Referenced by createSubSCIP(), SCIP_DECL_CONFLICTEXEC(), SCIPsetBinaryVarIndicator(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), and writeOpbConstraints().

◆ SCIPsetSlackVarUb()

SCIP_RETCODE SCIPsetSlackVarUb	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_Real	ub
	)

sets upper bound for slack variable corresponding to indicator constraint

Use with care if you know that the maximal violation of the corresponding constraint is at most ub. This bound might be improved automatically during the solution process.

Precondition

This method should only be called if SCIP is in one of the following stages:

Parameters

scip	SCIP data structure
cons	indicator constraint
ub	upper bound for slack variable

Definition at line 7944 of file cons_indicator.c.

References CONSHDLR_NAME, NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIP_STAGE_PROBLEM, SCIPchgVarUb(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPgetStage(), and SCIPisViolatedIndicator().

Referenced by SCIPgetSlackVarIndicator().

◆ SCIPisViolatedIndicator()

SCIP_Bool SCIPisViolatedIndicator	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SOL *	sol
	)

checks whether indicator constraint is violated w.r.t. sol

Parameters

scip	SCIP data structure
cons	indicator constraint
sol	solution, or NULL to use current node's solution

Definition at line 7970 of file cons_indicator.c.

References FALSE, NULL, SCIPconsGetData(), SCIPconsIsDeleted(), SCIPgetSolVal(), SCIPisFeasPositive(), SCIPmakeIndicatorFeasible(), and TRUE.

Referenced by SCIP_DECL_CONSGETDIVEBDCHGS(), and SCIPsetSlackVarUb().

◆ SCIPmakeIndicatorFeasible()

SCIP_RETCODE SCIPmakeIndicatorFeasible	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SOL *	sol,
		SCIP_Bool *	changed
	)

based on values of other variables, computes slack and binary variable to turn constraint feasible

It will also clean up the solution, i.e., shift slack variable, as follows:

If the inequality is \(a^T x + \gamma\, s \leq \beta\), the value of the slack variable \(s\) to achieve equality is

\[ s^* = \frac{\beta - a^T x^*}{\gamma}, \]

where \(x^*\) is the given solution. In case of \(a^T x + \gamma\, s \geq \alpha\), we arrive at

\[ s^* = \frac{\alpha - a^T x^*}{\gamma}. \]

The typical values of \(\gamma\) in the first case is -1 and +1 in the second case.

Now, let \(\sigma\) be the sign of \(\gamma\) in the first case and \(-\gamma\) in the second case. Thus, if \(\sigma > 0\) and \(s^* < 0\), the inequality cannot be satisfied by a nonnegative value for the slack variable; in this case, we have to leave the values as they are. If \(\sigma < 0\) and \(s^* > 0\), the solution violates the indicator constraint (we can set the slack variable to value \(s^*\)). If \(\sigma < 0\) and \(s^* \leq 0\) or \(\sigma > 0\) and \(s^* \geq 0\), the constraint is satisfied, and we can set the slack variable to 0.

Parameters

scip	SCIP data structure
cons	indicator constraint
sol	solution
changed	pointer to store whether the solution has been changed

Definition at line 8025 of file cons_indicator.c.

References CONSHDLR_NAME, FALSE, NULL, REALABS, SCIP_CALL, SCIP_LOCKTYPE_MODEL, SCIP_OKAY, SCIP_Real, SCIP_STAGE_INITPRESOLVE, SCIP_VARSTATUS_FIXED, SCIP_VARSTATUS_NEGATED, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPconsIsActive(), SCIPgetLhsLinear(), SCIPgetNVarsLinear(), SCIPgetRhsLinear(), SCIPgetSolVal(), SCIPgetStage(), SCIPgetValsLinear(), SCIPgetVarsLinear(), SCIPisFeasEQ(), SCIPisFeasGE(), SCIPisFeasNegative(), SCIPisFeasPositive(), SCIPisFeasZero(), SCIPisInfinity(), SCIPisZero(), SCIPmakeIndicatorsFeasible(), SCIPsetSolVal(), SCIPvarGetLbLocal(), SCIPvarGetNegationVar(), SCIPvarGetNLocksDownType(), SCIPvarGetNLocksUpType(), SCIPvarGetStatus(), TRUE, and varGetObjDelta().

Referenced by SCIP_DECL_CONSCHECK(), SCIPisViolatedIndicator(), and SCIPmakeIndicatorsFeasible().

◆ SCIPmakeIndicatorsFeasible()

SCIP_RETCODE SCIPmakeIndicatorsFeasible	(	SCIP *	scip,
		SCIP_CONSHDLR *	conshdlr,
		SCIP_SOL *	sol,
		SCIP_Bool *	changed
	)

based on values of other variables, computes slack and binary variable to turn all constraints feasible

Parameters

scip	SCIP data structure
conshdlr	indicator constraint handler
sol	solution
changed	pointer to store whether the solution has been changed

Definition at line 8200 of file cons_indicator.c.

References CONSHDLR_NAME, FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIP_STAGE_INITPRESOLVE, SCIPaddLinearConsIndicator(), SCIPconsGetData(), SCIPconshdlrGetConss(), SCIPconshdlrGetName(), SCIPconshdlrGetNConss(), SCIPgetStage(), and SCIPmakeIndicatorFeasible().

Referenced by SCIPmakeIndicatorFeasible(), and SCIPperformGenericDivingAlgorithm().

◆ SCIPaddLinearConsIndicator()

SCIP_RETCODE SCIPaddLinearConsIndicator	(	SCIP *	scip,
		SCIP_CONSHDLR *	conshdlr,
		SCIP_CONS *	lincons
	)

adds additional linear constraint that is not connected with an indicator constraint, but can be used for separation

Parameters

scip	SCIP data structure
conshdlr	indicator constraint handler
lincons	linear constraint

Definition at line 8247 of file cons_indicator.c.

References consdataEnsureAddLinConsSize(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_OKAY, SCIPaddRowIndicator(), SCIPconshdlrGetData(), SCIPconshdlrGetName(), and SCIPconsIsLocal().

Referenced by SCIPmakeIndicatorsFeasible().

◆ SCIPaddRowIndicator()

SCIP_RETCODE SCIPaddRowIndicator	(	SCIP *	scip,
		SCIP_CONSHDLR *	conshdlr,
		SCIP_ROW *	row
	)

adds additional globally valid row that is not connected with an indicator constraint, but can be used for separation

adds additional row that is not connected with an indicator constraint, but can be used for separation

Note: The row is directly added to the alternative polyhedron and is not stored.

Parameters

scip	SCIP data structure
conshdlr	indicator constraint handler
row	row to add

Definition at line 8279 of file cons_indicator.c.

References addAltLPRow(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_OKAY, SCIPconshdlrGetData(), SCIPconshdlrGetName(), SCIPdebugMsg, SCIProwGetName(), and SCIProwIsLocal().

Referenced by SCIP_DECL_CONSINITLP(), SCIPaddLinearConsIndicator(), and separatePoint().

◆ SCIPcreateConsKnapsack()

SCIP_RETCODE SCIPcreateConsKnapsack	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Longint *	weights,
		SCIP_Longint	capacity,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a knapsack constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a knapsack constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()! [SnippetConsCreationKnapsack]

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of items in the knapsack
vars	array with item variables
weights	array with item weights
capacity	capacity of knapsack (right hand side of inequality)
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 13449 of file cons_knapsack.c.

References catchEvents(), consdataCreate(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_Longint, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicKnapsack(), SCIPerrorMessage, SCIPfindConshdlr(), and SCIPisTransformed().

Referenced by createAndAddLinearCons(), createCapacityRestriction(), createMipCpFormulation(), createNormalizedKnapsack(), createRow(), presolRoundCardinality(), and SCIPcreateConsBasicKnapsack().

◆ SCIPcreateConsBasicKnapsack()

SCIP_RETCODE SCIPcreateConsBasicKnapsack	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Longint *	weights,
		SCIP_Longint	capacity
	)

creates and captures a knapsack constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsKnapsack(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsKnapsack() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

! [SnippetConsCreationKnapsack] creates and captures a knapsack constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsKnapsack(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsKnapsack() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of items in the knapsack
vars	array with item variables
weights	array with item weights
capacity	capacity of knapsack

Definition at line 13524 of file cons_knapsack.c.

References FALSE, NULL, SCIP_CALL, SCIP_Longint, SCIP_OKAY, SCIPaddCoefKnapsack(), SCIPcreateConsKnapsack(), and TRUE.

Referenced by createIntervalRelaxation(), createMipFormulation(), initPricing(), SCIP_DECL_SOLVECUMULATIVE(), and SCIPcreateConsKnapsack().

◆ SCIPaddCoefKnapsack()

SCIP_RETCODE SCIPaddCoefKnapsack	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Longint	weight
	)

adds new item to knapsack constraint

Parameters

scip	SCIP data structure
cons	constraint data
var	item variable
weight	item weight

Definition at line 13543 of file cons_knapsack.c.

References addCoef(), CONSHDLR_NAME, SCIP_CALL, SCIP_INVALIDDATA, SCIP_Longint, SCIP_OKAY, SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetCapacityKnapsack().

Referenced by addCoefTerm(), createCapacityRestriction(), createIntervalRelaxation(), createMipCpFormulation(), createMipFormulation(), SCIP_DECL_SOLVECUMULATIVE(), SCIPaddCoefPseudoboolean(), and SCIPcreateConsBasicKnapsack().

◆ SCIPgetCapacityKnapsack()

SCIP_Longint SCIPgetCapacityKnapsack	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the capacity of the knapsack constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13564 of file cons_knapsack.c.

References NULL, SCIP_Longint, SCIPABORT, SCIPchgCapacityKnapsack(), SCIPconsGetData(), and SCIPerrorMessage.

Referenced by addKnapsackConstraints(), checkKnapsack(), computeSymmetryGroup(), createAltLP(), getLinearConsSides(), presolveAddKKTKnapsackConss(), SCIPaddCoefKnapsack(), SCIPconsGetRhs(), SCIPmatrixCreate(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePip(), writeFzn(), writeOpbConstraints(), and writeOpbObjective().

◆ SCIPchgCapacityKnapsack()

SCIP_RETCODE SCIPchgCapacityKnapsack	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_Longint	capacity
	)

changes capacity of the knapsack constraint

Note: This method can only be called during problem creation stage (SCIP_STAGE_PROBLEM)

Parameters

scip	SCIP data structure
cons	constraint data
capacity	new capacity of knapsack

Definition at line 13588 of file cons_knapsack.c.

References CONSHDLR_NAME, NULL, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_STAGE_PROBLEM, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPgetNVarsKnapsack(), and SCIPgetStage().

Referenced by SCIPgetCapacityKnapsack().

◆ SCIPgetNVarsKnapsack()

int SCIPgetNVarsKnapsack	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the number of items in the knapsack constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13617 of file cons_knapsack.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVarsKnapsack().

Referenced by addKnapsackConstraints(), checkKnapsack(), computeSymmetryGroup(), createAltLP(), getLinearConsNVars(), getLinearConsVarsData(), presolveAddKKTKnapsackConss(), SCIPchgCapacityKnapsack(), SCIPmatrixCreate(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), writeFzn(), writeOpbConstraints(), and writeOpbObjective().

◆ SCIPgetVarsKnapsack()

SCIP_VAR** SCIPgetVarsKnapsack	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the array of variables in the knapsack constraint; the user must not modify this array!

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13638 of file cons_knapsack.c.

References CONSHDLR_NAME, NULL, SCIP_Longint, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetWeightsKnapsack().

Referenced by addKnapsackConstraints(), checkKnapsack(), computeSymmetryGroup(), createAltLP(), getLinearConsVarsData(), presolveAddKKTKnapsackConss(), SCIPgetNVarsKnapsack(), SCIPmatrixCreate(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), writeFzn(), writeOpbConstraints(), and writeOpbObjective().

◆ SCIPgetWeightsKnapsack()

SCIP_Longint* SCIPgetWeightsKnapsack	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the array of weights in the knapsack constraint; the user must not modify this array!

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13659 of file cons_knapsack.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetDualsolKnapsack().

Referenced by addKnapsackConstraints(), checkKnapsack(), computeSymmetryGroup(), createAltLP(), getLinearConsVarsData(), presolveAddKKTKnapsackConss(), SCIPgetConsVals(), SCIPgetVarsKnapsack(), SCIPmatrixCreate(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), writeFzn(), and writeOpbConstraints().

◆ SCIPgetDualsolKnapsack()

SCIP_Real SCIPgetDualsolKnapsack	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the dual solution of the knapsack constraint in the current LP

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13680 of file cons_knapsack.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPgetDualfarkasKnapsack(), and SCIProwGetDualsol().

Referenced by SCIPconsGetDualsol(), and SCIPgetWeightsKnapsack().

◆ SCIPgetDualfarkasKnapsack()

SCIP_Real SCIPgetDualfarkasKnapsack	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the dual Farkas value of the knapsack constraint in the current infeasible LP

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13704 of file cons_knapsack.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPgetRowKnapsack(), and SCIProwGetDualfarkas().

Referenced by SCIPconsGetDualfarkas(), and SCIPgetDualsolKnapsack().

◆ SCIPgetRowKnapsack()

SCIP_ROW* SCIPgetRowKnapsack	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the linear relaxation of the given knapsack constraint; may return NULL if no LP row was yet created; the user must not modify the row!

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 13730 of file cons_knapsack.c.

References NULL, SCIPABORT, SCIPconsGetData(), and SCIPerrorMessage.

Referenced by SCIPconsGetRow(), and SCIPgetDualfarkasKnapsack().

◆ SCIPsolveKnapsackExactly()

SCIP_RETCODE SCIPsolveKnapsackExactly	(	SCIP *	scip,
		int	nitems,
		SCIP_Longint *	weights,
		SCIP_Real *	profits,
		SCIP_Longint	capacity,
		int *	items,
		int *	solitems,
		int *	nonsolitems,
		int *	nsolitems,
		int *	nnonsolitems,
		SCIP_Real *	solval,
		SCIP_Bool *	success
	)

solves knapsack problem in maximization form exactly using dynamic programming; if needed, one can provide arrays to store all selected items and all not selected items

Note: in case you provide the solitems or nonsolitems array you also have to provide the counter part, as well; the algorithm will first compute a greedy solution and terminate if the greedy solution is proven to be optimal. The dynamic programming algorithm runs with a time and space complexity of O(nitems * capacity).

solves knapsack problem in maximization form exactly using dynamic programming; if needed, one can provide arrays to store all selected items and all not selected items

Note: in case you provide the solitems or nonsolitems array you also have to provide the counter part, as well; the algorithm will first compute a greedy solution and terminate if the greedy solution is proven to be optimal. The dynamic programming algorithm runs with a time and space complexity of O(nitems * capacity).

Parameters

scip	SCIP data structure
nitems	number of available items
weights	item weights
profits	item profits
capacity	capacity of knapsack
items	item numbers
solitems	array to store items in solution, or NULL
nonsolitems	array to store items not in solution, or NULL
nsolitems	pointer to store number of items in solution, or NULL
nnonsolitems	pointer to store number of items not in solution, or NULL
solval	pointer to store optimal solution value, or NULL
success	pointer to store if an error occured during solving (normally a memory problem)

Definition at line 1042 of file cons_knapsack.c.

References FALSE, IDX, MAX, NULL, SCIP_Bool, SCIP_CALL, SCIP_Longint, SCIP_LONGINT_FORMAT, SCIP_LONGINT_MAX, SCIP_NOMEMORY, SCIP_OKAY, SCIP_Real, SCIPallocBufferArray, SCIPcalcGreComDiv(), SCIPdebugMsg, SCIPfloor(), SCIPfreeBufferArray, SCIPisGE(), SCIPisIntegral(), SCIPselectWeightedDownRealLongRealInt(), SCIPsolveKnapsackApproximately(), SCIPsortDownRealIntLong(), and TRUE.

Referenced by buildFlowCover(), and getHighestCapacityUsage().

◆ SCIPsolveKnapsackApproximately()

SCIP_RETCODE SCIPsolveKnapsackApproximately	(	SCIP *	scip,
		int	nitems,
		SCIP_Longint *	weights,
		SCIP_Real *	profits,
		SCIP_Longint	capacity,
		int *	items,
		int *	solitems,
		int *	nonsolitems,
		int *	nsolitems,
		int *	nnonsolitems,
		SCIP_Real *	solval
	)

solves knapsack problem in maximization form approximately by solving the LP-relaxation of the problem using Dantzig's method and rounding down the solution; if needed, one can provide arrays to store all selected items and all not selected items

Parameters

scip	SCIP data structure
nitems	number of available items
weights	item weights
profits	item profits
capacity	capacity of knapsack
items	item numbers
solitems	array to store items in solution, or NULL
nonsolitems	array to store items not in solution, or NULL
nsolitems	pointer to store number of items in solution, or NULL
nnonsolitems	pointer to store number of items not in solution, or NULL
solval	pointer to store optimal solution value, or NULL

Definition at line 1541 of file cons_knapsack.c.

References GUBconsCreate(), SCIP_GUBSet::gubconss, SCIP_GUBCons::gubvars, SCIP_GUBSet::ngubconss, SCIP_GUBCons::ngubvars, NULL, SCIP_CALL, SCIP_Longint, SCIP_OKAY, SCIP_Real, SCIPallocBufferArray, SCIPdebugMsg, SCIPfreeBufferArray, SCIPisFeasGT(), SCIPselectWeightedDownRealLongRealInt(), and SCIPvarGetName().

Referenced by getCover(), and SCIPsolveKnapsackExactly().

◆ SCIPseparateKnapsackCuts()

SCIP_RETCODE SCIPseparateKnapsackCuts	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SEPA *	sepa,
		SCIP_VAR **	vars,
		int	nvars,
		SCIP_Longint *	weights,
		SCIP_Longint	capacity,
		SCIP_SOL *	sol,
		SCIP_Bool	usegubs,
		SCIP_Bool *	cutoff,
		int *	ncuts
	)

separates different classes of valid inequalities for the 0-1 knapsack problem

Parameters

scip	SCIP data structure
cons	originating constraint of the knapsack problem, or NULL
sepa	originating separator of the knapsack problem, or NULL
vars	variables in knapsack constraint
nvars	number of variables in knapsack constraint
weights	weights of variables in knapsack constraint
capacity	capacity of knapsack
sol	primal SCIP solution to separate, NULL for current LP solution
usegubs	should GUB information be used for separation?
cutoff	pointer to store whether a cutoff has been detected
ncuts	pointer to add up the number of found cuts

Definition at line 5531 of file cons_knapsack.c.

References FALSE, getCover(), getFeasibleSet(), GUBsetCreate(), GUBsetFree(), GUBsetGetCliquePartition(), makeCoverMinimal(), SCIP_GUBSet::ngubconss, NULL, SCIP_GUBSet::nvars, SCIP_Bool, SCIP_CALL, SCIP_Longint, SCIP_LONGINT_FORMAT, SCIP_OKAY, SCIP_Real, SCIPallocBufferArray, SCIPconsGetName(), SCIPdebugMsg, SCIPdebugMsgPrint, SCIPfreeBufferArray, SCIPgetSolVals(), SCIPincConsAge(), SCIPseparateRelaxedKnapsack(), SCIPvarGetName(), separateSequLiftedMinimalCoverInequality(), separateSupLiftedMinimalCoverInequality(), TRUE, and USESUPADDLIFT.

Referenced by getFeasibleSet(), SCIPseparateRelaxedKnapsack(), and separateCons().

◆ SCIPseparateRelaxedKnapsack()

SCIP_RETCODE SCIPseparateRelaxedKnapsack	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SEPA *	sepa,
		int	nknapvars,
		SCIP_VAR **	knapvars,
		SCIP_Real *	knapvals,
		SCIP_Real	valscale,
		SCIP_Real	rhs,
		SCIP_SOL *	sol,
		SCIP_Bool *	cutoff,
		int *	ncuts
	)

Parameters

scip	SCIP data structure
cons	originating constraint of the knapsack problem, or NULL
sepa	originating separator of the knapsack problem, or NULL
nknapvars	number of variables in the continuous knapsack constraint
knapvars	variables in the continuous knapsack constraint
knapvals	coefficients of the variables in the continuous knapsack constraint
valscale	-1.0 if lhs of row is used as rhs of c. k. constraint, +1.0 otherwise
rhs	right hand side of the continuous knapsack constraint
sol	primal CIP solution, NULL for current LP solution
cutoff	pointer to store whether a cutoff was found
ncuts	pointer to add up the number of found cuts

Definition at line 5748 of file cons_knapsack.c.

References BMSclearMemoryArray, CONSHDLR_NAME, DEFAULT_USEGUBS, FALSE, KNAPSACKRELAX_MAXDELTA, KNAPSACKRELAX_MAXDNOM, KNAPSACKRELAX_MAXSCALE, MAXABSVBCOEF, NULL, REALABS, SCIP_Bool, SCIP_CALL, SCIP_Longint, SCIP_LONGINT_FORMAT, SCIP_OKAY, SCIP_Real, SCIPallocBufferArray, SCIPcalcIntegralScalar(), SCIPconsGetName(), SCIPconshdlrGetData(), SCIPdebug, SCIPdebugMsg, SCIPdebugMsgPrint, SCIPdebugPrintCons, SCIPepsilon(), SCIPfeasFloor(), SCIPfindConshdlr(), SCIPfloor(), SCIPfreeBufferArray, SCIPgetNContVars(), SCIPgetNegatedVar(), SCIPgetNVars(), SCIPgetSolVal(), SCIPgetVars(), SCIPisFeasGT(), SCIPisFeasLT(), SCIPisGE(), SCIPisGT(), SCIPisInfinity(), SCIPisLE(), SCIPisLT(), SCIPreallocBlockMemoryArray, SCIPseparateKnapsackCuts(), SCIPvarGetLbGlobal(), SCIPvarGetLbLocal(), SCIPvarGetName(), SCIPvarGetNVlbs(), SCIPvarGetNVubs(), SCIPvarGetProbindex(), SCIPvarGetUbGlobal(), SCIPvarGetUbLocal(), SCIPvarGetVlbCoefs(), SCIPvarGetVlbConstants(), SCIPvarGetVlbVars(), SCIPvarGetVubCoefs(), SCIPvarGetVubConstants(), SCIPvarGetVubVars(), SCIPvarIsActive(), SCIPvarIsBinary(), separateCons(), and TRUE.

Referenced by addCut(), and SCIPseparateKnapsackCuts().

◆ SCIPincludeLinconsUpgrade()

SCIP_RETCODE SCIPincludeLinconsUpgrade	(	SCIP *	scip,
		SCIP_DECL_LINCONSUPGD((*linconsupgd))	,
		int	priority,
		const char *	conshdlrname
	)

includes a linear constraint update method into the linear constraint handler

Parameters

scip	SCIP data structure
priority	priority of upgrading method
conshdlrname	name of the constraint handler

Definition at line 17494 of file cons_linear.c.

Referenced by SCIPincludeConshdlrIndicator(), SCIPincludeConshdlrLogicor(), SCIPincludeConshdlrVarbound(), and SCIPincludeConshdlrXor().

◆ SCIPcreateConsLinear()

SCIP_RETCODE SCIPcreateConsLinear	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Real *	vals,
		SCIP_Real	lhs,
		SCIP_Real	rhs,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a linear constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of nonzeros in the constraint
vars	array with variables of constraint entries
vals	array with coefficients of constraint entries
lhs	left hand side of constraint
rhs	right hand side of constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 17546 of file cons_linear.c.

References consdataCreate(), CONSHDLR_NAME, FALSE, NULL, REALABS, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIP_Real, SCIP_STAGE_EXITPRESOLVE, SCIPABORT, SCIPcreateCons(), SCIPcreateConsBasicLinear(), SCIPcreateConsLinear(), SCIPduplicateBufferArray, SCIPerrorMessage, SCIPfindConshdlr(), SCIPfreeBufferArray, SCIPgetProbvarLinearSum(), SCIPgetStage(), SCIPinfinity(), SCIPisInfinity(), SCIPreallocBufferArray, and TRUE.

Referenced by addBranchingComplementaritiesSOS1(), addExtendedAsymmetricFormulation(), addExtendedFlowFormulation(), addLocalBranchingConstraint(), addLocalConss(), addScenarioConsToProb(), aggregateConstraints(), applyFixings(), branchOnVertex(), cancelRow(), consdataLinearize(), copyCuts(), CREATE_CONSTRAINT(), createAndAddLinearCons(), createAndAddProofcons(), createConstraints(), createCoveringProblem(), createDegreeConstraints(), createHopConstraint(), createLinearCons(), createMipCpFormulation(), createNAryBranch(), createPrizeConstraints(), createProbOnlyEdge(), createProbSimplified(), createProbSimplifiedTest(), createRows(), createSubSCIP(), createSubscip(), dualPresolve(), execmain(), fixDeleteOrUpgradeCons(), fixVariableZeroNode(), forbidCover(), getFixedVariable(), preprocessConstraintPairs(), presolveCreateBenTalNemirovskiApproxDim3(), presolveCreateGlineurApproxDim3(), presolveFindDuplicates(), presolveFindDuplicatesUpgradeCons(), presolveRemoveFixedVariables(), presolveTryAddLinearReform(), propIndicator(), scipexamples::QueensSolver::QueensSolver(), readCnf(), readConstraints(), readOPBFile(), readRows(), readRowsMop(), replaceByLinearConstraints(), replaceViolatedByLinearConstraints(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSINITPRE(), SCIP_DECL_CONSPRESOL(), SCIP_DECL_NONLINCONSUPGD(), SCIP_DECL_QUADCONSUPGD(), SCIP_DECL_READERREAD(), SCIPcopyConsLinear(), SCIPcreateConsIndicator(), SCIPcreateConsLinear(), SCIPgetVarCopy(), SCIPStpDualAscent(), SCIPStpDualAscentPcMw(), selectVarMultAggrBranching(), setupAndSolveSubscip(), setupSubproblem(), setupSubScip(), tightenBounds(), tightenSingleVar(), tryUpgradingLogicor(), tryUpgradingSetppc(), and upgradeLinearSuperindicator().

◆ SCIPcreateConsBasicLinear()

SCIP_RETCODE SCIPcreateConsBasicLinear	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Real *	vals,
		SCIP_Real	lhs,
		SCIP_Real	rhs
	)

creates and captures a linear constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsLinear(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsLinear() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of nonzeros in the constraint
vars	array with variables of constraint entries
vals	array with coefficients of constraint entries
lhs	left hand side of constraint
rhs	right hand side of constraint

Definition at line 17725 of file cons_linear.c.

Referenced by addLocalBranchingConstraint(), applyRepair(), polyscip::Polyscip::computeNondomPoints(), createAndAddTransferredCut(), createKKTComplementarityBinary(), createKKTComplementarityBounds(), createKKTComplementarityLinear(), createKKTDualCons(), createMasterproblem(), createMIP(), createMipFormulation(), createOriginalproblem(), createProbSimplified(), createProbSimplifiedTest(), createSubproblem(), createSubproblems(), disaggregate(), generateAndApplyBendersCuts(), generateAndApplyBendersIntegerCuts(), generateAndApplyBendersNogoodCut(), readLIBSVM(), SCIPapplyProximity(), SCIPbendersMergeSubproblemIntoMaster(), SCIPcreateConsLinear(), SCIPverifyCircularPatternNLP(), setupAndSolveFiniteSolSubscip(), setupProblem(), and solvePricingMINLP().

◆ SCIPcopyConsLinear()

SCIP_RETCODE SCIPcopyConsLinear	(	SCIP *	scip,
		SCIP_CONS **	cons,
		SCIP *	sourcescip,
		const char *	name,
		int	nvars,
		SCIP_VAR **	sourcevars,
		SCIP_Real *	sourcecoefs,
		SCIP_Real	lhs,
		SCIP_Real	rhs,
		SCIP_HASHMAP *	varmap,
		SCIP_HASHMAP *	consmap,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode,
		SCIP_Bool	global,
		SCIP_Bool *	valid
	)

creates by copying and captures a linear constraint

Parameters

scip	target SCIP data structure
cons	pointer to store the created target constraint
sourcescip	source SCIP data structure
name	name of constraint
nvars	number of variables in source variable array
sourcevars	source variables of the linear constraints
sourcecoefs	coefficient array of the linear constraint, or NULL if all coefficients are one
lhs	left hand side of the linear constraint
rhs	right hand side of the linear constraint
varmap	a SCIP_HASHMAP mapping variables of the source SCIP to corresponding variables of the target SCIP
consmap	a hashmap to store the mapping of source constraints to the corresponding target constraints
initial	should the LP relaxation of constraint be in the initial LP?
separate	should the constraint be separated during LP processing?
enforce	should the constraint be enforced during node processing?
check	should the constraint be checked for feasibility?
propagate	should the constraint be propagated during node processing?
local	is constraint only valid locally?
modifiable	is constraint modifiable (subject to column generation)?
dynamic	is constraint subject to aging?
removable	should the relaxation be removed from the LP due to aging or cleanup?
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node?
global	create a global or a local copy?
valid	pointer to store if the copying was valid

Definition at line 17745 of file cons_linear.c.

References CONSHDLR_NAME, FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_Real, SCIPaddCoefLinear(), SCIPallocBufferArray, SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPcreateConsLinear(), SCIPduplicateBufferArray, SCIPerrorMessage, SCIPfreeBufferArray, SCIPgetProbvarLinearSum(), SCIPgetVarCopy(), SCIPisGT(), SCIPisInfinity(), SCIPreallocBufferArray, SCIPvarGetOrigvarSum(), SCIPvarIsOriginal(), and TRUE.

Referenced by SCIP_DECL_CONSCOPY().

◆ SCIPaddCoefLinear()

SCIP_RETCODE SCIPaddCoefLinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	val
	)

adds coefficient to linear constraint (if it is not zero)

Parameters

scip	SCIP data structure
cons	constraint data
var	variable of constraint entry
val	coefficient of constraint entry

Definition at line 17874 of file cons_linear.c.

References addCoef(), chgLhs(), chgRhs(), CONSHDLR_NAME, NULL, REALABS, SCIP_Bool, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_Real, SCIPABORT, SCIPallocBufferArray, SCIPchgCoefLinear(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconsGetName(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPfreeBufferArray, SCIPgetProbvarLinearSum(), SCIPinfinity(), SCIPisInfinity(), SCIPreallocBufferArray, SCIPvarGetName(), and TRUE.

Referenced by ObjPricerVRP::add_tour_variable(), addAuxiliaryVariableToCut(), addCoefTerm(), addScenarioConsToProb(), addVariable(), applyFixings(), applyRepair(), branchOnVertex(), computeNogoodCut(), computeStandardFeasibilityCut(), computeStandardIntegerOptCut(), consdataLinearize(), createAndAddLinearCons(), createAndAddProofcons(), createAndAddTransferredCut(), createKKTComplementarityBinary(), createKKTComplementarityBounds(), createKKTComplementarityLinear(), createKKTDualCons(), createMasterproblem(), createMIP(), createMipCpFormulation(), createMipFormulation(), createOriginalproblem(), createProbOnlyEdge(), createProbSimplified(), createProbSimplifiedTest(), createSubproblem(), createSubproblems(), createSubSCIP(), createVariables(), execmain(), generateAndApplyBendersCuts(), getBoundConsFromVertices(), presolveAddKKTLinearCons(), presolveAddKKTQuadBilinearTerms(), presolveAddKKTQuadLinearTerms(), presolveAddKKTQuadQuadraticTerms(), pricing(), scipexamples::QueensSolver::QueensSolver(), readCols(), readColsMop(), readIndicators(), readLinearCoefs(), SCIP_DECL_CONSINITPRE(), SCIP_DECL_CONSPRESOL(), SCIP_DECL_NONLINCONSUPGD(), SCIP_DECL_QUADCONSUPGD(), SCIP_DECL_READERREAD(), SCIPaddCoefPseudoboolean(), SCIPaddVarIndicator(), SCIPapplyProximity(), SCIPbendersMergeSubproblemIntoMaster(), SCIPchgCoefLinear(), SCIPcopyConsLinear(), SCIPcreateConsIndicator(), SCIPgetVarCopy(), SCIPprobdataAddNewSol(), SCIPStpDualAscent(), SCIPStpDualAscentPcMw(), SCIPverifyCircularPatternNLP(), setupAndSolveFiniteSolSubscip(), setupAndSolveSubscip(), setupProblem(), setupSubproblem(), setupSubScip(), solvePricingMINLP(), tightenSingleVar(), tryUpgradingLogicor(), and tryUpgradingSetppc().

◆ SCIPchgCoefLinear()

SCIP_RETCODE SCIPchgCoefLinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	val
	)

changes coefficient of variable in linear constraint; deletes the variable if coefficient is zero; adds variable if not yet contained in the constraint

Note: This method may only be called during problem creation stage for an original constraint and variable.; This method requires linear time to search for occurences of the variable in the constraint data.

Parameters

scip	SCIP data structure
cons	constraint data
var	variable of constraint entry
val	new coefficient of constraint entry

Definition at line 18035 of file cons_linear.c.

References chgCoefPos(), delCoefPos(), FALSE, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_Real, SCIP_STAGE_PROBLEM, SCIPaddCoefLinear(), SCIPchgCoefLinear(), SCIPconsGetData(), SCIPconsIsOriginal(), SCIPdelCoefLinear(), SCIPerrorMessage, SCIPgetLhsLinear(), SCIPgetStage(), SCIPisZero(), SCIPvarIsOriginal(), and TRUE.

Referenced by addScenarioVarsAndConsToProb(), SCIPaddCoefLinear(), and SCIPchgCoefLinear().

◆ SCIPdelCoefLinear()

SCIP_RETCODE SCIPdelCoefLinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var
	)

deletes variable from linear constraint

Note: This method may only be called during problem creation stage for an original constraint and variable.; This method requires linear time to search for occurences of the variable in the constraint data.

Parameters

scip	SCIP data structure
cons	constraint data
var	variable of constraint entry

Definition at line 18103 of file cons_linear.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPchgCoefLinear().

◆ SCIPgetLhsLinear()

SCIP_Real SCIPgetLhsLinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets left hand side of linear constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 18119 of file cons_linear.c.

Referenced by addAltLPConstraint(), addLinearConstraints(), addScenarioConsToProb(), addScenarioVarsAndConsToProb(), checkConsnames(), checkLinearConssVarboundSOS1(), computeNogoodCut(), computeStandardFeasibilityCut(), computeStandardIntegerOptCut(), computeSymmetryGroup(), createAltLP(), createAndAddProofcons(), generateAndApplyBendersCuts(), generateAndApplyBendersIntegerCuts(), getLinearConsSides(), presolveAddKKTLinearConss(), presolveAddKKTQuadLinearTerms(), printRangeSection(), readIndicators(), readNonlinearExprs(), readQCMatrix(), readQuadraticCoefs(), readRanges(), readRhs(), saveConsLinear(), SCIP_DECL_CONSLOCK(), SCIP_DECL_CONSPARSE(), SCIP_DECL_PARAMCHGD(), SCIP_DECL_PRESOLEXEC(), SCIPchgCoefLinear(), SCIPconflictstoreCleanNewIncumbent(), SCIPconsGetLhs(), SCIPgetDualSolVal(), SCIPmakeIndicatorFeasible(), SCIPmatrixCreate(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePip(), separatePerspective(), tightenVarsBoundsSOS1(), upgradeIndicatorSuperindicator(), upgradeLinearSuperindicator(), writeFzn(), and writeOpbConstraints().

◆ SCIPgetRhsLinear()

SCIP_Real SCIPgetRhsLinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets right hand side of linear constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 18142 of file cons_linear.c.

Referenced by addAltLPConstraint(), addLinearConstraints(), addScenarioConsToProb(), addScenarioVarsAndConsToProb(), checkLinearConssVarboundSOS1(), computeStandardFeasibilityCut(), computeSymmetryGroup(), createAltLP(), createAndAddProofcons(), getLinearConsSides(), presolveAddKKTLinearConss(), presolveAddKKTQuadLinearTerms(), printRangeSection(), propIndicator(), readIndicators(), readNonlinearExprs(), readQCMatrix(), readQuadraticCoefs(), readRanges(), readRhs(), saveConsLinear(), SCIP_DECL_CONSLOCK(), SCIP_DECL_CONSPARSE(), SCIP_DECL_PARAMCHGD(), SCIP_DECL_PRESOLEXEC(), SCIPapplyProximity(), SCIPconflictstoreCleanNewIncumbent(), SCIPconsGetRhs(), SCIPgetDualSolVal(), SCIPmakeIndicatorFeasible(), SCIPmatrixCreate(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePip(), separatePerspective(), tightenVarsBoundsSOS1(), upgradeIndicatorSuperindicator(), upgradeLinearSuperindicator(), writeFzn(), writeOpbConstraints(), and writeOpbObjective().

◆ SCIPchgLhsLinear()

SCIP_RETCODE SCIPchgLhsLinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_Real	lhs
	)

changes left hand side of linear constraint

Parameters

scip	SCIP data structure
cons	constraint data
lhs	new left hand side

Definition at line 18165 of file cons_linear.c.

References chgRhs(), CONSHDLR_NAME, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by addScenarioVarsAndConsToProb(), applyFixings(), chgLhsLinearCons(), computeNogoodCut(), polyscip::Polyscip::computeNondomPoints(), computeStandardFeasibilityCut(), computeStandardIntegerOptCut(), fixDiscreteVars(), generateAndApplyBendersIntegerCuts(), presolveAddKKTQuadLinearTerms(), readIndicators(), readRanges(), readRhs(), SCIP_DECL_PRESOLEXEC(), SCIPconflictstoreCleanNewIncumbent(), and tryUpgradingLogicor().

◆ SCIPchgRhsLinear()

SCIP_RETCODE SCIPchgRhsLinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_Real	rhs
	)

changes right hand side of linear constraint

Parameters

scip	SCIP data structure
cons	constraint data
rhs	new right hand side

Definition at line 18186 of file cons_linear.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by addScenarioVarsAndConsToProb(), applyFixings(), chgRhsLinearCons(), polyscip::Polyscip::computeNondomPoints(), fixDiscreteVars(), presolveAddKKTQuadLinearTerms(), readRanges(), readRhs(), SCIP_DECL_PRESOLEXEC(), SCIPapplyHeurDualval(), SCIPapplyProximity(), SCIPconflictstoreCleanNewIncumbent(), and tryUpgradingSetppc().

◆ SCIPgetNVarsLinear()

int SCIPgetNVarsLinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the number of variables in the linear constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 18204 of file cons_linear.c.

Referenced by addAltLPConstraint(), addLinearConstraints(), addScenarioConsToProb(), checkLinearConssVarboundSOS1(), computeSymmetryGroup(), createAltLP(), extractLinearValues(), getLinearConsNVars(), getLinearConsVarsData(), presolveAddKKTLinearConss(), propIndicator(), readIndicators(), readNonlinearExprs(), readQCMatrix(), readQuadraticCoefs(), SCIP_DECL_CONSLOCK(), SCIP_DECL_CONSPRESOL(), SCIP_DECL_PARAMCHGD(), SCIPcreateConsIndicatorLinCons(), SCIPmakeIndicatorFeasible(), SCIPmatrixCreate(), SCIPsetLinearConsIndicator(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), separatePerspective(), tightenVarsBoundsSOS1(), upgradeIndicatorSuperindicator(), upgradeLinearSuperindicator(), writeFzn(), writeOpbConstraints(), and writeOpbObjective().

◆ SCIPgetVarsLinear()

SCIP_VAR** SCIPgetVarsLinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the array of variables in the linear constraint; the user must not modify this array!

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 18227 of file cons_linear.c.

Referenced by addAltLPConstraint(), addLinearConstraints(), addScenarioConsToProb(), checkLinearConssVarboundSOS1(), computeSymmetryGroup(), createAltLP(), extractLinearValues(), getLinearConsVarsData(), presolveAddKKTLinearConss(), propIndicator(), readIndicators(), readNonlinearExprs(), readQCMatrix(), readQuadraticCoefs(), saveConsLinear(), SCIP_DECL_CONSLOCK(), SCIP_DECL_CONSPRESOL(), SCIP_DECL_PARAMCHGD(), SCIPcreateConsIndicatorLinCons(), SCIPgetDualSolVal(), SCIPmakeIndicatorFeasible(), SCIPmatrixCreate(), SCIPsetLinearConsIndicator(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), separatePerspective(), tightenVarsBoundsSOS1(), upgradeIndicatorSuperindicator(), upgradeLinearSuperindicator(), writeFzn(), writeOpbConstraints(), and writeOpbObjective().

◆ SCIPgetValsLinear()

SCIP_Real* SCIPgetValsLinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the array of coefficient values in the linear constraint; the user must not modify this array!

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 18250 of file cons_linear.c.

Referenced by addAltLPConstraint(), addLinearConstraints(), addScenarioConsToProb(), checkLinearConssVarboundSOS1(), computeSymmetryGroup(), createAltLP(), extractLinearValues(), getLinearConsVarsData(), presolveAddKKTLinearConss(), propIndicator(), readIndicators(), readNonlinearExprs(), readQCMatrix(), readQuadraticCoefs(), saveConsLinear(), SCIP_DECL_CONSLOCK(), SCIP_DECL_CONSPRESOL(), SCIP_DECL_PARAMCHGD(), SCIPgetConsVals(), SCIPgetDualSolVal(), SCIPmakeIndicatorFeasible(), SCIPmatrixCreate(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), separatePerspective(), tightenVarsBoundsSOS1(), upgradeIndicatorSuperindicator(), upgradeLinearSuperindicator(), writeFzn(), and writeOpbConstraints().

◆ SCIPgetActivityLinear()

SCIP_Real SCIPgetActivityLinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SOL *	sol
	)

gets the activity of the linear constraint in the given solution

Note: if the solution contains values at infinity, this method will return SCIP_INVALID in case the activity comprises positive and negative infinity contributions

Parameters

scip	SCIP data structure
cons	constraint data
sol	solution, or NULL to use current node's solution

Definition at line 18277 of file cons_linear.c.

Referenced by computeNogoodCut(), computeStandardFeasibilityCut(), computeStandardIntegerOptCut(), and generateAndApplyBendersCuts().

◆ SCIPgetFeasibilityLinear()

SCIP_Real SCIPgetFeasibilityLinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SOL *	sol
	)

gets the feasibility of the linear constraint in the given solution

Parameters

scip	SCIP data structure
cons	constraint data
sol	solution, or NULL to use current node's solution

Definition at line 18304 of file cons_linear.c.

◆ SCIPgetDualsolLinear()

SCIP_Real SCIPgetDualsolLinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the dual solution of the linear constraint in the current LP

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 18331 of file cons_linear.c.

Referenced by ObjPricerVRP::pricing(), pricing(), SCIP_DECL_EVENTEXEC(), SCIP_DECL_PRICERREDCOST(), SCIPconsGetDualsol(), and SCIPgetDualSolVal().

◆ SCIPgetDualfarkasLinear()

SCIP_Real SCIPgetDualfarkasLinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the dual Farkas value of the linear constraint in the current infeasible LP

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 18358 of file cons_linear.c.

Referenced by ObjPricerVRP::pricing(), pricing(), and SCIPconsGetDualfarkas().

◆ SCIPgetRowLinear()

SCIP_ROW* SCIPgetRowLinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the linear relaxation of the given linear constraint; may return NULL if no LP row was yet created; the user must not modify the row!

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 18387 of file cons_linear.c.

Referenced by SCIPconsGetRow().

◆ SCIPupgradeConsLinear()

SCIP_RETCODE SCIPupgradeConsLinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_CONS **	upgdcons
	)

tries to automatically convert a linear constraint into a more specific and more specialized constraint

Parameters

scip	SCIP data structure
cons	source constraint to try to convert
upgdcons	pointer to store upgraded constraint, or NULL if not successful

Definition at line 18410 of file cons_linear.c.

Referenced by createAndAddProofcons().

◆ SCIPclassifyConstraintTypesLinear()

SCIP_RETCODE SCIPclassifyConstraintTypesLinear	(	SCIP *	scip,
		SCIP_LINCONSSTATS *	linconsstats
	)

performs linear constraint type classification as used for MIPLIB

iterates through all linear constraints and stores relevant statistics in the linear constraint statistics linconsstats.

Note: only constraints are iterated that belong to the linear constraint handler. If the problem has been presolved already, constraints that were upgraded to more special types such as, e.g., varbound constraints, will not be shown correctly anymore. Similarly, if specialized constraints were created through the API, these are currently not present.

Parameters

scip	SCIP data structure
linconsstats	linear constraint type classification

Definition at line 15107 of file cons_linear.c.

Referenced by SCIP_DECL_DIALOGEXEC().

◆ SCIPcreateConsLinking()

SCIP_RETCODE SCIPcreateConsLinking	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	intvar,
		SCIP_VAR **	binvars,
		int *	vals,
		int	nbinvars,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a linking constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
intvar	integer variable which should be linked
binvars	binary variables, or NULL
vals	coefficients of the binary variables
nbinvars	number of binary variables
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 3284 of file cons_linking.c.

References consdataCreate(), consdataCreateBinvars(), CONSHDLR_NAME, getHashmapKey(), HASHSIZE_BINVARSCONS, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPblkmem(), SCIPconshdlrGetData(), SCIPcreateCons(), SCIPdebugMsg, SCIPerrorMessage, SCIPfindConshdlr(), SCIPgetStage(), SCIPhashmapCreate(), SCIPhashmapExists(), SCIPhashmapInsert(), SCIPisInfinity(), SCIPvarGetLbGlobal(), SCIPvarGetName(), and SCIPvarGetUbGlobal().

Referenced by consdataCollectLinkingCons(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), and SCIPcreateConsBasicLinking().

◆ SCIPcreateConsBasicLinking()

SCIP_RETCODE SCIPcreateConsBasicLinking	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	intvar,
		SCIP_VAR **	binvars,
		int *	vals,
		int	nbinvars
	)

creates and captures a linking constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsLinking(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsLinking() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a linking constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsLinking(); all flags can be set via SCIPsetCons<Flagname>-methods in scip.h

See also: SCIPcreateConsLinking() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
intvar	integer variable which should be linked
binvars	binary variables, or NULL
vals	coefficients of the binary variables
nbinvars	number of binary variables

Definition at line 3376 of file cons_linking.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPcreateConsLinking(), and TRUE.

◆ SCIPexistsConsLinking()

SCIP_Bool SCIPexistsConsLinking	(	SCIP *	scip,
		SCIP_VAR *	intvar
	)

checks if for the given integer variable a linking constraint exists

Parameters

scip	SCIP data structure
intvar	integer variable which should be linked

Definition at line 3395 of file cons_linking.c.

References CONSHDLR_NAME, getHashmapKey(), NULL, SCIPconshdlrGetData(), SCIPfindConshdlr(), and SCIPhashmapExists().

Referenced by collectBinaryVars(), and consdataCollectLinkingCons().

◆ SCIPgetConsLinking()

SCIP_CONS* SCIPgetConsLinking	(	SCIP *	scip,
		SCIP_VAR *	intvar
	)

returns the linking constraint belonging the given integer variable or NULL if it does not exist yet

returns the linking constraint belonging to the given integer variable or NULL if it does not exist yet

Parameters

scip	SCIP data structure
intvar	integer variable which should be linked

Definition at line 3413 of file cons_linking.c.

References CONSHDLR_NAME, getHashmapKey(), NULL, SCIPconshdlrGetData(), SCIPfindConshdlr(), and SCIPhashmapGetImage().

Referenced by collectBinaryVars(), consdataCollectLinkingCons(), and consdataCreate().

◆ SCIPgetIntvarLinking()

SCIP_VAR* SCIPgetIntvarLinking	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the integer variable of the linking constraint

Parameters

scip	SCIP data structure
cons	linking constraint

Definition at line 3434 of file cons_linking.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by computeSymmetryGroup(), and SCIPmatrixCreate().

◆ SCIPgetBinvarsLinking()

SCIP_RETCODE SCIPgetBinvarsLinking	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR ***	binvars,
		int *	nbinvars
	)

returns the binary variables of the linking constraint

Parameters

scip	SCIP data structure
cons	linking constraint
binvars	pointer to store the binary variables array pointer
nbinvars	pointer to store the number of returned binary variables

Definition at line 3455 of file cons_linking.c.

References consdataCreateBinvars(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetData(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by collectBinaryVars(), computeSymmetryGroup(), createCoverCutsTimepoint(), and SCIPmatrixCreate().

◆ SCIPgetNBinvarsLinking()

int SCIPgetNBinvarsLinking	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the number of binary variables of the linking constraint

Parameters

scip	SCIP data structure
cons	linking constraint

Definition at line 3499 of file cons_linking.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

◆ SCIPgetValsLinking()

int* SCIPgetValsLinking	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the coefficients of the binary variables

Parameters

scip	SCIP data structure
cons	linking constraint

Definition at line 3520 of file cons_linking.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by collectBinaryVars(), computeSymmetryGroup(), createCoverCutsTimepoint(), and SCIPmatrixCreate().

◆ SCIPcreateConsLogicor()

SCIP_RETCODE SCIPcreateConsLogicor	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a logic or constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 5166 of file cons_logicor.c.

References consdataCreate(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_EVENTTYPE_VARFIXED, SCIP_INVALIDCALL, SCIP_OKAY, SCIP_STAGE_PRESOLVING, SCIPcatchVarEvent(), SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicLogicor(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPgetStage(), and SCIPisTransformed().

Referenced by addSplitcons(), applyCliqueFixings(), BENDERS_CUTORACLE(), consdataLinearize(), createAndAddLinearCons(), createConflict(), createConflictCons(), createNormalizedLogicor(), extendToCover(), readCnf(), SCIP_DECL_CONFLICTEXEC(), SCIPcreateConsBasicLogicor(), SCIPincludeConshdlrLogicor(), SCIPreoptApplyGlbConss(), and upgradeCons().

◆ SCIPcreateConsBasicLogicor()

SCIP_RETCODE SCIPcreateConsBasicLogicor	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars
	)

creates and captures a logicor constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsLogicor(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsLogicor() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries

Definition at line 5243 of file cons_logicor.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPaddCoefLogicor(), SCIPcreateConsLogicor(), and TRUE.

Referenced by addFixedVarsConss(), createProbQP(), createProbSimplified(), createProbSimplifiedTest(), and SCIPcreateConsLogicor().

◆ SCIPaddCoefLogicor()

SCIP_RETCODE SCIPaddCoefLogicor	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var
	)

adds coefficient in logic or constraint

Parameters

scip	SCIP data structure
cons	logicor constraint
var	variable to add to the constraint

Definition at line 5260 of file cons_logicor.c.

References addCoef(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetNVarsLogicor().

Referenced by addCoefTerm(), createConflictCons(), createProbQP(), createProbSimplified(), createProbSimplifiedTest(), SCIPaddCoefPseudoboolean(), and SCIPcreateConsBasicLogicor().

◆ SCIPgetNVarsLogicor()

int SCIPgetNVarsLogicor	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets number of variables in logic or constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5283 of file cons_logicor.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVarsLogicor().

Referenced by addLogicOrConstraints(), checkLogicor(), computeSymmetryGroup(), correctPresoldata(), createAltLP(), createPresoldata(), extractGates(), getLinearConsNVars(), getLinearConsVarsData(), presolveAddKKTLogicorConss(), SCIPaddCoefLogicor(), SCIPmatrixCreate(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), writeFzn(), and writeOpbConstraints().

◆ SCIPgetVarsLogicor()

SCIP_VAR** SCIPgetVarsLogicor	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of variables in logic or constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5304 of file cons_logicor.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetDualsolLogicor().

Referenced by addLogicOrConstraints(), checkLogicor(), computeSymmetryGroup(), createAltLP(), extractGates(), getLinearConsVarsData(), presolveAddKKTLogicorConss(), saveConsLinear(), SCIPgetNVarsLogicor(), SCIPmatrixCreate(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), writeFzn(), and writeOpbConstraints().

◆ SCIPgetDualsolLogicor()

SCIP_Real SCIPgetDualsolLogicor	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the dual solution of the logic or constraint in the current LP

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5325 of file cons_logicor.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPgetDualfarkasLogicor(), and SCIProwGetDualsol().

Referenced by SCIPconsGetDualsol(), and SCIPgetVarsLogicor().

◆ SCIPgetDualfarkasLogicor()

SCIP_Real SCIPgetDualfarkasLogicor	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the dual Farkas value of the logic or constraint in the current infeasible LP

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5349 of file cons_logicor.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPgetRowLogicor(), and SCIProwGetDualfarkas().

Referenced by SCIPconsGetDualfarkas(), and SCIPgetDualsolLogicor().

◆ SCIPgetRowLogicor()

SCIP_ROW* SCIPgetRowLogicor	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the linear relaxation of the given logic or constraint; may return NULL if no LP row was yet created; the user must not modify the row!

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5375 of file cons_logicor.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPconsGetRow(), and SCIPgetDualfarkasLogicor().

◆ SCIPincludeNonlinconsUpgrade()

SCIP_RETCODE SCIPincludeNonlinconsUpgrade	(	SCIP *	scip,
		SCIP_DECL_NONLINCONSUPGD((*nonlinconsupgd))	,
		SCIP_DECL_EXPRGRAPHNODEREFORM((*nodereform))	,
		int	priority,
		SCIP_Bool	active,
		const char *	conshdlrname
	)

includes a nonlinear constraint upgrade method into the nonlinear constraint handler

Parameters

scip	SCIP data structure
priority	priority of upgrading method
active	should the upgrading method by active by default?
conshdlrname	name of the constraint handler

Definition at line 9242 of file cons_nonlinear.c.

References active, SCIP_NlConsUpgrade::active, CONSHDLR_NAME, LinVarEventData::conshdlrdata, FALSE, NULL, SCIP_NlConsUpgrade::priority, SCIP_CALL, SCIP_MAXSTRLEN, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPaddBoolParam(), SCIPallocBlockMemory, SCIPcalcMemGrowSize(), SCIPconshdlrGetData(), SCIPcreateConsNonlinear(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPreallocBlockMemoryArray, SCIPsnprintf(), and SCIPwarningMessage().

Referenced by SCIPincludeConshdlrAbspower(), SCIPincludeConshdlrAnd(), SCIPincludeConshdlrBivariate(), SCIPincludeConshdlrNonlinear(), and SCIPincludeConshdlrQuadratic().

◆ SCIPcreateConsNonlinear()

SCIP_RETCODE SCIPcreateConsNonlinear	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nlinvars,
		SCIP_VAR **	linvars,
		SCIP_Real *	lincoefs,
		int	nexprtrees,
		SCIP_EXPRTREE **	exprtrees,
		SCIP_Real *	nonlincoefs,
		SCIP_Real	lhs,
		SCIP_Real	rhs,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a nonlinear constraint this variant takes expression trees as input

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nlinvars	number of linear variables in the constraint
linvars	array with linear variables of constraint entries
lincoefs	array with coefficients of constraint linear entries
nexprtrees	number of expression trees for nonlinear part of constraint
exprtrees	expression trees for nonlinear part of constraint
nonlincoefs	coefficients for expression trees for nonlinear part, or NULL if all 1.0
lhs	left hand side of constraint
rhs	right hand side of constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are seperated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 9327 of file cons_nonlinear.c.

References addLinearCoef(), consdataCreateEmpty(), consdataEnsureLinearVarsSize(), consdataSetExprtrees(), CONSHDLR_NAME, FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPcreateCons(), SCIPcreateConsBasicNonlinear(), SCIPdebugMsg, SCIPdebugPrintCons, SCIPerrorMessage, SCIPfindConshdlr(), SCIPisZero(), and TRUE.

Referenced by readConstraints(), readNonlinearExprs(), readObjective(), removeFixedVariables(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIPcreateConsBasicNonlinear(), and SCIPincludeNonlinconsUpgrade().

◆ SCIPcreateConsBasicNonlinear()

SCIP_RETCODE SCIPcreateConsBasicNonlinear	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nlinvars,
		SCIP_VAR **	linvars,
		SCIP_Real *	lincoefs,
		int	nexprtrees,
		SCIP_EXPRTREE **	exprtrees,
		SCIP_Real *	nonlincoefs,
		SCIP_Real	lhs,
		SCIP_Real	rhs
	)

creates and captures a nonlinear constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsNonlinear(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

this variant takes expression trees as input

See also: SCIPcreateConsNonlinear() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nlinvars	number of linear variables in the constraint
linvars	array with linear variables of constraint entries
lincoefs	array with coefficients of constraint linear entries
nexprtrees	number of expression trees for nonlinear part of constraint
exprtrees	expression trees for nonlinear part of constraint
nonlincoefs	coefficients for expression trees for nonlinear part, or NULL if all 1.0
lhs	left hand side of constraint
rhs	right hand side of constraint

Definition at line 9420 of file cons_nonlinear.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPcreateConsNonlinear(), SCIPcreateConsNonlinear2(), and TRUE.

Referenced by SCIPcreateConsNonlinear(), and setupProblem().

◆ SCIPcreateConsNonlinear2()

SCIP_RETCODE SCIPcreateConsNonlinear2	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nlinvars,
		SCIP_VAR **	linvars,
		SCIP_Real *	lincoefs,
		SCIP_EXPRGRAPHNODE *	exprgraphnode,
		SCIP_Real	lhs,
		SCIP_Real	rhs,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a nonlinear constraint this variant takes a node of the expression graph as input and can only be used during presolving it is assumed that the nonlinear constraint will be added to the transformed problem short after creation the given exprgraphnode is captured in this method

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nlinvars	number of linear variables in the constraint
linvars	array with linear variables of constraint entries
lincoefs	array with coefficients of constraint linear entries
exprgraphnode	expression graph node associated to nonlinear expression
lhs	left hand side of constraint
rhs	right hand side of constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are seperated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 9450 of file cons_nonlinear.c.

References addLinearCoef(), consdataCreateEmpty(), consdataEnsureLinearVarsSize(), CONSHDLR_NAME, FALSE, NULL, SCIP_CALL, SCIP_EXPRCURV_UNKNOWN, SCIP_INVALID, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIP_STAGE_PRESOLVING, SCIPcreateCons(), SCIPcreateConsBasicNonlinear2(), SCIPdebugMsg, SCIPdebugPrintCons, SCIPerrorMessage, SCIPexprgraphCaptureNode(), SCIPfindConshdlr(), SCIPgetStage(), and SCIPisZero().

Referenced by reformMonomial(), reformNode2Var(), reformulate(), SCIP_DECL_EXPRGRAPHNODEREFORM(), SCIP_DECL_NONLINCONSUPGD(), SCIPcreateConsBasicNonlinear(), and SCIPcreateConsBasicNonlinear2().

◆ SCIPcreateConsBasicNonlinear2()

SCIP_RETCODE SCIPcreateConsBasicNonlinear2	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nlinvars,
		SCIP_VAR **	linvars,
		SCIP_Real *	lincoefs,
		SCIP_EXPRGRAPHNODE *	exprgraphnode,
		SCIP_Real	lhs,
		SCIP_Real	rhs
	)

creates and captures a nonlinear constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsNonlinear2(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

this variant takes a node of the expression graph as input and can only be used during presolving it is assumed that the nonlinear constraint will be added to the transformed problem short after creation the given exprgraphnode is captured in this method

See also: SCIPcreateConsNonlinear2() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a nonlinear constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsNonlinear(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

this variant takes a node of the expression graph as input and can only be used during presolving it is assumed that the nonlinear constraint will be added to the transformed problem short after creation the given exprgraphnode is captured in this method

See also: SCIPcreateConsNonlinear() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nlinvars	number of linear variables in the constraint
linvars	array with linear variables of constraint entries
lincoefs	array with coefficients of constraint linear entries
exprgraphnode	expression graph node associated to nonlinear expression
lhs	left hand side of constraint
rhs	right hand side of constraint

Definition at line 9548 of file cons_nonlinear.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPaddLinearVarNonlinear(), SCIPcreateConsNonlinear2(), and TRUE.

Referenced by SCIPcreateConsNonlinear2().

◆ SCIPaddLinearVarNonlinear()

SCIP_RETCODE SCIPaddLinearVarNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	coef
	)

adds a linear variable with coefficient to a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint
var	variable
coef	coefficient of variable

Definition at line 9569 of file cons_nonlinear.c.

References addLinearCoef(), NULL, REALABS, SCIP_CALL, SCIP_OKAY, SCIPisInfinity(), and SCIPsetExprtreesNonlinear().

Referenced by SCIPcreateConsBasicNonlinear2().

◆ SCIPsetExprtreesNonlinear()

SCIP_RETCODE SCIPsetExprtreesNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		int	nexprtrees,
		SCIP_EXPRTREE **	exprtrees,
		SCIP_Real *	coefs
	)

sets the expression trees in a nonlinear constraint constraint must not be active yet

Parameters

scip	SCIP data structure
cons	constraint
nexprtrees	number of expression trees
exprtrees	new expression trees, or NULL if nexprtrees is 0
coefs	coefficients of expression trees, or NULL if all 1.0

Definition at line 9589 of file cons_nonlinear.c.

References consdataSetExprtrees(), NULL, SCIP_CALL, SCIP_OKAY, SCIPaddExprtreesNonlinear(), SCIPconsGetData(), SCIPconsIsActive(), and TRUE.

Referenced by SCIPaddLinearVarNonlinear().

◆ SCIPaddExprtreesNonlinear()

SCIP_RETCODE SCIPaddExprtreesNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		int	nexprtrees,
		SCIP_EXPRTREE **	exprtrees,
		SCIP_Real *	coefs
	)

adds expression trees to a nonlinear constraint constraint must not be active yet

Parameters

scip	SCIP data structure
cons	constraint
nexprtrees	number of expression trees
exprtrees	new expression trees, or NULL if nexprtrees is 0
coefs	coefficients of expression trees, or NULL if all 1.0

Definition at line 9611 of file cons_nonlinear.c.

References consdataAddExprtrees(), NULL, SCIP_CALL, SCIP_OKAY, SCIPconsGetData(), SCIPconsIsActive(), SCIPgetNlRowNonlinear(), and TRUE.

Referenced by readNonlinearExprs(), and SCIPsetExprtreesNonlinear().

◆ SCIPgetNlRowNonlinear()

SCIP_RETCODE SCIPgetNlRowNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_NLROW **	nlrow
	)

gets the nonlinear constraint as a nonlinear row representation

Parameters

scip	SCIP data structure
cons	constraint
nlrow	pointer to store nonlinear row

Definition at line 9631 of file cons_nonlinear.c.

References createNlRow(), NULL, SCIP_CALL, SCIP_OKAY, SCIPconsGetData(), and SCIPgetNLinearVarsNonlinear().

Referenced by SCIPaddExprtreesNonlinear().

◆ SCIPgetNLinearVarsNonlinear()

int SCIPgetNLinearVarsNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the number of variables in the linear term of a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9656 of file cons_nonlinear.c.

References NULL, SCIPconsGetData(), and SCIPgetLinearVarsNonlinear().

Referenced by readNonlinearExprs(), SCIP_DECL_NONLINCONSUPGD(), SCIP_DECL_QUADCONSUPGD(), SCIPgetNlRowNonlinear(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetLinearVarsNonlinear()

SCIP_VAR** SCIPgetLinearVarsNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the variables in the linear part of a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9668 of file cons_nonlinear.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetLinearCoefsNonlinear().

Referenced by readNonlinearExprs(), SCIP_DECL_NONLINCONSUPGD(), SCIPgetNLinearVarsNonlinear(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetLinearCoefsNonlinear()

SCIP_Real* SCIPgetLinearCoefsNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the coefficients in the linear part of a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9680 of file cons_nonlinear.c.

References NULL, SCIPconsGetData(), and SCIPgetNExprtreesNonlinear().

Referenced by readNonlinearExprs(), SCIP_DECL_NONLINCONSUPGD(), SCIPgetLinearVarsNonlinear(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetNExprtreesNonlinear()

int SCIPgetNExprtreesNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the number of expression trees of a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9692 of file cons_nonlinear.c.

References NULL, SCIP_STAGE_EXITPRESOLVE, SCIP_STAGE_INITPRESOLVE, SCIPconsGetData(), SCIPgetExprtreesNonlinear(), and SCIPgetStage().

Referenced by SCIPgetLinearCoefsNonlinear(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetExprtreesNonlinear()

SCIP_EXPRTREE** SCIPgetExprtreesNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the expression trees of a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9705 of file cons_nonlinear.c.

References NULL, SCIP_Real, SCIP_STAGE_EXITPRESOLVE, SCIP_STAGE_INITPRESOLVE, SCIPconsGetData(), SCIPgetExprtreeCoefsNonlinear(), and SCIPgetStage().

Referenced by SCIPgetNExprtreesNonlinear(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetExprtreeCoefsNonlinear()

SCIP_Real* SCIPgetExprtreeCoefsNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the coefficients of the expression trees of a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9718 of file cons_nonlinear.c.

References NULL, SCIP_STAGE_EXITPRESOLVE, SCIP_STAGE_INITPRESOLVE, SCIPconsGetData(), SCIPgetExprgraphNodeNonlinear(), and SCIPgetStage().

Referenced by SCIPgetExprtreesNonlinear(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetExprgraphNodeNonlinear()

SCIP_EXPRGRAPHNODE* SCIPgetExprgraphNodeNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the expression graph node of a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9731 of file cons_nonlinear.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetLhsNonlinear().

Referenced by SCIP_DECL_NONLINCONSUPGD(), SCIP_DECL_QUADCONSUPGD(), SCIPgetExprtreeCoefsNonlinear(), and SCIPwriteGms().

◆ SCIPgetLhsNonlinear()

SCIP_Real SCIPgetLhsNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the left hand side of a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9743 of file cons_nonlinear.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetRhsNonlinear().

Referenced by readNonlinearExprs(), SCIP_DECL_NONLINCONSUPGD(), SCIPgetExprgraphNodeNonlinear(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPgetRhsNonlinear()

SCIP_Real SCIPgetRhsNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the right hand side of a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9755 of file cons_nonlinear.c.

References NULL, SCIPcheckCurvatureNonlinear(), and SCIPconsGetData().

Referenced by readNonlinearExprs(), SCIP_DECL_NONLINCONSUPGD(), SCIPgetLhsNonlinear(), SCIPwriteGms(), and SCIPwritePip().

◆ SCIPcheckCurvatureNonlinear()

SCIP_RETCODE SCIPcheckCurvatureNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

check the function of a nonlinear constraint for convexity/concavity, if not done yet

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9767 of file cons_nonlinear.c.

References checkCurvature(), LinVarEventData::conshdlrdata, NULL, SCIP_CALL, SCIP_OKAY, SCIPconsGetHdlr(), SCIPconshdlrGetData(), and SCIPgetCurvatureNonlinear().

Referenced by SCIPgetRhsNonlinear().

◆ SCIPgetCurvatureNonlinear()

SCIP_RETCODE SCIPgetCurvatureNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_Bool	checkcurv,
		SCIP_EXPRCURV *	curvature
	)

gets the curvature of the nonlinear function of a nonlinear constraint

The curvature is computed by summing up the curvature for each nonlinear summand. To get the curvature for single summands, use SCIPgetExprtreeCurvaturesNonlinear().

gets the curvature of the nonlinear function of a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint
checkcurv	whether to check constraint curvature, if not checked before
curvature	pointer to store curvature of constraint

Definition at line 9789 of file cons_nonlinear.c.

References checkCurvature(), LinVarEventData::conshdlrdata, NULL, SCIP_CALL, SCIP_OKAY, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetData(), and SCIPgetExprtreeCurvaturesNonlinear().

Referenced by SCIPcheckCurvatureNonlinear().

◆ SCIPgetExprtreeCurvaturesNonlinear()

SCIP_RETCODE SCIPgetExprtreeCurvaturesNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_Bool	checkcurv,
		SCIP_EXPRCURV **	curvatures
	)

gets the curvature of the expression trees (multiplied by their coefficient) of a nonlinear constraint

Parameters

scip	SCIP data structure
cons	constraint
checkcurv	whether to check constraint curvature, if not checked before
curvatures	buffer to store curvatures of exprtrees

Definition at line 9823 of file cons_nonlinear.c.

References checkCurvature(), LinVarEventData::conshdlrdata, NULL, SCIP_CALL, SCIP_OKAY, SCIP_STAGE_EXITPRESOLVE, SCIP_STAGE_INITPRESOLVE, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetData(), SCIPgetStage(), and SCIPgetViolationNonlinear().

Referenced by SCIPgetCurvatureNonlinear().

◆ SCIPgetViolationNonlinear()

SCIP_RETCODE SCIPgetViolationNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SOL *	sol,
		SCIP_Real *	violation
	)

computes the violation of a nonlinear constraint by a solution

Parameters

scip	SCIP data structure
cons	constraint
sol	solution which violation to calculate, or NULL for LP solution
violation	pointer to store violation of constraint

Definition at line 9860 of file cons_nonlinear.c.

References computeViolation(), MAX, NULL, SCIP_Bool, SCIP_CALL, SCIP_ERROR, SCIP_INVALID, SCIP_OKAY, SCIP_STAGE_EXITPRESOLVE, SCIP_STAGE_INITPRESOLVE, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconsIsActive(), SCIPerrorMessage, SCIPgetLinvarMayDecreaseNonlinear(), SCIPgetStage(), and SCIPwarningMessage().

Referenced by SCIPgetExprtreeCurvaturesNonlinear().

◆ SCIPgetLinvarMayDecreaseNonlinear()

int SCIPgetLinvarMayDecreaseNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

get index of a linear variable of a nonlinear constraint that may be decreased without making any other constraint infeasible, or -1 if none

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9903 of file cons_nonlinear.c.

References consdataFindUnlockedLinearVar(), NULL, SCIPconsGetData(), and SCIPgetLinvarMayIncreaseNonlinear().

Referenced by SCIPgetViolationNonlinear().

◆ SCIPgetLinvarMayIncreaseNonlinear()

int SCIPgetLinvarMayIncreaseNonlinear	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

get index of a linear variable of a nonlinear constraint that may be increased without making any other constraint infeasible, or -1 if none

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 9923 of file cons_nonlinear.c.

References consdataFindUnlockedLinearVar(), NULL, SCIPconsGetData(), and SCIPgetExprgraphNonlinear().

Referenced by SCIPgetLinvarMayDecreaseNonlinear().

◆ SCIPgetExprgraphNonlinear()

SCIP_EXPRGRAPH* SCIPgetExprgraphNonlinear	(	SCIP *	scip,
		SCIP_CONSHDLR *	conshdlr
	)

gets expression graph of nonlinear constraint handler

Parameters

scip	SCIP data structure
conshdlr	nonlinear constraint handler

Definition at line 9943 of file cons_nonlinear.c.

References LinVarEventData::conshdlrdata, NULL, SCIPcomputeHyperplaneThreePoints(), and SCIPconshdlrGetData().

Referenced by SCIP_DECL_NONLINCONSUPGD(), SCIPgetLinvarMayIncreaseNonlinear(), and SCIPwriteGms().

◆ SCIPcomputeHyperplaneThreePoints()

SCIP_RETCODE SCIPcomputeHyperplaneThreePoints	(	SCIP *	scip,
		SCIP_Real	a1,
		SCIP_Real	a2,
		SCIP_Real	a3,
		SCIP_Real	b1,
		SCIP_Real	b2,
		SCIP_Real	b3,
		SCIP_Real	c1,
		SCIP_Real	c2,
		SCIP_Real	c3,
		SCIP_Real *	alpha,
		SCIP_Real *	beta,
		SCIP_Real *	gamma_,
		SCIP_Real *	delta
	)

given three points, constructs coefficient of equation for hyperplane generated by these three points Three points a, b, and c are given. Computes coefficients alpha, beta, gamma, and delta, such that a, b, and c, satisfy alpha * x1 + beta * x2 + gamma * x3 = delta and gamma >= 0.0.

Parameters

scip	SCIP data structure
a1	first coordinate of a
a2	second coordinate of a
a3	third coordinate of a
b1	first coordinate of b
b2	second coordinate of b
b3	third coordinate of b
c1	first coordinate of c
c2	second coordinate of c
c3	third coordinate of c
alpha	coefficient of first coordinate
beta	coefficient of second coordinate
gamma_	coefficient of third coordinate
delta	constant right-hand side

Definition at line 9965 of file cons_nonlinear.c.

References NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIP_Real, SCIPdebugMsg, SCIPisRelEQ(), and SCIPsolveLinearProb().

Referenced by addConcaveEstimatorBivariate(), generateEstimatingHyperplane(), and SCIPgetExprgraphNonlinear().

◆ SCIPcreateConsOr()

SCIP_RETCODE SCIPcreateConsOr	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	resvar,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures an or constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
resvar	resultant variable of the operation
nvars	number of operator variables in the constraint
vars	array with operator variables of constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 2092 of file cons_or.c.

References consdataCreate(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicOr(), SCIPerrorMessage, and SCIPfindConshdlr().

Referenced by CREATE_CONSTRAINT(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIPcreateConsBasicOr(), and SCIPincludeConshdlrOr().

◆ SCIPcreateConsBasicOr()

SCIP_RETCODE SCIPcreateConsBasicOr	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	resvar,
		int	nvars,
		SCIP_VAR **	vars
	)

creates and captures an or constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsNonlinear(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsOr() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures an or constraint in its most basic variant, i. e., with all constraint flags set to their default values

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
resvar	resultant variable of the operation
nvars	number of operator variables in the constraint
vars	array with operator variables of constraint

Definition at line 2154 of file cons_or.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIPcreateConsOr(), SCIPgetNVarsOr(), and TRUE.

Referenced by SCIPcreateConsOr().

◆ SCIPgetNVarsOr()

int SCIPgetNVarsOr	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets number of variables in or constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 2170 of file cons_or.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVarsOr().

Referenced by computeSymmetryGroup(), SCIP_DECL_CONSCOPY(), and SCIPcreateConsBasicOr().

◆ SCIPgetVarsOr()

SCIP_VAR** SCIPgetVarsOr	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of variables in or constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 2191 of file cons_or.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetResultantOr().

Referenced by computeSymmetryGroup(), SCIP_DECL_CONSCOPY(), and SCIPgetNVarsOr().

◆ SCIPgetResultantOr()

SCIP_VAR* SCIPgetResultantOr	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the resultant variable in or constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 2212 of file cons_or.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by computeSymmetryGroup(), SCIP_DECL_CONSCOPY(), and SCIPgetVarsOr().

◆ SCIPseparateCoversOrbisack()

SCIP_RETCODE SCIPseparateCoversOrbisack	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SOL *	sol,
		SCIP_VAR **	vars1,
		SCIP_VAR **	vars2,
		int	nrows,
		SCIP_Bool *	infeasible,
		int *	ngen
	)

separate orbisack solutions

separate orbisack cover inequalities for a given solution

Parameters

scip	pointer to scip
cons	pointer to constraint for which cover inequality should be added
sol	solution to be separated
vars1	variables of first columns
vars2	variables of second columns
nrows	number of rows
infeasible	memory address to store whether we detected infeasibility
ngen	memory address to store number of generated cuts

Definition at line 1823 of file cons_orbisack.c.

References FALSE, NULL, SCIP_CALL, SCIP_DECL_CONSGETVARS(), SCIP_OKAY, SCIP_Real, SCIPaddRow(), SCIPaddVarToRow(), SCIPallocBufferArray, SCIPcacheRowExtensions(), SCIPconsGetHdlr(), SCIPcreateEmptyRowCons(), SCIPflushRowExtensions(), SCIPfreeBufferArray, SCIPgetSolVals(), SCIPinfinity(), SCIPisEfficacious(), SCIPprintRow(), SCIPreleaseRow(), and TRUE.

Referenced by SCIPcheckSolutionOrbisack(), and separateConstraints().

◆ SCIPcheckSolutionOrbisack()

SCIP_RETCODE SCIPcheckSolutionOrbisack	(	SCIP *	scip,
		SCIP_SOL *	sol,
		SCIP_VAR **	vars1,
		SCIP_VAR **	vars2,
		int	nrows,
		SCIP_Bool	printreason,
		SCIP_Bool *	feasible
	)

checks whether a given binary solution is feasible for the orbisack

checks given solution for feasibility

Parameters

scip	SCIP data structure
sol	solution to check for feasibility
vars1	variables of first column
vars2	variables of second column
nrows	number of rows
printreason	whether reason for infeasibility should be printed
feasible	memory address to store whether sol is feasible

Definition at line 1768 of file cons_orbisack.c.

References FALSE, NULL, SCIP_OKAY, SCIPgetSolVal(), SCIPinfoMessage(), SCIPisFeasIntegral(), SCIPseparateCoversOrbisack(), and TRUE.

Referenced by checkFullOrbitopeSolution(), SCIP_DECL_CONSCHECK(), SCIP_DECL_CONSENFOPS(), and SCIP_DECL_CONSPRINT().

◆ SCIPcreateConsOrbisack()

SCIP_RETCODE SCIPcreateConsOrbisack	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR const	vars1,
		SCIP_VAR const	vars2,
		int	nrows,
		SCIP_Bool	ispporbisack,
		SCIP_Bool	isparttype,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a orbisack constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
vars1	first column of matrix of variables on which the symmetry acts
vars2	second column of matrix of variables on which the symmetry acts
nrows	number of rows in variable matrix
ispporbisack	whether the orbisack is a packing/partitioning orbisack
isparttype	whether the orbisack is a partitioning orbisack
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 2045 of file cons_orbisack.c.

References consdataCreate(), CONSHDLR_NAME, NULL, packingUpgrade(), SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIP_ORBITOPETYPE_PACKING, SCIP_ORBITOPETYPE_PARTITIONING, SCIP_PLUGINNOTFOUND, SCIPallocBufferArray, SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicOrbisack(), SCIPcreateConsOrbitope(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPfreeBufferArray, and TRUE.

Referenced by orbisackUpgrade(), SCIPcreateConsBasicOrbisack(), and SCIPincludeConshdlrOrbisack().

◆ SCIPcreateConsBasicOrbisack()

SCIP_RETCODE SCIPcreateConsBasicOrbisack	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR **	vars1,
		SCIP_VAR **	vars2,
		int	nrows,
		SCIP_Bool	ispporbisack,
		SCIP_Bool	isparttype
	)

creates and captures an orbisack constraint in its most basic variant

All constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h.

See also: SCIPcreateConsOrbisack() for the default constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures an orbisack constraint in its most basic variant

All constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h.

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
vars1	first column of matrix of variables on which the symmetry acts
vars2	second column of matrix of variables on which the symmetry acts
nrows	number of rows in constraint matrix
ispporbisack	whether the orbisack is a packing/partitioning orbisack
isparttype	whether the orbisack is a partitioning orbisack

Definition at line 2150 of file cons_orbisack.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIPcreateConsOrbisack(), and TRUE.

Referenced by SCIPcreateConsOrbisack().

◆ SCIPcreateConsOrbitope()

SCIP_RETCODE SCIPcreateConsOrbitope	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR ***	vars,
		SCIP_ORBITOPETYPE	orbitopetype,
		int	nspcons,
		int	nblocks,
		SCIP_Bool	resolveprop,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a orbitope constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a orbitope constraint

Precondition: If packing/partitioning orbitopes are used, this constraint handler assumes that constraints which enforce the packing/partitioning constraints are contained in the problem. It does not implement, e.g., separation and propagation of set packing/partitioning constraints, since this would just copy large parts of the code of the setppc constraint handler.

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
vars	matrix of variables on which the symmetry acts
orbitopetype	type of orbitope constraint
nspcons	number of set partitioning/packing constraints <=> p
nblocks	number of symmetric variable blocks <=> q
resolveprop	should propagation be resolved?
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 3161 of file cons_orbitope.c.

References consdataCreate(), CONSHDLR_NAME, NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIP_ORBITOPETYPE_FULL, SCIP_ORBITOPETYPE_PACKING, SCIP_ORBITOPETYPE_PARTITIONING, SCIP_PLUGINNOTFOUND, SCIP_Real, SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicOrbitope(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPgetSubscipDepth(), SCIPinfinity(), SCIPisEQ(), SCIPisInfinity(), SCIPisZero(), SCIPvarGetLbGlobal(), SCIPvarGetNegatedVar(), SCIPvarGetObj(), SCIPvarGetUbGlobal(), SCIPvarIsActive(), SCIPvarIsBinary(), SCIPvarIsNegated(), and strenghtenOrbitopeConstraint().

Referenced by detectOrbitopes(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIPcreateConsBasicOrbitope(), SCIPcreateConsOrbisack(), and SCIPincludeConshdlrOrbitope().

◆ SCIPcreateConsBasicOrbitope()

SCIP_RETCODE SCIPcreateConsBasicOrbitope	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR ***	vars,
		SCIP_ORBITOPETYPE	orbitopetype,
		int	nspcons,
		int	nblocks,
		SCIP_Bool	resolveprop
	)

creates and captures an orbitope constraint in its most basic variant, i. e., with all constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h

See also: SCIPcreateConsOrbitope() for the default constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures an orbitope constraint in its most basic variant, i. e., with all constraint flags set to their default values

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
vars	matrix of variables on which the symmetry acts
orbitopetype	type of orbitope constraint
nspcons	number of set partitioning/packing constraints <=> p
nblocks	number of symmetric variable blocks <=> q
resolveprop	should propagation be resolved?

Definition at line 3279 of file cons_orbitope.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIPcreateConsOrbitope(), and TRUE.

Referenced by SCIPcreateConsOrbitope().

◆ SCIPcreateConsPseudobooleanWithConss()

SCIP_RETCODE SCIPcreateConsPseudobooleanWithConss	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_CONS *	lincons,
		SCIP_LINEARCONSTYPE	linconstype,
		SCIP_CONS **	andconss,
		SCIP_Real *	andcoefs,
		int	nandconss,
		SCIP_VAR *	indvar,
		SCIP_Real	weight,
		SCIP_Bool	issoftcons,
		SCIP_VAR *	intvar,
		SCIP_Real	lhs,
		SCIP_Real	rhs,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a pseudoboolean constraint, with given linear and and-constraints

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
lincons	associated linear constraint
linconstype	linear constraint type of associated linear constraint
andconss	associated and-constraints
andcoefs	associated coefficients of and-constraints
nandconss	number of associated and-constraints
indvar	indicator variable if it's a soft constraint, or NULL
weight	weight of the soft constraint, if it is one
issoftcons	is this a soft constraint
intvar	an artificial variable which was added only for the objective function, if this variable is not NULL this constraint (without this integer variable) describes the objective function
lhs	left hand side of constraint
rhs	right hand side of constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are seperated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 8897 of file cons_pseudoboolean.c.

References BMScopyMemoryArray, ConsAndData::cons, consdataCreate(), CONSHDLR_NAME, FALSE, inithashmapandtable(), ConsAndData::isoriginal, ConsAndData::istransformed, ConsAndData::newvars, ConsAndData::nnewvars, ConsAndData::noriguses, NULL, ConsAndData::nuses, ConsAndData::nvars, ConsAndData::origcons, SCIP_Bool, SCIP_CALL, SCIP_LINEARCONSTYPE_INVALIDCONS, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPallocBlockMemory, SCIPcalcMemGrowSize(), SCIPcaptureCons(), SCIPcaptureVar(), SCIPconsAddUpgradeLocks(), SCIPconshdlrGetData(), SCIPconsIsTransformed(), SCIPcreateCons(), SCIPcreateConsPseudoboolean(), SCIPduplicateBlockMemoryArray, SCIPensureBlockMemoryArray, SCIPerrorMessage, SCIPfindConshdlr(), SCIPfreeBlockMemory, SCIPfreeBlockMemoryArray, SCIPgetNVarsAnd(), SCIPgetResultantAnd(), SCIPgetVarsAnd(), SCIPhashmapExists(), SCIPhashmapInsert(), SCIPhashtableInsert(), SCIPhashtableRetrieve(), SCIPinfinity(), SCIPisInfinity(), SCIPsortPtr(), SCIPwarningMessage(), ConsAndData::snewvars, ConsAndData::svars, TRUE, and ConsAndData::vars.

Referenced by copyConsPseudoboolean(), and SCIPincludeConshdlrPseudoboolean().

◆ SCIPcreateConsPseudoboolean()

SCIP_RETCODE SCIPcreateConsPseudoboolean	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR **	linvars,
		int	nlinvars,
		SCIP_Real *	linvals,
		SCIP_VAR ***	terms,
		int	nterms,
		int *	ntermvars,
		SCIP_Real *	termvals,
		SCIP_VAR *	indvar,
		SCIP_Real	weight,
		SCIP_Bool	issoftcons,
		SCIP_VAR *	intvar,
		SCIP_Real	lhs,
		SCIP_Real	rhs,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a pseudoboolean constraint

Note: linear and nonlinear terms can be added using SCIPaddCoefPseudoboolean() and SCIPaddTermPseudoboolean(), respectively; the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
linvars	variables of the linear part, or NULL
nlinvars	number of variables of the linear part
linvals	coefficients of linear part, or NULL
terms	nonlinear terms of variables, or NULL
nterms	number of terms of variables of nonlinear term
ntermvars	number of variables in nonlinear terms, or NULL
termvals	coefficients of nonlinear parts, or NULL
indvar	indicator variable if it's a soft constraint, or NULL
weight	weight of the soft constraint, if it is one
issoftcons	is this a soft constraint
intvar	an artificial variable which was added only for the objective function, if this variable is not NULL this constraint (without this integer variable) describes the objective function
lhs	left hand side of constraint
rhs	right hand side of constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 9167 of file cons_pseudoboolean.c.

References consdataCreate(), CONSHDLR_NAME, createAndAddAnds(), createAndAddLinearCons(), FALSE, inithashmapandtable(), nterms, NULL, SCIP_Bool, SCIP_CALL, SCIP_INVALIDDATA, SCIP_LINEARCONSTYPE_INVALIDCONS, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIP_Real, SCIPallocBufferArray, SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicPseudoboolean(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPfreeBufferArray, SCIPgetResultantAnd(), SCIPinfinity(), and SCIPisInfinity().

Referenced by readConstraints(), SCIPcreateConsBasicPseudoboolean(), SCIPcreateConsPseudobooleanWithConss(), and setObjective().

◆ SCIPcreateConsBasicPseudoboolean()

SCIP_RETCODE SCIPcreateConsBasicPseudoboolean	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR **	linvars,
		int	nlinvars,
		SCIP_Real *	linvals,
		SCIP_VAR ***	terms,
		int	nterms,
		int *	ntermvars,
		SCIP_Real *	termvals,
		SCIP_VAR *	indvar,
		SCIP_Real	weight,
		SCIP_Bool	issoftcons,
		SCIP_VAR *	intvar,
		SCIP_Real	lhs,
		SCIP_Real	rhs
	)

creates and captures a pseudoboolean constraint in its most basic variant, i. e., with all constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h

See also: SCIPcreateConsPseudoboolean() for the default constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a pseudoboolean constraint in its most basic variant, i. e., with all constraint flags set to their default values

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
linvars	variables of the linear part, or NULL
nlinvars	number of variables of the linear part
linvals	coefficients of linear part, or NULL
terms	nonlinear terms of variables, or NULL
nterms	number of terms of variables of nonlinear term
ntermvars	number of variables in nonlinear terms, or NULL
termvals	coefficients of nonlinear parts, or NULL
indvar	indicator variable if it's a soft constraint, or NULL
weight	weight of the soft constraint, if it is one
issoftcons	is this a soft constraint
intvar	a artificial variable which was added only for the objective function, if this variable is not NULL this constraint (without this integer variable) describes the objective function
lhs	left hand side of constraint
rhs	right hand side of constraint

Definition at line 9314 of file cons_pseudoboolean.c.

References FALSE, nterms, SCIP_CALL, SCIP_OKAY, SCIPaddCoefPseudoboolean(), SCIPcreateConsPseudoboolean(), and TRUE.

Referenced by SCIPcreateConsPseudoboolean().

◆ SCIPaddCoefPseudoboolean()

SCIP_RETCODE SCIPaddCoefPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons,
		SCIP_VAR *const	var,
		SCIP_Real const	val
	)

adds linear term pseudo boolean constraint (if it is not zero)

Note: you can only add a coefficient if the special type of linear constraint won't changed

adds a variable to the pseudo boolean constraint (if it is not zero)

Note: you can only add a coefficient if the special type of linear constraint won't changed

Parameters

scip	SCIP data structure
cons	constraint data
var	variable of constraint entry
val	coefficient of constraint entry

Definition at line 9349 of file cons_pseudoboolean.c.

References CONSHDLR_NAME, FALSE, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_LINEARCONSTYPE_INVALIDCONS, SCIP_LINEARCONSTYPE_KNAPSACK, SCIP_LINEARCONSTYPE_LINEAR, SCIP_LINEARCONSTYPE_LOGICOR, SCIP_LINEARCONSTYPE_SETPPC, SCIP_Longint, SCIP_OKAY, SCIPABORT, SCIPaddCoefKnapsack(), SCIPaddCoefLinear(), SCIPaddCoefLogicor(), SCIPaddCoefSetppc(), SCIPaddTermPseudoboolean(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPisEQ(), SCIPisIntegral(), SCIPisPositive(), and SCIPisZero().

Referenced by SCIPcreateConsBasicPseudoboolean().

◆ SCIPaddTermPseudoboolean()

SCIP_RETCODE SCIPaddTermPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons,
		SCIP_VAR **const	vars,
		int const	nvars,
		SCIP_Real const	val
	)

adds nonlinear term to pseudo boolean constraint (if it is not zero)

Note: you can only add a coefficient if the special type of linear constraint won't changed

adds nonlinear term to pseudo boolean constraint (if it is not zero)

Note: you can only add a coefficient if the special type of linear constraint won't changed

Parameters

scip	SCIP data structure
cons	pseudoboolean constraint
vars	variables of the nonlinear term
nvars	number of variables of the nonlinear term
val	coefficient of constraint entry

Definition at line 9426 of file cons_pseudoboolean.c.

References addCoefTerm(), CONSHDLR_NAME, NULL, ConsAndData::nvars, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPABORT, SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetIndVarPseudoboolean().

Referenced by SCIPaddCoefPseudoboolean().

◆ SCIPgetIndVarPseudoboolean()

SCIP_VAR* SCIPgetIndVarPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons
	)

gets indicator variable of pseudoboolean constraint, or NULL if there is no

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9451 of file cons_pseudoboolean.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetLinearConsPseudoboolean().

Referenced by SCIPaddTermPseudoboolean(), and writeOpbConstraints().

◆ SCIPgetLinearConsPseudoboolean()

SCIP_CONS* SCIPgetLinearConsPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons
	)

gets linear constraint of pseudoboolean constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9475 of file cons_pseudoboolean.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetLinearConsTypePseudoboolean().

Referenced by SCIPgetIndVarPseudoboolean(), and writeOpbConstraints().

◆ SCIPgetLinearConsTypePseudoboolean()

SCIP_LINEARCONSTYPE SCIPgetLinearConsTypePseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons
	)

gets type of linear constraint of pseudoboolean constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9499 of file cons_pseudoboolean.c.

References CONSHDLR_NAME, NULL, SCIP_LINEARCONSTYPE_INVALIDCONS, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetNLinVarsWithoutAndPseudoboolean().

Referenced by SCIPgetLinearConsPseudoboolean().

◆ SCIPgetNLinVarsWithoutAndPseudoboolean()

int SCIPgetNLinVarsWithoutAndPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons
	)

gets number of linear variables without artificial terms variables of pseudoboolean constraint

Parameters

scip	SCIP data structure
cons	pseudoboolean constraint

Definition at line 9523 of file cons_pseudoboolean.c.

References checkConsConsistency, CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetLinDatasWithoutAndPseudoboolean().

Referenced by SCIPgetLinearConsTypePseudoboolean(), and writeOpbConstraints().

◆ SCIPgetLinDatasWithoutAndPseudoboolean()

SCIP_RETCODE SCIPgetLinDatasWithoutAndPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons,
		SCIP_VAR **const	linvars,
		SCIP_Real *const	lincoefs,
		int *const	nlinvars
	)

gets linear constraint of pseudoboolean constraint

Parameters

scip	SCIP data structure
cons	pseudoboolean constraint
linvars	array to store and-constraints
lincoefs	array to store and-coefficients
nlinvars	pointer to store the required array size for and-constraints, have to be initialized with size of given array

Definition at line 9549 of file cons_pseudoboolean.c.

References checkConsConsistency, CONSHDLR_NAME, getLinearConsNVars(), getLinearConsVarsData(), getLinVarsAndAndRess(), NULL, ConsAndData::nvars, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_Real, SCIPABORT, SCIPallocBufferArray, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPfreeBufferArray, SCIPgetAndDatasPseudoboolean(), and ConsAndData::vars.

Referenced by SCIPgetNLinVarsWithoutAndPseudoboolean(), and writeOpbConstraints().

◆ SCIPgetAndDatasPseudoboolean()

SCIP_RETCODE SCIPgetAndDatasPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons,
		SCIP_CONS **const	andconss,
		SCIP_Real *const	andcoefs,
		int *const	nandconss
	)

gets and-constraints of pseudoboolean constraint

Parameters

scip	SCIP data structure
cons	pseudoboolean constraint
andconss	array to store and-constraints
andcoefs	array to store and-coefficients
nandconss	pointer to store the required array size for and-constraints, have to be initialized with size of given array

Definition at line 9609 of file cons_pseudoboolean.c.

References checkConsConsistency, CONSHDLR_NAME, NULL, SCIP_Bool, SCIP_INVALIDDATA, SCIP_OKAY, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPconsIsOriginal(), SCIPerrorMessage, SCIPgetNAndsPseudoboolean(), and TRUE.

Referenced by SCIPgetLinDatasWithoutAndPseudoboolean(), and writeOpbConstraints().

◆ SCIPgetNAndsPseudoboolean()

int SCIPgetNAndsPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons
	)

gets number of and constraints of pseudoboolean constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9669 of file cons_pseudoboolean.c.

References checkConsConsistency, CONSHDLR_NAME, NULL, SCIPABORT, SCIPchgLhsPseudoboolean(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPgetAndDatasPseudoboolean(), and writeOpbConstraints().

◆ SCIPchgLhsPseudoboolean()

SCIP_RETCODE SCIPchgLhsPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons,
		SCIP_Real const	lhs
	)

changes left hand side of pseudoboolean constraint

Note: you can only change the left hand side if the special type of linear constraint won't changed

changes left hand side of pseudoboolean constraint

Note: you can only change the left hand side if the special type of linear constraint won't changed

Parameters

scip	SCIP data structure
cons	constraint data
lhs	new left hand side

Definition at line 9701 of file cons_pseudoboolean.c.

References checkConsConsistency, chgLhs(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_LINEARCONSTYPE_INVALIDCONS, SCIP_LINEARCONSTYPE_KNAPSACK, SCIP_LINEARCONSTYPE_LINEAR, SCIP_LINEARCONSTYPE_LOGICOR, SCIP_LINEARCONSTYPE_SETPPC, SCIP_OKAY, SCIPchgRhsPseudoboolean(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPgetNAndsPseudoboolean().

◆ SCIPchgRhsPseudoboolean()

SCIP_RETCODE SCIPchgRhsPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons,
		SCIP_Real const	rhs
	)

changes right hand side of pseudoboolean constraint

Note: you can only change the right hand side if the special type of linear constraint won't changed

changes right hand side of pseudoboolean constraint

Note: you can only change the right hand side if the special type of linear constraint won't changed

Parameters

scip	SCIP data structure
cons	constraint data
rhs	new right hand side

Definition at line 9752 of file cons_pseudoboolean.c.

References checkConsConsistency, chgRhs(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_LINEARCONSTYPE_INVALIDCONS, SCIP_LINEARCONSTYPE_KNAPSACK, SCIP_LINEARCONSTYPE_LINEAR, SCIP_LINEARCONSTYPE_LOGICOR, SCIP_LINEARCONSTYPE_SETPPC, SCIP_OKAY, SCIP_Real, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetLhsPseudoboolean().

Referenced by SCIPchgLhsPseudoboolean().

◆ SCIPgetLhsPseudoboolean()

SCIP_Real SCIPgetLhsPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons
	)

get left hand side of pseudoboolean constraint

Parameters

scip	SCIP data structure
cons	pseudoboolean constraint

Definition at line 9794 of file cons_pseudoboolean.c.

References checkConsConsistency, CONSHDLR_NAME, NULL, SCIP_INVALID, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetRhsPseudoboolean().

Referenced by SCIPchgRhsPseudoboolean(), and writeOpbConstraints().

◆ SCIPgetRhsPseudoboolean()

SCIP_Real SCIPgetRhsPseudoboolean	(	SCIP *const	scip,
		SCIP_CONS *const	cons
	)

get right hand side of pseudoboolean constraint

Parameters

scip	SCIP data structure
cons	pseudoboolean constraint

Definition at line 9817 of file cons_pseudoboolean.c.

References checkConsConsistency, CONSHDLR_NAME, NULL, SCIP_INVALID, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPgetLhsPseudoboolean(), and writeOpbConstraints().

◆ SCIPincludeQuadconsUpgrade()

SCIP_RETCODE SCIPincludeQuadconsUpgrade	(	SCIP *	scip,
		SCIP_DECL_QUADCONSUPGD((*quadconsupgd))	,
		int	priority,
		SCIP_Bool	active,
		const char *	conshdlrname
	)

includes a quadratic constraint upgrade method into the quadratic constraint handler

includes a quadratic constraint update method into the quadratic constraint handler

Parameters

scip	SCIP data structure
priority	priority of upgrading method
active	should the upgrading method be active by default?
conshdlrname	name of the constraint handler

Definition at line 14187 of file cons_quadratic.c.

References active, SCIP_QuadConsUpgrade::active, CONSHDLR_NAME, conshdlrdataHasUpgrade(), FALSE, NULL, SCIP_QuadConsUpgrade::priority, SCIP_CALL, SCIP_MAXSTRLEN, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPaddBoolParam(), SCIPallocBlockMemory, SCIPcalcMemGrowSize(), SCIPconshdlrGetData(), SCIPcreateConsQuadratic(), SCIPerrorMessage, SCIPfindConshdlr(), SCIPreallocBlockMemoryArray, and SCIPsnprintf().

Referenced by SCIPincludeConshdlrAbspower(), SCIPincludeConshdlrBivariate(), SCIPincludeConshdlrBounddisjunction(), SCIPincludeConshdlrQuadratic(), and SCIPincludeConshdlrSOC().

◆ SCIPcreateConsQuadratic()

SCIP_RETCODE SCIPcreateConsQuadratic	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nlinvars,
		SCIP_VAR **	linvars,
		SCIP_Real *	lincoefs,
		int	nquadterms,
		SCIP_VAR **	quadvars1,
		SCIP_VAR **	quadvars2,
		SCIP_Real *	quadcoefs,
		SCIP_Real	lhs,
		SCIP_Real	rhs,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable
	)

Creates and captures a quadratic constraint.

The constraint should be given in the form

\[ \ell \leq \sum_{i=1}^n b_i x_i + \sum_{j=1}^m a_j y_j z_j \leq u, \]

where \(x_i = y_j = z_k\) is possible.

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nlinvars	number of linear terms (n)
linvars	array with variables in linear part (x_i)
lincoefs	array with coefficients of variables in linear part (b_i)
nquadterms	number of quadratic terms (m)
quadvars1	array with first variables in quadratic terms (y_j)
quadvars2	array with second variables in quadratic terms (z_j)
quadcoefs	array with coefficients of quadratic terms (a_j)
lhs	left hand side of quadratic equation (ell)
rhs	right hand side of quadratic equation (u)
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.

Definition at line 14263 of file cons_quadratic.c.

References addBilinearTerm(), addLinearCoef(), addQuadVarTerm(), consdataCreateEmpty(), consdataEnsureBilinSize(), consdataEnsureLinearVarsSize(), CONSHDLR_NAME, FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIP_Real, SCIPblkmem(), SCIPcreateCons(), SCIPcreateConsBasicQuadratic(), SCIPdebugMsg, SCIPdebugPrintCons, SCIPerrorMessage, SCIPfindConshdlr(), SCIPhashmapCreate(), SCIPhashmapExists(), SCIPhashmapFree(), SCIPhashmapGetImageInt(), SCIPhashmapInsertInt(), and SCIPisZero().

Referenced by createQuadraticCons(), readConstraints(), readObjective(), readQCMatrix(), readQMatrix(), readQuadraticCoefs(), SCIP_DECL_CONSPARSE(), SCIP_DECL_NONLINCONSUPGD(), SCIP_DECL_QUADCONSUPGD(), SCIPcreateConsBasicQuadratic(), SCIPcreateConsIndicator(), SCIPcreateConsIndicatorLinCons(), and SCIPincludeQuadconsUpgrade().

◆ SCIPcreateConsBasicQuadratic()

SCIP_RETCODE SCIPcreateConsBasicQuadratic	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nlinvars,
		SCIP_VAR **	linvars,
		SCIP_Real *	lincoefs,
		int	nquadterms,
		SCIP_VAR **	quadvars1,
		SCIP_VAR **	quadvars2,
		SCIP_Real *	quadcoefs,
		SCIP_Real	lhs,
		SCIP_Real	rhs
	)

creates and captures a quadratic constraint in its most basic variant, i. e., with all constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h

The constraint should be given in the form

\[ \ell \leq \sum_{i=1}^n b_i x_i + \sum_{j=1}^m a_j y_jz_j \leq u, \]

where \(x_i = y_j = z_k\) is possible.

See also: SCIPcreateConsQuadratic() for the default constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a quadratic constraint with all its flags set to their default values.

The constraint should be given in the form

\[ \ell \leq \sum_{i=1}^n b_i x_i + \sum_{j=1}^m a_j y_j z_j \leq u, \]

where \(x_i = y_j = z_k\) is possible.

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nlinvars	number of linear terms (n)
linvars	array with variables in linear part (x_i)
lincoefs	array with coefficients of variables in linear part (b_i)
nquadterms	number of quadratic terms (m)
quadvars1	array with first variables in quadratic terms (y_j)
quadvars2	array with second variables in quadratic terms (z_j)
quadcoefs	array with coefficients of quadratic terms (a_j)
lhs	left hand side of quadratic equation (ell)
rhs	right hand side of quadratic equation (u)

Definition at line 14445 of file cons_quadratic.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIPcreateConsQuadratic(), SCIPcreateConsQuadratic2(), and TRUE.

Referenced by createProbQP(), SCIPcreateConsQuadratic(), SCIPverifyCircularPatternNLP(), setupProblem(), and solvePricingMINLP().

◆ SCIPcreateConsQuadratic2()

SCIP_RETCODE SCIPcreateConsQuadratic2	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nlinvars,
		SCIP_VAR **	linvars,
		SCIP_Real *	lincoefs,
		int	nquadvarterms,
		SCIP_QUADVARTERM *	quadvarterms,
		int	nbilinterms,
		SCIP_BILINTERM *	bilinterms,
		SCIP_Real	lhs,
		SCIP_Real	rhs,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable
	)

creates and captures a quadratic constraint.

The constraint should be given in the form

\[ \ell \leq \sum_{i=1}^n b_i x_i + \sum_{j=1}^m (a_j y_j^2 + b_j y_j) + \sum_{k=1}^p c_k v_k w_k \leq u. \]

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Creates and captures a quadratic constraint.

The constraint should be given in the form

\[ \ell \leq \sum_{i=1}^n b_i x_i + \sum_{j=1}^m (a_j y_j^2 + b_j y_j) + \sum_{k=1}^p c_k v_k w_k \leq u. \]

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nlinvars	number of linear terms (n)
linvars	array with variables in linear part (x_i)
lincoefs	array with coefficients of variables in linear part (b_i)
nquadvarterms	number of quadratic terms (m)
quadvarterms	quadratic variable terms
nbilinterms	number of bilinear terms (p)
bilinterms	bilinear terms
lhs	constraint left hand side (ell)
rhs	constraint right hand side (u)
initial	should the LP relaxation of constraint be in the initial LP?
separate	should the constraint be separated during LP processing?
enforce	should the constraint be enforced during node processing?
check	should the constraint be checked for feasibility?
propagate	should the constraint be propagated during node processing?
local	is constraint only valid locally?
modifiable	is constraint modifiable (subject to column generation)?
dynamic	is constraint dynamic?
removable	should the constraint be removed from the LP due to aging or cleanup?

Definition at line 14476 of file cons_quadratic.c.

References consdataCreate(), CONSHDLR_NAME, FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPcreateCons(), SCIPcreateConsBasicQuadratic2(), SCIPerrorMessage, SCIPfindConshdlr(), and TRUE.

Referenced by presolveDisaggregate(), presolveRemoveFixedVariables(), SCIP_DECL_CONSCOPY(), SCIP_DECL_QUADCONSUPGD(), SCIPcreateConsBasicQuadratic(), and SCIPcreateConsBasicQuadratic2().

◆ SCIPcreateConsBasicQuadratic2()

SCIP_RETCODE SCIPcreateConsBasicQuadratic2	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nlinvars,
		SCIP_VAR **	linvars,
		SCIP_Real *	lincoefs,
		int	nquadvarterms,
		SCIP_QUADVARTERM *	quadvarterms,
		int	nbilinterms,
		SCIP_BILINTERM *	bilinterms,
		SCIP_Real	lhs,
		SCIP_Real	rhs
	)

creates and captures a quadratic constraint in its most basic variant, i. e., with all constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h

The constraint should be given in the form

\[ \ell \leq \sum_{i=1}^n b_i x_i + \sum_{j=1}^m (a_j y_j^2 + b_j y_j) + \sum_{k=1}^p c_kv_kw_k \leq u. \]

See also: SCIPcreateConsQuadratic2() for the default constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a quadratic constraint in its most basic version, i.e., all constraint flags are set to their default values.

The constraint should be given in the form

\[ \ell \leq \sum_{i=1}^n b_i x_i + \sum_{j=1}^m (a_j y_j^2 + b_j y_j) + \sum_{k=1}^p c_k v_k w_k \leq u. \]

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nlinvars	number of linear terms (n)
linvars	array with variables in linear part (x_i)
lincoefs	array with coefficients of variables in linear part (b_i)
nquadvarterms	number of quadratic terms (m)
quadvarterms	quadratic variable terms
nbilinterms	number of bilinear terms (p)
bilinterms	bilinear terms
lhs	constraint left hand side (ell)
rhs	constraint right hand side (u)

Definition at line 14538 of file cons_quadratic.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIPaddConstantQuadratic(), SCIPcreateConsQuadratic2(), and TRUE.

Referenced by SCIPcreateConsQuadratic2().

◆ SCIPaddConstantQuadratic()

void SCIPaddConstantQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_Real	constant
	)

Adds a constant to the constraint function, that is, subtracts a constant from both sides

Parameters

scip	SCIP data structure
cons	constraint
constant	constant to subtract from both sides

Definition at line 14562 of file cons_quadratic.c.

References NULL, REALABS, SCIP_STAGE_SOLVING, SCIPABORT, SCIPaddLinearVarQuadratic(), SCIPconsGetData(), SCIPconsIsEnabled(), SCIPerrorMessage, SCIPgetStage(), SCIPisEQ(), and SCIPisInfinity().

Referenced by SCIP_DECL_CONSPARSE(), SCIP_DECL_NONLINCONSUPGD(), and SCIPcreateConsBasicQuadratic2().

◆ SCIPaddLinearVarQuadratic()

SCIP_RETCODE SCIPaddLinearVarQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	coef
	)

Adds a linear variable with coefficient to a quadratic constraint.

Parameters

scip	SCIP data structure
cons	constraint
var	variable
coef	coefficient of variable

Definition at line 14598 of file cons_quadratic.c.

References addLinearCoef(), NULL, REALABS, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIP_STAGE_SOLVING, SCIPaddQuadVarQuadratic(), SCIPconsIsEnabled(), SCIPerrorMessage, SCIPgetStage(), and SCIPisInfinity().

Referenced by createProbQP(), presolveDisaggregate(), readObjective(), SCIP_DECL_CONSPARSE(), SCIP_DECL_QUADCONSUPGD(), SCIPaddConstantQuadratic(), and setupProblem().

◆ SCIPaddQuadVarQuadratic()

SCIP_RETCODE SCIPaddQuadVarQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	lincoef,
		SCIP_Real	sqrcoef
	)

Adds a quadratic variable with linear and square coefficient to a quadratic constraint.

Parameters

scip	SCIP data structure
cons	constraint
var	variable
lincoef	linear coefficient of variable
sqrcoef	square coefficient of variable

Definition at line 14623 of file cons_quadratic.c.

References addQuadVarTerm(), NULL, REALABS, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIP_STAGE_SOLVING, SCIPaddQuadVarLinearCoefQuadratic(), SCIPconsIsEnabled(), SCIPerrorMessage, SCIPgetStage(), and SCIPisInfinity().

Referenced by presolveDisaggregate(), SCIP_DECL_CONSPARSE(), SCIP_DECL_NONLINCONSUPGD(), SCIP_DECL_QUADCONSUPGD(), and SCIPaddLinearVarQuadratic().

◆ SCIPaddQuadVarLinearCoefQuadratic()

SCIP_RETCODE SCIPaddQuadVarLinearCoefQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	coef
	)

Adds a linear coefficient for a quadratic variable.

Variable will be added with square coefficient 0.0 if not existing yet.

Parameters

scip	SCIP data structure
cons	constraint
var	variable
coef	value to add to linear coefficient of variable

Definition at line 14653 of file cons_quadratic.c.

References addQuadVarTerm(), consdataFindQuadVarTerm(), FALSE, NULL, REALABS, SCIP_CALL, SCIP_INVALID, SCIP_INVALIDCALL, SCIP_OKAY, SCIP_STAGE_SOLVING, SCIPaddSquareCoefQuadratic(), SCIPconsGetData(), SCIPconsIsEnabled(), SCIPerrorMessage, SCIPgetStage(), SCIPintervalSetEmpty(), SCIPisInfinity(), and SCIPisZero().

Referenced by presolveDisaggregate(), SCIP_DECL_NONLINCONSUPGD(), SCIP_DECL_QUADCONSUPGD(), SCIPaddQuadVarQuadratic(), and setupProblem().

◆ SCIPaddSquareCoefQuadratic()

SCIP_RETCODE SCIPaddSquareCoefQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	coef
	)

Adds a square coefficient for a quadratic variable.

Variable will be added with linear coefficient 0.0 if not existing yet.

Parameters

scip	SCIP data structure
cons	constraint
var	variable
coef	value to add to square coefficient of variable

Definition at line 14706 of file cons_quadratic.c.

References addQuadVarTerm(), consdataFindQuadVarTerm(), FALSE, NULL, REALABS, SCIP_CALL, SCIP_INVALID, SCIP_INVALIDCALL, SCIP_OKAY, SCIP_STAGE_SOLVING, SCIPaddBilinTermQuadratic(), SCIPconsGetData(), SCIPconsIsEnabled(), SCIPerrorMessage, SCIPgetStage(), SCIPintervalSetEmpty(), SCIPisInfinity(), and SCIPisZero().

Referenced by SCIP_DECL_NONLINCONSUPGD(), SCIP_DECL_QUADCONSUPGD(), SCIPaddBilinTermQuadratic(), SCIPaddQuadVarLinearCoefQuadratic(), and setupProblem().

◆ SCIPaddBilinTermQuadratic()

SCIP_RETCODE SCIPaddBilinTermQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var1,
		SCIP_VAR *	var2,
		SCIP_Real	coef
	)

Adds a bilinear term to a quadratic constraint.

Variables will be added with linear and square coefficient 0.0 if not existing yet. If variables are equal, only the square coefficient of the variable is updated.

Parameters

scip	SCIP data structure
cons	constraint
var1	first variable
var2	second variable
coef	coefficient of bilinear term

Definition at line 14763 of file cons_quadratic.c.

References addBilinearTerm(), addQuadVarTerm(), consdataFindQuadVarTerm(), consdataSortQuadVarTerms(), NULL, REALABS, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIP_STAGE_SOLVING, SCIPaddSquareCoefQuadratic(), SCIPconsGetData(), SCIPconsIsEnabled(), SCIPerrorMessage, SCIPgetNlRowQuadratic(), SCIPgetStage(), and SCIPisInfinity().

Referenced by createProbQP(), presolveDisaggregate(), readQuadraticCoefs(), SCIP_DECL_CONSPARSE(), SCIP_DECL_NONLINCONSUPGD(), SCIP_DECL_QUADCONSUPGD(), SCIPaddSquareCoefQuadratic(), SCIPchgBilinCoefQuadratic(), and setupProblem().

◆ SCIPgetNlRowQuadratic()

SCIP_RETCODE SCIPgetNlRowQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_NLROW **	nlrow
	)

Gets the quadratic constraint as a nonlinear row representation.

Parameters

scip	SCIP data structure
cons	constraint
nlrow	pointer to store nonlinear row

Definition at line 14829 of file cons_quadratic.c.

References createNlRow(), NULL, SCIP_CALL, SCIP_OKAY, SCIPconsGetData(), and SCIPgetNLinearVarsQuadratic().

Referenced by createCoveringProblem(), and SCIPaddBilinTermQuadratic().

◆ SCIPgetNLinearVarsQuadratic()

int SCIPgetNLinearVarsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the number of variables in the linear part of a quadratic constraint.

Gets the number of variables in the linear term of a quadratic constraint.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 14854 of file cons_quadratic.c.

References NULL, SCIPconsGetData(), and SCIPgetLinearVarsQuadratic().

Referenced by checkConsQuadraticProblem(), SCIP_DECL_QUADCONSUPGD(), SCIPgetNlRowQuadratic(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), and SCIPwritePip().

◆ SCIPgetLinearVarsQuadratic()

SCIP_VAR** SCIPgetLinearVarsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the variables in the linear part of a quadratic constraint. Length is given by SCIPgetNLinearVarsQuadratic.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 14868 of file cons_quadratic.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetCoefsLinearVarsQuadratic().

Referenced by checkConsQuadraticProblem(), SCIP_DECL_QUADCONSUPGD(), SCIPgetNLinearVarsQuadratic(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), and SCIPwritePip().

◆ SCIPgetCoefsLinearVarsQuadratic()

SCIP_Real* SCIPgetCoefsLinearVarsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the coefficients in the linear part of a quadratic constraint. Length is given by SCIPgetNLinearVarsQuadratic.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 14882 of file cons_quadratic.c.

References NULL, SCIPconsGetData(), and SCIPgetNQuadVarTermsQuadratic().

Referenced by checkConsQuadraticProblem(), SCIP_DECL_QUADCONSUPGD(), SCIPgetLinearVarsQuadratic(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), and SCIPwritePip().

◆ SCIPgetNQuadVarTermsQuadratic()

int SCIPgetNQuadVarTermsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the number of quadratic variable terms of a quadratic constraint.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 14895 of file cons_quadratic.c.

References NULL, SCIPconsGetData(), and SCIPgetQuadVarTermsQuadratic().

Referenced by readNonlinearExprs(), SCIP_DECL_QUADCONSUPGD(), SCIPgetCoefsLinearVarsQuadratic(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), and SCIPwritePip().

◆ SCIPgetQuadVarTermsQuadratic()

SCIP_QUADVARTERM* SCIPgetQuadVarTermsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the quadratic variable terms of a quadratic constraint. Length is given by SCIPgetNQuadVarTermsQuadratic.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 14909 of file cons_quadratic.c.

References NULL, SCIPconsGetData(), and SCIPsortQuadVarTermsQuadratic().

Referenced by readNonlinearExprs(), SCIP_DECL_QUADCONSUPGD(), SCIPgetNQuadVarTermsQuadratic(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), and SCIPwritePip().

◆ SCIPsortQuadVarTermsQuadratic()

SCIP_RETCODE SCIPsortQuadVarTermsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Ensures that quadratic variable terms are sorted.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 14921 of file cons_quadratic.c.

References consdataSortQuadVarTerms(), NULL, SCIP_CALL, SCIP_OKAY, SCIPconsGetData(), and SCIPfindQuadVarTermQuadratic().

Referenced by readNonlinearExprs(), SCIP_DECL_QUADCONSUPGD(), and SCIPgetQuadVarTermsQuadratic().

◆ SCIPfindQuadVarTermQuadratic()

SCIP_RETCODE SCIPfindQuadVarTermQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		int *	pos
	)

Finds the position of a quadratic variable term for a given variable.

Note: If the quadratic variable terms have not been sorted before, then a search may reorder the current order of the terms.

Parameters

scip	SCIP data structure
cons	constraint
var	variable to search for
pos	buffer to store position of quadvarterm for var, or -1 if not found

Definition at line 14938 of file cons_quadratic.c.

References consdataFindQuadVarTerm(), NULL, SCIP_CALL, SCIP_OKAY, SCIPconsGetData(), and SCIPgetNBilinTermsQuadratic().

Referenced by readNonlinearExprs(), SCIP_DECL_CONSPARSE(), SCIP_DECL_QUADCONSUPGD(), and SCIPsortQuadVarTermsQuadratic().

◆ SCIPgetNBilinTermsQuadratic()

int SCIPgetNBilinTermsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the number of bilinear terms of a quadratic constraint.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 14956 of file cons_quadratic.c.

References NULL, SCIPconsGetData(), and SCIPgetBilinTermsQuadratic().

Referenced by readNonlinearExprs(), SCIP_DECL_QUADCONSUPGD(), SCIPfindQuadVarTermQuadratic(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), and SCIPwritePip().

◆ SCIPgetBilinTermsQuadratic()

SCIP_BILINTERM* SCIPgetBilinTermsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the bilinear terms of a quadratic constraint. Length is given by SCIPgetNBilinTermQuadratic.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 14970 of file cons_quadratic.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetLhsQuadratic().

Referenced by readNonlinearExprs(), SCIP_DECL_QUADCONSUPGD(), SCIPgetNBilinTermsQuadratic(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), and SCIPwritePip().

◆ SCIPgetLhsQuadratic()

SCIP_Real SCIPgetLhsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the left hand side of a quadratic constraint.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 14982 of file cons_quadratic.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetRhsQuadratic().

Referenced by checkConsnames(), checkConsQuadraticProblem(), createCoveringProblem(), SCIP_DECL_QUADCONSUPGD(), SCIPgetBilinTermsQuadratic(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), and SCIPwritePip().

◆ SCIPgetRhsQuadratic()

SCIP_Real SCIPgetRhsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the right hand side of a quadratic constraint.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 14994 of file cons_quadratic.c.

References NULL, SCIPconsGetData(), and SCIPgetLinvarMayDecreaseQuadratic().

Referenced by checkConsnames(), checkConsQuadraticProblem(), createCoveringProblem(), SCIP_DECL_QUADCONSUPGD(), SCIPgetLhsQuadratic(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), and SCIPwritePip().

◆ SCIPgetLinvarMayDecreaseQuadratic()

int SCIPgetLinvarMayDecreaseQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

get index of a variable in linvars that may be decreased without making any other constraint infeasible, or -1 if none

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 15006 of file cons_quadratic.c.

References consdataFindUnlockedLinearVar(), NULL, SCIPconsGetData(), and SCIPgetLinvarMayIncreaseQuadratic().

Referenced by checkConsQuadraticProblem(), and SCIPgetRhsQuadratic().

◆ SCIPgetLinvarMayIncreaseQuadratic()

int SCIPgetLinvarMayIncreaseQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

get index of a variable in linvars that may be increased without making any other constraint infeasible, or -1 if none

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 15025 of file cons_quadratic.c.

References consdataFindUnlockedLinearVar(), NULL, SCIPcheckCurvatureQuadratic(), and SCIPconsGetData().

Referenced by checkConsQuadraticProblem(), and SCIPgetLinvarMayDecreaseQuadratic().

◆ SCIPcheckCurvatureQuadratic()

SCIP_RETCODE SCIPcheckCurvatureQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Check the quadratic function of a quadratic constraint for its semi-definiteness, if not done yet.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 15044 of file cons_quadratic.c.

References checkCurvature(), NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIPisConvexQuadratic(), and TRUE.

Referenced by SCIP_DECL_QUADCONSUPGD(), and SCIPgetLinvarMayIncreaseQuadratic().

◆ SCIPisConvexQuadratic()

SCIP_Bool SCIPisConvexQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Indicates whether the quadratic function of a quadratic constraint is (known to be) convex.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 15057 of file cons_quadratic.c.

References checkCurvatureEasy(), FALSE, NULL, SCIP_Bool, SCIPconsGetData(), and SCIPisConcaveQuadratic().

Referenced by createCoveringProblem(), SCIP_DECL_QUADCONSUPGD(), and SCIPcheckCurvatureQuadratic().

◆ SCIPisConcaveQuadratic()

SCIP_Bool SCIPisConcaveQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Indicates whether the quadratic function of a quadratic constraint is (known to be) concave.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 15074 of file cons_quadratic.c.

References checkCurvatureEasy(), FALSE, NULL, SCIP_Bool, SCIPconsGetData(), and SCIPgetViolationQuadratic().

Referenced by createCoveringProblem(), SCIP_DECL_QUADCONSUPGD(), and SCIPisConvexQuadratic().

◆ SCIPgetViolationQuadratic()

SCIP_RETCODE SCIPgetViolationQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SOL *	sol,
		SCIP_Real *	violation
	)

Gets the violation of a constraint by a solution.

Computes the violation of a constraint by a solution

Parameters

scip	SCIP data structure
cons	constraint
sol	solution which violation to calculate, or NULL for LP solution
violation	pointer to store violation of constraint

Definition at line 15091 of file cons_quadratic.c.

References computeViolation(), MAX, NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIPconsGetData(), and SCIPisLinearLocalQuadratic().

Referenced by SCIPisConcaveQuadratic().

◆ SCIPisLinearLocalQuadratic()

SCIP_Bool SCIPisLinearLocalQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Indicates whether the quadratic constraint is local w.r.t. the current local bounds.

That is, checks whether each variable with a square term is fixed and for each bilinear term at least one variable is fixed.

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 15120 of file cons_quadratic.c.

References FALSE, NULL, SCIPaddToNlpiProblemQuadratic(), SCIPconsGetData(), SCIPisRelEQ(), SCIPvarGetLbLocal(), SCIPvarGetUbLocal(), and TRUE.

Referenced by SCIPgetViolationQuadratic().

◆ SCIPaddToNlpiProblemQuadratic()

SCIP_RETCODE SCIPaddToNlpiProblemQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_NLPI *	nlpi,
		SCIP_NLPIPROBLEM *	nlpiprob,
		SCIP_HASHMAP *	scipvar2nlpivar,
		SCIP_Bool	names
	)

Adds the constraint to an NLPI problem.

Parameters

scip	SCIP data structure
cons	constraint
nlpi	interface to NLP solver
nlpiprob	NLPI problem where to add constraint
scipvar2nlpivar	mapping from SCIP variables to variable indices in NLPI
names	whether to pass constraint names to NLPI

Definition at line 15166 of file cons_quadratic.c.

References SCIP_QuadElement::coef, SCIP_QuadElement::idx1, SCIP_QuadElement::idx2, MAX, MIN, NULL, SCIP_CALL, SCIP_OKAY, SCIP_Real, SCIPallocBufferArray, SCIPchgLhsQuadratic(), SCIPconsGetData(), SCIPconsGetName(), SCIPfreeBufferArrayNull, SCIPhashmapExists(), SCIPhashmapGetImageInt(), and SCIPnlpiAddConstraints().

Referenced by SCIPisLinearLocalQuadratic().

◆ SCIPchgLhsQuadratic()

SCIP_RETCODE SCIPchgLhsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_Real	lhs
	)

sets the left hand side of a quadratic constraint

Note: This method may only be called during problem creation stage for an original constraint.

Parameters

scip	SCIP data structure
cons	constraint data
lhs	new left hand side

Definition at line 15304 of file cons_quadratic.c.

References CONSHDLR_NAME, NULL, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_STAGE_PROBLEM, SCIPchgRhsQuadratic(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPconsIsOriginal(), SCIPerrorMessage, SCIPgetStage(), SCIPinfinity(), SCIPisInfinity(), and SCIPisLE().

Referenced by SCIPaddToNlpiProblemQuadratic().

◆ SCIPchgRhsQuadratic()

SCIP_RETCODE SCIPchgRhsQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_Real	rhs
	)

sets the right hand side of a quadratic constraint

Note: This method may only be called during problem creation stage for an original constraint.

Parameters

scip	SCIP data structure
cons	constraint data
rhs	new right hand side

Definition at line 15349 of file cons_quadratic.c.

References CONSHDLR_NAME, NULL, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_STAGE_PROBLEM, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPconsIsOriginal(), SCIPerrorMessage, SCIPgetFeasibilityQuadratic(), SCIPgetStage(), SCIPinfinity(), SCIPisInfinity(), and SCIPisLE().

Referenced by SCIPchgLhsQuadratic().

◆ SCIPgetFeasibilityQuadratic()

SCIP_RETCODE SCIPgetFeasibilityQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SOL *	sol,
		SCIP_Real *	feasibility
	)

gets the feasibility of the quadratic constraint in the given solution

Parameters

scip	SCIP data structure
cons	constraint data
sol	solution, or NULL to use current node's solution
feasibility	pointer to store the feasibility

Definition at line 15391 of file cons_quadratic.c.

References computeViolation(), CONSHDLR_NAME, MIN, NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPgetActivityQuadratic(), SCIPinfinity(), and SCIPisInfinity().

Referenced by SCIPchgRhsQuadratic().

◆ SCIPgetActivityQuadratic()

SCIP_RETCODE SCIPgetActivityQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_SOL *	sol,
		SCIP_Real *	activity
	)

gets the activity of the quadratic constraint in the given solution

Parameters

scip	SCIP data structure
cons	constraint data
sol	solution, or NULL to use current node's solution
activity	pointer to store the activity

Definition at line 15433 of file cons_quadratic.c.

References computeViolation(), CONSHDLR_NAME, NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIPABORT, SCIPchgLinearCoefQuadratic(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPgetFeasibilityQuadratic().

◆ SCIPchgLinearCoefQuadratic()

SCIP_RETCODE SCIPchgLinearCoefQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	coef
	)

changes the linear coefficient value for a given quadratic variable in a quadratic constraint data; if not available, it adds it

Note: this is only allowed for original constraints and variables in problem creation stage

Parameters

scip	SCIP data structure
cons	constraint data
var	quadratic variable
coef	new coefficient

Definition at line 15468 of file cons_quadratic.c.

References addLinearCoef(), chgLinearCoefPos(), CONSHDLR_NAME, delLinearCoefPos(), FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_INVALID, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_STAGE_PROBLEM, SCIPchgSquareCoefQuadratic(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPconsIsOriginal(), SCIPerrorMessage, SCIPgetStage(), SCIPintervalSetEmpty(), SCIPisZero(), SCIPvarIsOriginal(), and TRUE.

Referenced by SCIPgetActivityQuadratic().

◆ SCIPchgSquareCoefQuadratic()

SCIP_RETCODE SCIPchgSquareCoefQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	coef
	)

changes the square coefficient value for a given quadratic variable in a quadratic constraint data; if not available, it adds it

Note: this is only allowed for original constraints and variables in problem creation stage

Parameters

scip	SCIP data structure
cons	constraint data
var	quadratic variable
coef	new coefficient

Definition at line 15561 of file cons_quadratic.c.

References addQuadVarTerm(), CONSHDLR_NAME, FALSE, NULL, REALABS, SCIP_Bool, SCIP_CALL, SCIP_INVALID, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_STAGE_PROBLEM, SCIPchgBilinCoefQuadratic(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPconsIsOriginal(), SCIPerrorMessage, SCIPgetStage(), SCIPintervalSetEmpty(), SCIPisInfinity(), SCIPisZero(), SCIPvarIsOriginal(), and TRUE.

Referenced by SCIPchgBilinCoefQuadratic(), and SCIPchgLinearCoefQuadratic().

◆ SCIPchgBilinCoefQuadratic()

SCIP_RETCODE SCIPchgBilinCoefQuadratic	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var1,
		SCIP_VAR *	var2,
		SCIP_Real	coef
	)

changes the bilinear coefficient value for a given quadratic variable in a quadratic constraint data; if not available, it adds it

Note: this is only allowed for original constraints and variables in problem creation stage

Parameters

scip	SCIP data structure
cons	constraint
var1	first variable
var2	second variable
coef	coefficient of bilinear term

Definition at line 15630 of file cons_quadratic.c.

References CONSHDLR_NAME, FALSE, NULL, REALABS, SCIP_Bool, SCIP_CALL, SCIP_INVALID, SCIP_INVALIDDATA, SCIP_OKAY, SCIP_STAGE_PROBLEM, SCIPaddBilinTermQuadratic(), SCIPchgSquareCoefQuadratic(), SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPconsIsOriginal(), SCIPerrorMessage, SCIPgetNAllBilinearTermsQuadratic(), SCIPgetStage(), SCIPintervalSetEmpty(), SCIPisInfinity(), SCIPisZero(), SCIPvarIsOriginal(), and TRUE.

Referenced by SCIPchgSquareCoefQuadratic().

◆ SCIPgetNAllBilinearTermsQuadratic()

int SCIPgetNAllBilinearTermsQuadratic ( SCIP * scip )

returns the total number of bilinear terms that are contained in all quadratic constraints

Parameters

scip	SCIP data structure

Definition at line 15709 of file cons_quadratic.c.

References CONSHDLR_NAME, NULL, SCIPconshdlrGetData(), SCIPfindConshdlr(), and SCIPgetAllBilinearTermsQuadratic().

Referenced by SCIPchgBilinCoefQuadratic().

◆ SCIPgetAllBilinearTermsQuadratic()

SCIP_RETCODE SCIPgetAllBilinearTermsQuadratic	(	SCIP *	scip,
		SCIP_VAR **RESTRICT	x,
		SCIP_VAR **RESTRICT	y,
		int *RESTRICT	nbilinterms,
		int *RESTRICT	nunderests,
		int *RESTRICT	noverests,
		SCIP_Real *	maxnonconvexity
	)

returns all bilinear terms that are contained in all quadratic constraints

Parameters

scip	SCIP data structure
x	array to store first variable of each bilinear term
y	array to second variable of each bilinear term
nbilinterms	buffer to store the total number of bilinear terms
nunderests	array to store the total number of constraints that require to underestimate a bilinear term
noverests	array to store the total number of constraints that require to overestimate a bilinear term
maxnonconvexity	largest absolute value of nonconvex eigenvalues of all quadratic constraints containing a bilinear term

Definition at line 15730 of file cons_quadratic.c.

References CONSHDLR_NAME, getIneqViol(), NULL, SCIP_OKAY, SCIPconshdlrGetData(), and SCIPfindConshdlr().

Referenced by SCIPgetNAllBilinearTermsQuadratic().

◆ SCIPaddBilinearIneqQuadratic()

SCIP_RETCODE SCIPaddBilinearIneqQuadratic	(	SCIP *	scip,
		SCIP_VAR *	x,
		SCIP_VAR *	y,
		int	idx,
		SCIP_Real	xcoef,
		SCIP_Real	ycoef,
		SCIP_Real	constant,
		SCIP_Bool *	success
	)

adds a globally valid inequality of the form xcoef x <= ycoef y + constant for a bilinear term (x,y)

Note: the indices of bilinear terms match with the entries of bilinear terms returned by SCIPgetAllBilinearTermsQuadratic

Parameters

scip	SCIP data structure
x	first variable
y	second variable
idx	index of the bilinear term
xcoef	x coefficient
ycoef	y coefficient
constant	constant part
success	buffer to store whether inequality has been accepted

Definition at line 15819 of file cons_quadratic.c.

References CONSHDLR_NAME, FALSE, getIneqViol(), BilinearEstimator::ineqoverest, BilinearEstimator::inequnderest, MAX, BilinearEstimator::nineqoverest, BilinearEstimator::ninequnderest, NULL, SCIP_INVALID, SCIP_OKAY, SCIP_Real, SCIPconshdlrGetData(), SCIPcreateRowprep(), SCIPdebugMsg, SCIPfindConshdlr(), SCIPisFeasEQ(), SCIPisFeasLE(), SCIPisFeasZero(), SCIPisGT(), SCIPvarGetName(), TRUE, BilinearEstimator::x, and BilinearEstimator::y.

Referenced by getIneqViol().

◆ SCIPcreateConsSetpart()

SCIP_RETCODE SCIPcreateConsSetpart	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a set partitioning constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 9058 of file cons_setppc.c.

References createConsSetppc(), SCIP_SETPPCTYPE_PARTITIONING, and SCIPcreateConsBasicSetpart().

Referenced by branchOnVertex(), cliquePresolve(), consdataLinearize(), createAndAddLinearCons(), createMipCpFormulation(), createProbQP(), createProbSimplified(), createProbSimplifiedTest(), extractGates(), and processIntegerBoundChg().

◆ SCIPcreateConsBasicSetpart()

SCIP_RETCODE SCIPcreateConsBasicSetpart	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars
	)

creates and captures a set partitioning constraint in its most basic variant, i. e., with all constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h

See also: SCIPcreateConsSetpart() for the default constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a set partitioning constraint with all constraint flags set to their default values

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries

Definition at line 9098 of file cons_setppc.c.

Referenced by createCipFormulation(), createMipFormulation(), SCIP_DECL_SOLVECUMULATIVE(), SCIPcreateConsSetpart(), and setupProblem().

◆ SCIPcreateConsSetpack()

SCIP_RETCODE SCIPcreateConsSetpack	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a set packing constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 9116 of file cons_setppc.c.

References createConsSetppc(), SCIP_SETPPCTYPE_PACKING, and SCIPcreateConsBasicSetpack().

Referenced by addCliques(), addExtraCliques(), cliquePresolve(), consdataLinearize(), createAndAddLinearCons(), createCoveringProblem(), createPrizeConstraints(), deleteRedundantVars(), detectRedundantVars(), dualWeightsTightening(), fixDeleteOrUpgradeCons(), presolRoundConsSOS1(), removeConstraintsDueToNegCliques(), tightenWeights(), upgradeCons(), and upgradeConss().

◆ SCIPcreateConsBasicSetpack()

SCIP_RETCODE SCIPcreateConsBasicSetpack	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars
	)

creates and captures a set packing constraint in its most basic variant, i. e., with all constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h

See also: SCIPcreateConsSetpack() for the default constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a set packing constraint with all constraint flags set to their default values

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries

Definition at line 9156 of file cons_setppc.c.

Referenced by createSetPackingCons(), and SCIPcreateConsSetpack().

◆ SCIPcreateConsSetcover()

SCIP_RETCODE SCIPcreateConsSetcover	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a set covering constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 9174 of file cons_setppc.c.

References createConsSetppc(), SCIP_SETPPCTYPE_COVERING, and SCIPcreateConsBasicSetcover().

Referenced by COLORprobSetUpArrayOfCons(), createAndAddLinearCons(), CUTOFF_CONSTRAINT(), forbidCover(), forbidFixation(), processNlRow(), and readCnf().

◆ SCIPcreateConsBasicSetcover()

SCIP_RETCODE SCIPcreateConsBasicSetcover	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars
	)

creates and captures a set packing constraint in its most basic variant, i. e., with all constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h

See also: SCIPcreateConsSetpack() for the default constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a set covering constraint with all constraint flags set to their default values

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries

Definition at line 9214 of file cons_setppc.c.

Referenced by SCIPcreateConsSetcover(), and SCIPprobdataCreate().

◆ SCIPaddCoefSetppc()

SCIP_RETCODE SCIPaddCoefSetppc	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var
	)

adds coefficient in set partitioning / packing / covering constraint

Parameters

scip	SCIP data structure
cons	constraint data
var	variable to add to the constraint

Definition at line 9229 of file cons_setppc.c.

References addCoef(), CONSHDLR_NAME, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetNVarsSetppc().

Referenced by addCoefTerm(), branchOnVertex(), cliquePresolve(), createCipFormulation(), createInitialColumns(), createMipCpFormulation(), createMipFormulation(), createProbQP(), createProbSimplified(), createProbSimplifiedTest(), createSetPackingCons(), createVariables(), SCIP_DECL_HEUREXEC(), SCIP_DECL_PRICERFARKAS(), SCIP_DECL_PRICERREDCOST(), SCIP_DECL_READERREAD(), SCIP_DECL_SOLVECUMULATIVE(), and SCIPaddCoefPseudoboolean().

◆ SCIPgetNVarsSetppc()

int SCIPgetNVarsSetppc	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets number of variables in set partitioning / packing / covering constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9252 of file cons_setppc.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVarsSetppc().

Referenced by addSetppcConstraints(), cleanupHashDatas(), computeSymmetryGroup(), correctPresoldata(), createAltLP(), createPresoldata(), getLinearConsNVars(), getLinearConsVarsData(), packingUpgrade(), presolveAddKKTSetppcConss(), SCIP_DECL_BRANCHEXECLP(), SCIPaddCoefSetppc(), SCIPmatrixCreate(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), strenghtenOrbitopeConstraint(), writeFzn(), writeOpbConstraints(), and writeOpbObjective().

◆ SCIPgetVarsSetppc()

SCIP_VAR** SCIPgetVarsSetppc	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of variables in set partitioning / packing / covering constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9273 of file cons_setppc.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetTypeSetppc().

Referenced by addSetppcConstraints(), computeSymmetryGroup(), correctPresoldata(), createAltLP(), createPresoldata(), getLinearConsVarsData(), packingUpgrade(), presolveAddKKTSetppcConss(), saveConsLinear(), SCIP_DECL_BRANCHEXECLP(), SCIPgetNVarsSetppc(), SCIPmatrixCreate(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), strenghtenOrbitopeConstraint(), writeFzn(), writeOpbConstraints(), and writeOpbObjective().

◆ SCIPgetTypeSetppc()

SCIP_SETPPCTYPE SCIPgetTypeSetppc	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets type of set partitioning / packing / covering constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9294 of file cons_setppc.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetDualsolSetppc().

Referenced by addSetppcConstraints(), cleanupHashDatas(), computeSymmetryGroup(), correctPresoldata(), createAltLP(), createPresoldata(), findAggregation(), getLinearConsSides(), packingUpgrade(), presolveAddKKTSetppcConss(), saveConsLinear(), SCIPconsGetLhs(), SCIPconsGetRhs(), SCIPgetVarsSetppc(), SCIPmatrixCreate(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePip(), strenghtenOrbitopeConstraint(), tryUpgradingSetppc(), writeFzn(), and writeOpbConstraints().

◆ SCIPgetDualsolSetppc()

SCIP_Real SCIPgetDualsolSetppc	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the dual solution of the set partitioning / packing / covering constraint in the current LP

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9314 of file cons_setppc.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPgetDualfarkasSetppc(), and SCIProwGetDualsol().

Referenced by initPricing(), SCIP_DECL_PRICERREDCOST(), SCIPconsGetDualsol(), and SCIPgetTypeSetppc().

◆ SCIPgetDualfarkasSetppc()

SCIP_Real SCIPgetDualfarkasSetppc	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the dual Farkas value of the set partitioning / packing / covering constraint in the current infeasible LP

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9338 of file cons_setppc.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPgetRowSetppc(), and SCIProwGetDualfarkas().

Referenced by SCIPconsGetDualfarkas(), and SCIPgetDualsolSetppc().

◆ SCIPgetRowSetppc()

SCIP_ROW* SCIPgetRowSetppc	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the linear relaxation of the given set partitioning / packing / covering constraint; may return NULL if no LP row was yet created; the user must not modify the row!

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9364 of file cons_setppc.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetNFixedonesSetppc().

Referenced by SCIPconsGetRow(), and SCIPgetDualfarkasSetppc().

◆ SCIPgetNFixedonesSetppc()

int SCIPgetNFixedonesSetppc	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns current number of variables fixed to one in the constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9385 of file cons_setppc.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetNFixedzerosSetppc().

Referenced by addFixedVarsConss(), initPricing(), SCIP_DECL_PRICERREDCOST(), and SCIPgetRowSetppc().

◆ SCIPgetNFixedzerosSetppc()

int SCIPgetNFixedzerosSetppc	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns current number of variables fixed to zero in the constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 9407 of file cons_setppc.c.

References NULL, SCIPABORT, SCIPconsGetData(), and SCIPerrorMessage.

Referenced by SCIPgetNFixedonesSetppc().

◆ SCIPcreateConsSOC()

SCIP_RETCODE SCIPcreateConsSOC	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Real *	coefs,
		SCIP_Real *	offsets,
		SCIP_Real	constant,
		SCIP_VAR *	rhsvar,
		SCIP_Real	rhscoeff,
		SCIP_Real	rhsoffset,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable
	)

creates and captures a second order cone constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables on left hand side of constraint (n)
vars	array with variables on left hand side (x_i)
coefs	array with coefficients of left hand side variables (alpha_i), or NULL if all 1.0
offsets	array with offsets of variables (beta_i), or NULL if all 0.0
constant	constant on left hand side (gamma)
rhsvar	variable on right hand side of constraint (x_{n+1})
rhscoeff	coefficient of variable on right hand side (alpha_{n+1})
rhsoffset	offset of variable on right hand side (beta_{n+1})
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.

Definition at line 5198 of file cons_soc.c.

References ABS, BMSclearMemoryArray, catchVarEvents(), CONSHDLR_NAME, FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPallocBlockMemory, SCIPallocBlockMemoryArray, SCIPcaptureVar(), SCIPcomputeVarLbGlobal(), SCIPcomputeVarLbLocal(), SCIPcomputeVarUbGlobal(), SCIPcomputeVarUbLocal(), SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicSOC(), SCIPduplicateBlockMemoryArray, SCIPerrorMessage, SCIPfindConshdlr(), SCIPisGE(), SCIPisInfinity(), SCIPisLE(), and SCIPisTransformed().

Referenced by SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIP_DECL_QUADCONSUPGD(), SCIPcreateConsBasicSOC(), and SCIPincludeConshdlrSOC().

◆ SCIPcreateConsBasicSOC()

SCIP_RETCODE SCIPcreateConsBasicSOC	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Real *	coefs,
		SCIP_Real *	offsets,
		SCIP_Real	constant,
		SCIP_VAR *	rhsvar,
		SCIP_Real	rhscoeff,
		SCIP_Real	rhsoffset
	)

creates and captures a second order cone constraint in its most basic variant, i. e., with all constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h

See also: SCIPcreateConsSOC() for the default constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a second order cone constraint with all its constraint flags set to their default values

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables on left hand side of constraint (n)
vars	array with variables on left hand side (x_i)
coefs	array with coefficients of left hand side variables (alpha_i), or NULL if all 1.0
offsets	array with offsets of variables (beta_i), or NULL if all 0.0
constant	constant on left hand side (gamma)
rhsvar	variable on right hand side of constraint (x_{n+1})
rhscoeff	coefficient of variable on right hand side (alpha_{n+1})
rhsoffset	offset of variable on right hand side (beta_{n+1})

Definition at line 5327 of file cons_soc.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIPcreateConsSOC(), SCIPgetNlRowSOC(), and TRUE.

Referenced by disaggregate(), SCIPcreateConsSOC(), and setupProblem().

◆ SCIPgetNlRowSOC()

SCIP_RETCODE SCIPgetNlRowSOC	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_NLROW **	nlrow
	)

Gets the SOC constraint as a nonlinear row representation.

Parameters

scip	SCIP data structure
cons	constraint
nlrow	pointer to store nonlinear row

Definition at line 5349 of file cons_soc.c.

References createNlRow(), NULL, SCIP_CALL, SCIP_OKAY, SCIPconsGetData(), SCIPconsGetHdlr(), and SCIPgetNLhsVarsSOC().

Referenced by createCoveringProblem(), and SCIPcreateConsBasicSOC().

◆ SCIPgetNLhsVarsSOC()

int SCIPgetNLhsVarsSOC	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the number of variables on the left hand side of a SOC constraint.

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5374 of file cons_soc.c.

References NULL, SCIPconsGetData(), and SCIPgetLhsVarsSOC().

Referenced by createCoveringProblem(), printSOCCons(), SCIPgetNlRowSOC(), SCIPwriteGms(), SCIPwriteLp(), and SCIPwriteMps().

◆ SCIPgetLhsVarsSOC()

SCIP_VAR** SCIPgetLhsVarsSOC	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the variables on the left hand side of a SOC constraint.

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5386 of file cons_soc.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetLhsCoefsSOC().

Referenced by createCoveringProblem(), printSOCCons(), SCIPgetNLhsVarsSOC(), SCIPwriteGms(), SCIPwriteLp(), and SCIPwriteMps().

◆ SCIPgetLhsCoefsSOC()

SCIP_Real* SCIPgetLhsCoefsSOC	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the coefficients of the variables on the left hand side of a SOC constraint, or NULL if all are equal to 1.0.

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5398 of file cons_soc.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetLhsOffsetsSOC().

Referenced by createCoveringProblem(), printSOCCons(), SCIPgetLhsVarsSOC(), SCIPwriteGms(), and SCIPwriteMps().

◆ SCIPgetLhsOffsetsSOC()

SCIP_Real* SCIPgetLhsOffsetsSOC	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the offsets of the variables on the left hand side of a SOC constraint, or NULL if all are equal to 0.0.

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5410 of file cons_soc.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetLhsConstantSOC().

Referenced by printSOCCons(), SCIPgetLhsCoefsSOC(), SCIPwriteGms(), and SCIPwriteMps().

◆ SCIPgetLhsConstantSOC()

SCIP_Real SCIPgetLhsConstantSOC	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the constant on the left hand side of a SOC constraint.

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5422 of file cons_soc.c.

References NULL, SCIPconsGetData(), and SCIPgetRhsVarSOC().

Referenced by printSOCCons(), SCIPgetLhsOffsetsSOC(), SCIPwriteGms(), and SCIPwriteMps().

◆ SCIPgetRhsVarSOC()

SCIP_VAR* SCIPgetRhsVarSOC	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the variable on the right hand side of a SOC constraint.

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5434 of file cons_soc.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetRhsCoefSOC().

Referenced by createCoveringProblem(), printSOCCons(), SCIPgetLhsConstantSOC(), SCIPwriteGms(), SCIPwriteLp(), and SCIPwriteMps().

◆ SCIPgetRhsCoefSOC()

SCIP_Real SCIPgetRhsCoefSOC	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the coefficient of the variable on the right hand side of a SOC constraint.

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5446 of file cons_soc.c.

References NULL, SCIP_Real, SCIPconsGetData(), and SCIPgetRhsOffsetSOC().

Referenced by createCoveringProblem(), printSOCCons(), SCIPgetRhsVarSOC(), SCIPwriteGms(), and SCIPwriteMps().

◆ SCIPgetRhsOffsetSOC()

SCIP_Real SCIPgetRhsOffsetSOC	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

Gets the offset of the variables on the right hand side of a SOC constraint.

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5458 of file cons_soc.c.

References NULL, SCIPaddToNlpiProblemSOC(), and SCIPconsGetData().

Referenced by printSOCCons(), SCIPgetRhsCoefSOC(), SCIPwriteGms(), and SCIPwriteMps().

◆ SCIPaddToNlpiProblemSOC()

SCIP_RETCODE SCIPaddToNlpiProblemSOC	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_NLPI *	nlpi,
		SCIP_NLPIPROBLEM *	nlpiprob,
		SCIP_HASHMAP *	scipvar2nlpivar,
		SCIP_Bool	names
	)

Adds the constraint to an NLPI problem. Uses nonconvex formulation as quadratic function.

Parameters

scip	SCIP data structure
cons	SOC constraint
nlpi	interface to NLP solver
nlpiprob	NLPI problem where to add constraint
scipvar2nlpivar	mapping from SCIP variables to variable indices in NLPI
names	whether to pass constraint names to NLPI

Definition at line 5472 of file cons_soc.c.

References SCIP_QuadElement::coef, SCIP_QuadElement::idx1, SCIP_QuadElement::idx2, NULL, SCIP_CALL, SCIP_OKAY, SCIP_Real, SCIPallocBufferArray, SCIPconsGetData(), SCIPconsGetName(), SCIPfreeBufferArray, SCIPfreeBufferArrayNull, SCIPhashmapGetImageInt(), SCIPinfinity(), and SCIPnlpiAddConstraints().

Referenced by SCIPgetRhsOffsetSOC().

◆ SCIPcreateConsSOS1()

SCIP_RETCODE SCIPcreateConsSOS1	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Real *	weights,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures an SOS1 constraint

We set the constraint to not be modifable. If the weights are non NULL, the variables are ordered according to these weights (in ascending order).

Note: The constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons().

creates and captures a SOS1 constraint

We set the constraint to not be modifable. If the weights are non NULL, the variables are ordered according to these weights (in ascending order).

Note: The constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons().

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries
weights	weights determining the variable order, or NULL if natural order should be used
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 10336 of file cons_sos1.c.

References CONSHDLR_NAME, FALSE, handleNewVariableSOS1(), NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIP_STAGE_TRANSFORMED, SCIPallocBlockMemory, SCIPconshdlrGetData(), SCIPconsIsTransformed(), SCIPcreateCons(), SCIPcreateConsBasicSOS1(), SCIPduplicateBlockMemoryArray, SCIPerrorMessage, SCIPfindConshdlr(), SCIPgetStage(), SCIPgetTransformedVar(), SCIPmarkDoNotMultaggrVar(), SCIPsortRealPtr(), and SCIPvarIsTransformed().

Referenced by addBranchingComplementaritiesSOS1(), extensionOperatorSOS1(), performImplicationGraphAnalysis(), readSOS(), readSos(), readSOScons(), and SCIPcreateConsBasicSOS1().

◆ SCIPcreateConsBasicSOS1()

SCIP_RETCODE SCIPcreateConsBasicSOS1	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Real *	weights
	)

creates and captures an SOS1 constraint in its most basic variant, i. e., with all constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h

See also: SCIPcreateConsSOS1() for the default constraint flag configuration

Warning: Do NOT set the constraint to be modifiable manually, because this might lead to wrong results as the variable array will not be resorted

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a SOS1 constraint with all constraint flags set to their default values.

Warning: Do NOT set the constraint to be modifiable manually, because this might lead to wrong results as the variable array will not be resorted

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries
weights	weights determining the variable order, or NULL if natural order should be used

Definition at line 10457 of file cons_sos1.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIP_Real, SCIPaddVarSOS1(), SCIPcreateConsSOS1(), and TRUE.

Referenced by createKKTComplementarityBinary(), createKKTComplementarityBounds(), createKKTComplementarityLinear(), and SCIPcreateConsSOS1().

◆ SCIPaddVarSOS1()

SCIP_RETCODE SCIPaddVarSOS1	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	weight
	)

adds variable to SOS1 constraint, the position is determined by the given weight

Parameters

scip	SCIP data structure
cons	constraint
var	variable to add to the constraint
weight	weight determining position of variable

Definition at line 10473 of file cons_sos1.c.

References addVarSOS1(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPappendVarSOS1(), SCIPconsGetHdlr(), SCIPconsGetName(), SCIPconshdlrGetData(), SCIPconshdlrGetName(), SCIPdebugMsg, SCIPerrorMessage, and SCIPvarGetName().

Referenced by createKKTComplementarityBinary(), createKKTComplementarityBounds(), createKKTComplementarityLinear(), readSOS(), readSos(), readSOScons(), and SCIPcreateConsBasicSOS1().

◆ SCIPappendVarSOS1()

SCIP_RETCODE SCIPappendVarSOS1	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var
	)

appends variable to SOS1 constraint

Parameters

scip	SCIP data structure
cons	constraint
var	variable to add to the constraint

Definition at line 10507 of file cons_sos1.c.

Referenced by SCIPaddVarSOS1().

◆ SCIPgetNVarsSOS1()

int SCIPgetNVarsSOS1	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets number of variables in SOS1 constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 10540 of file cons_sos1.c.

Referenced by SCIPwriteGms(), SCIPwriteLp(), and SCIPwriteMps().

◆ SCIPgetVarsSOS1()

SCIP_VAR** SCIPgetVarsSOS1	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of variables in SOS1 constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 10565 of file cons_sos1.c.

Referenced by SCIPwriteGms(), SCIPwriteLp(), and SCIPwriteMps().

◆ SCIPgetWeightsSOS1()

SCIP_Real* SCIPgetWeightsSOS1	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of weights in SOS1 constraint (or NULL if not existent)

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 10590 of file cons_sos1.c.

Referenced by SCIPgetConsVals(), SCIPwriteLp(), and SCIPwriteMps().

◆ SCIPgetConflictgraphSOS1()

SCIP_DIGRAPH* SCIPgetConflictgraphSOS1 ( SCIP_CONSHDLR * conshdlr )

gets conflict graph of SOS1 constraints (or NULL if not existent)

Note: The conflict graph is globally valid; local changes are not taken into account.

Parameters

conshdlr SOS1 constraint handler

Definition at line 10618 of file cons_sos1.c.

Referenced by getDiveBdChgsSOS1conflictgraph(), makeSOS1conflictgraphFeasible(), SCIP_DECL_SEPAEXECLP(), and sepaBoundInequalitiesFromGraph().

◆ SCIPgetNSOS1Vars()

int SCIPgetNSOS1Vars ( SCIP_CONSHDLR * conshdlr )

gets number of problem variables that are part of the SOS1 conflict graph

Parameters

conshdlr SOS1 constraint handler

Definition at line 10640 of file cons_sos1.c.

Referenced by getDiveBdChgsSOS1conflictgraph(), makeSOS1conflictgraphFeasible(), SCIP_DECL_SEPAEXECLP(), SCIPperformGenericDivingAlgorithm(), and sepaBoundInequalitiesFromGraph().

◆ SCIPvarIsSOS1()

SCIP_Bool SCIPvarIsSOS1	(	SCIP_CONSHDLR *	conshdlr,
		SCIP_VAR *	var
	)

returns whether variable is part of the SOS1 conflict graph

Parameters

conshdlr	SOS1 constraint handler
var	variable

Definition at line 10662 of file cons_sos1.c.

◆ SCIPvarGetNodeSOS1()

int SCIPvarGetNodeSOS1	(	SCIP_CONSHDLR *	conshdlr,
		SCIP_VAR *	var
	)

returns node of variable in the conflict graph or -1 if variable is not part of the SOS1 conflict graph

returns SOS1 index of variable or -1 if variable is not part of the SOS1 conflict graph

Parameters

conshdlr	SOS1 constraint handler
var	variable

Definition at line 10686 of file cons_sos1.c.

Referenced by markNeighborsMWISHeuristic().

◆ SCIPnodeGetVarSOS1()

SCIP_VAR* SCIPnodeGetVarSOS1	(	SCIP_DIGRAPH *	conflictgraph,
		int	node
	)

returns variable that belongs to a given node from the conflict graph

Parameters

conflictgraph	conflict graph
node	node from the conflict graph

Definition at line 10717 of file cons_sos1.c.

Referenced by addBranchingComplementaritiesSOS1(), enforceConflictgraph(), extensionOperatorSOS1(), getBranchingDecisionStrongbranchSOS1(), getBranchingPrioritiesSOS1(), getBranchingVerticesSOS1(), getDiveBdChgsSOS1conflictgraph(), getVectorOfWeights(), initImplGraphSOS1(), initTCliquegraph(), isViolatedSOS1(), makeSOS1conflictgraphFeasible(), markNeighborsMWISHeuristic(), nodeGetSolvalBinaryBigMSOS1(), performImplicationGraphAnalysis(), performStrongbranchSOS1(), presolRoundVarsSOS1(), propVariableNonzero(), SCIP_DECL_SEPAEXECLP(), tightenVarsBoundsSOS1(), and updateWeightsTCliquegraph().

◆ SCIPmakeSOS1sFeasible()

SCIP_RETCODE SCIPmakeSOS1sFeasible	(	SCIP *	scip,
		SCIP_CONSHDLR *	conshdlr,
		SCIP_SOL *	sol,
		SCIP_Bool *	changed,
		SCIP_Bool *	success
	)

based on solution values of the variables, fixes variables to zero to turn all SOS1 constraints feasible

Parameters

scip	SCIP pointer
conshdlr	SOS1 constraint handler
sol	solution
changed	pointer to store whether the solution has been changed
success	pointer to store whether SOS1 constraints have been turned feasible and solution was good enough

Definition at line 10742 of file cons_sos1.c.

References CONSHDLR_NAME, FALSE, makeSOS1conflictgraphFeasible(), makeSOS1constraintsFeasible(), NULL, SCIP_Bool, SCIP_CALL, SCIP_OBJSENSE_MAXIMIZE, SCIP_OKAY, SCIP_PARAMETERWRONGVAL, SCIP_Real, SCIPconshdlrGetData(), SCIPconshdlrGetName(), SCIPconshdlrGetNConss(), SCIPerrorMessage, SCIPgetObjsense(), SCIPgetSolOrigObj(), SCIPgetUpperbound(), SCIPisLT(), and TRUE.

Referenced by SCIPperformGenericDivingAlgorithm().

◆ SCIPcreateConsSOS2()

SCIP_RETCODE SCIPcreateConsSOS2	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Real *	weights,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures an SOS2 constraint

We set the constraint to not be modifable. If the weights are non NULL, the variables are ordered according to these weights (in ascending order).

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a SOS2 constraint

We set the constraint to not be modifable. If the weights are non NULL, the variables are ordered according to these weights (in ascending order).

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries
weights	weights determining the variable order, or NULL if natural order should be used
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 2327 of file cons_sos2.c.

References CONSHDLR_NAME, FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPallocBlockMemory, SCIPcreateCons(), SCIPcreateConsBasicSOS2(), SCIPduplicateBlockMemoryArray, SCIPerrorMessage, SCIPfindConshdlr(), and SCIPsortRealPtr().

Referenced by readSOS(), readSos(), readSOScons(), SCIP_DECL_CONSCOPY(), SCIP_DECL_CONSPARSE(), SCIPcreateConsBasicSOS2(), and SCIPincludeConshdlrSOS2().

◆ SCIPcreateConsBasicSOS2()

SCIP_RETCODE SCIPcreateConsBasicSOS2	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Real *	weights
	)

creates and captures a SOS2 constraint with all constraint flags set to their default values.

Warning: Do NOT set the constraint to be modifiable manually, because this might lead to wrong results as the variable array will not be resorted

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
nvars	number of variables in the constraint
vars	array with variables of constraint entries
weights	weights determining the variable order, or NULL if natural order should be used

Definition at line 2410 of file cons_sos2.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIPaddVarSOS2(), SCIPcreateConsSOS2(), and TRUE.

Referenced by SCIPcreateConsSOS2().

◆ SCIPaddVarSOS2()

SCIP_RETCODE SCIPaddVarSOS2	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var,
		SCIP_Real	weight
	)

adds variable to SOS2 constraint, the position is determined by the given weight

Parameters

scip	SCIP data structure
cons	constraint
var	variable to add to the constraint
weight	weight determining position of variable

Definition at line 2426 of file cons_sos2.c.

References addVarSOS2(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPappendVarSOS2(), SCIPconsGetHdlr(), SCIPconsGetName(), SCIPconshdlrGetName(), SCIPdebugMsg, SCIPerrorMessage, and SCIPvarGetName().

Referenced by readSOS(), readSos(), readSOScons(), SCIP_DECL_CONSPARSE(), and SCIPcreateConsBasicSOS2().

◆ SCIPappendVarSOS2()

SCIP_RETCODE SCIPappendVarSOS2	(	SCIP *	scip,
		SCIP_CONS *	cons,
		SCIP_VAR *	var
	)

appends variable to SOS2 constraint

Parameters

scip	SCIP data structure
cons	constraint
var	variable to add to the constraint

Definition at line 2452 of file cons_sos2.c.

References appendVarSOS2(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_INVALIDDATA, SCIP_OKAY, SCIPconsGetHdlr(), SCIPconsGetName(), SCIPconshdlrGetName(), SCIPdebugMsg, SCIPerrorMessage, SCIPgetNVarsSOS2(), and SCIPvarGetName().

Referenced by SCIPaddVarSOS2().

◆ SCIPgetNVarsSOS2()

int SCIPgetNVarsSOS2	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets number of variables in SOS2 constraint

Parameters

scip	SCIP data structure
cons	constraint

Definition at line 2477 of file cons_sos2.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVarsSOS2().

Referenced by SCIPappendVarSOS2(), SCIPwriteGms(), SCIPwriteLp(), and SCIPwriteMps().

◆ SCIPgetVarsSOS2()

SCIP_VAR** SCIPgetVarsSOS2	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of variables in SOS2 constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 2502 of file cons_sos2.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetWeightsSOS2().

Referenced by SCIPgetNVarsSOS2(), SCIPwriteGms(), SCIPwriteLp(), and SCIPwriteMps().

◆ SCIPgetWeightsSOS2()

SCIP_Real* SCIPgetWeightsSOS2	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of weights in SOS2 constraint (or NULL if not existent)

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 2527 of file cons_sos2.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPgetConsVals(), SCIPgetVarsSOS2(), SCIPwriteLp(), and SCIPwriteMps().

◆ SCIPcreateConsSuperindicator()

SCIP_RETCODE SCIPcreateConsSuperindicator	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	binvar,
		SCIP_CONS *	slackcons,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a superindicator constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
binvar	pointer to the indicator constraint
slackcons	constraint corresponding to the handled constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 1991 of file cons_superindicator.c.

References consdataCreateSuperindicator(), CONSHDLR_NAME, FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPconsGetHdlr(), SCIPconsGetName(), SCIPconshdlrGetData(), SCIPconshdlrGetName(), SCIPcreateCons(), SCIPcreateConsBasicSuperindicator(), SCIPerrorMessage, SCIPfindConshdlr(), and SCIPwarningMessage().

Referenced by SCIPcreateConsBasicSuperindicator(), SCIPincludeConshdlrSuperindicator(), and SCIPtransformMinUC().

◆ SCIPcreateConsBasicSuperindicator()

SCIP_RETCODE SCIPcreateConsBasicSuperindicator	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	binvar,
		SCIP_CONS *	slackcons
	)

creates and captures a superindicator constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsSuperindicator(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsSuperindicator() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
binvar	pointer to the indicator constraint
slackcons	constraint corresponding to the handled constraint

Definition at line 2102 of file cons_superindicator.c.

References FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPcreateConsSuperindicator(), SCIPgetBinaryVarSuperindicator(), and TRUE.

Referenced by SCIPcreateConsSuperindicator().

◆ SCIPgetBinaryVarSuperindicator()

SCIP_VAR* SCIPgetBinaryVarSuperindicator ( SCIP_CONS * cons )

gets binary variable corresponding to the superindicator constraint

gets binary variable corresponding to the general indicator constraint

Parameters

cons	superindicator constraint

Definition at line 2124 of file cons_superindicator.c.

References CONSHDLR_NAME, NULL, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPgetSlackConsSuperindicator().

Referenced by SCIPcreateConsBasicSuperindicator().

◆ SCIPgetSlackConsSuperindicator()

SCIP_CONS* SCIPgetSlackConsSuperindicator ( SCIP_CONS * cons )

gets the slack constraint corresponding to the superindicator constraint

gets the slack constraint corresponding to the general indicator constraint

Parameters

cons	superindicator constraint

Definition at line 2136 of file cons_superindicator.c.

References CONSHDLR_NAME, NULL, SCIP_Bool, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPtransformMinUC().

Referenced by SCIPgetBinaryVarSuperindicator().

◆ SCIPtransformMinUC()

SCIP_RETCODE SCIPtransformMinUC	(	SCIP *	scip,
		SCIP_Bool *	success
	)

transforms the current problem into a MinUC problem (minimizing the number of unsatisfied constraints), a CIP generalization of the MinULR (min. unsatisfied linear relations) problem

Parameters

scip	SCIP data structure
success	pointer to store whether all constraints could be transformed

Definition at line 2155 of file cons_superindicator.c.

References FALSE, NULL, SCIP_Bool, SCIP_CALL, SCIP_DECL_DIALOGEXEC(), SCIP_INVALIDCALL, SCIP_MAXSTRLEN, SCIP_OBJSENSE_MINIMIZE, SCIP_OKAY, SCIP_STAGE_PROBLEM, SCIP_VARTYPE_BINARY, SCIPaddCons(), SCIPaddVar(), SCIPchgVarBranchPriority(), SCIPchgVarObj(), SCIPconsGetHdlr(), SCIPconsGetName(), SCIPconshdlrGetName(), SCIPconsIsChecked(), SCIPconsIsDynamic(), SCIPconsIsEnforced(), SCIPconsIsInitial(), SCIPconsIsLocal(), SCIPconsIsPropagated(), SCIPconsIsRemovable(), SCIPconsIsSeparated(), SCIPconsIsStickingAtNode(), SCIPcreateConsSuperindicator(), SCIPcreateVar(), SCIPdebugMsg, SCIPdelCons(), SCIPduplicateBufferArray, SCIPerrorMessage, SCIPfreeBufferArray, SCIPgetConss(), SCIPgetNConss(), SCIPgetNegatedVar(), SCIPgetStage(), SCIPgetVarsData(), SCIPreleaseCons(), SCIPreleaseVar(), SCIPsetObjsense(), SCIPsnprintf(), SCIPvarGetBranchPriority(), and TRUE.

Referenced by SCIPgetSlackConsSuperindicator().

◆ SCIP_DECL_DIALOGEXEC() [4/4]

SCIP_DECL_DIALOGEXEC ( SCIPdialogExecChangeMinUC )

dialog execution method for the SCIPtransformMinUC() command

dialog execution method for the SCIPtransformMinUC() method

Definition at line 2291 of file cons_superindicator.c.

Referenced by SCIPtransformMinUC().

◆ SCIPcreateSymbreakCons()

SCIP_RETCODE SCIPcreateSymbreakCons	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int *	perm,
		SCIP_VAR **	vars,
		int	nvars,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates a symmetry breaking constraint

Depending on the given permutation, either an orbisack or symresack constraint is created.

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
perm	permutation
vars	variables
nvars	number of variables in vars array
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 1307 of file cons_symresack.c.

References FALSE, NULL, orbisackUpgrade(), SCIP_Bool, SCIP_CALL, SCIP_DECL_CONSDELETE(), SCIP_OKAY, and SCIPcreateConsSymresack().

Referenced by addSymresackConss(), and orbisackUpgrade().

◆ SCIPcreateConsSymresack()

SCIP_RETCODE SCIPcreateConsSymresack	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int *	perm,
		SCIP_VAR **	vars,
		int	nvars,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a symresack constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a symresack constraint

In a presolving step, we check whether the permutation acts only on binary points. Otherwise, we eliminate the non-binary variables from the permutation.

Note: The constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons().

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
perm	permutation
vars	variables
nvars	number of variables in vars array
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 2354 of file cons_symresack.c.

References consdataCreate(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPcreateCons(), SCIPcreateConsBasicSymresack(), SCIPerrorMessage, and SCIPfindConshdlr().

Referenced by SCIPcreateConsBasicSymresack(), SCIPcreateSymbreakCons(), and SCIPincludeConshdlrSymresack().

◆ SCIPcreateConsBasicSymresack()

SCIP_RETCODE SCIPcreateConsBasicSymresack	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		int *	perm,
		SCIP_VAR **	vars,
		int	nvars
	)

creates and captures a symresack constraint in its most basic variant, i.e., with all constraint flags set to their default values, which can be set afterwards using SCIPsetConsFLAGNAME() in scip.h

See also: SCIPcreateConsSymresack() for the default constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a symresack constraint in its most basic variant, i.e., with all constraint flags set to their default values

In a presolving step, we remove all fixed points and cycles that act on non-binary variables of the permutation

Note: The constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons().

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
perm	permutation
vars	variables
nvars	number of variables in vars array

Definition at line 2418 of file cons_symresack.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIPcreateConsSymresack(), and TRUE.

Referenced by SCIPcreateConsSymresack().

◆ SCIPcreateConsVarbound()

SCIP_RETCODE SCIPcreateConsVarbound	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	var,
		SCIP_VAR *	vbdvar,
		SCIP_Real	vbdcoef,
		SCIP_Real	lhs,
		SCIP_Real	rhs,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures a variable bound constraint: lhs <= x + c*y <= rhs

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
var	variable x that has variable bound
vbdvar	binary, integer or implicit integer bounding variable y
vbdcoef	coefficient c of bounding variable y
lhs	left hand side of variable bound inequality
rhs	right hand side of variable bound inequality
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 4801 of file cons_varbound.c.

References catchEvents(), consdataCreate(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPconshdlrGetData(), SCIPcreateCons(), SCIPcreateConsBasicVarbound(), SCIPerrorMessage, SCIPfindConshdlr(), and SCIPisTransformed().

Referenced by addVarbound(), createPrecedenceCons(), createVarUbs(), presolveTryAddLinearReform(), SCIP_DECL_CONSINITLP(), SCIP_DECL_CONSPARSE(), SCIP_DECL_CONSPRESOL(), SCIP_DECL_LINCONSUPGD(), SCIPcreateConsBasicVarbound(), SCIPcreateSchedulingProblem(), and SCIPincludeConshdlrVarbound().

◆ SCIPcreateConsBasicVarbound()

SCIP_RETCODE SCIPcreateConsBasicVarbound	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_VAR *	var,
		SCIP_VAR *	vbdvar,
		SCIP_Real	vbdcoef,
		SCIP_Real	lhs,
		SCIP_Real	rhs
	)

creates and captures a varbound constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsVarbound(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsVarbound() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a variable bound constraint: lhs <= x + c*y <= rhs with all constraint flags set to their default values

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
var	variable x that has variable bound
vbdvar	binary, integer or implicit integer bounding variable y
vbdcoef	coefficient c of bounding variable y
lhs	left hand side of variable bound inequality
rhs	right hand side of variable bound inequality

Definition at line 4871 of file cons_varbound.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIP_Real, SCIPcreateConsVarbound(), SCIPgetLhsVarbound(), and TRUE.

Referenced by addBranchingDecisionConss(), applyRepair(), createVarboundCons(), and SCIPcreateConsVarbound().

◆ SCIPgetLhsVarbound()

SCIP_Real SCIPgetLhsVarbound	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets left hand side of variable bound constraint lhs <= x + c*y <= rhs

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 4889 of file cons_varbound.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetRhsVarbound().

Referenced by addVarboundConstraints(), checkVarbound(), computeSymmetryGroup(), createAltLP(), presolveAddKKTVarboundConss(), printRangeSection(), SCIP_DECL_CONSCOPY(), SCIPconsGetLhs(), SCIPcreateConsBasicVarbound(), SCIPmatrixCreate(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePip(), writeFzn(), and writeOpbConstraints().

◆ SCIPgetRhsVarbound()

SCIP_Real SCIPgetRhsVarbound	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets right hand side of variable bound constraint lhs <= x + c*y <= rhs

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 4910 of file cons_varbound.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVarVarbound().

Referenced by addVarboundConstraints(), checkVarbound(), computeSymmetryGroup(), createAltLP(), presolveAddKKTVarboundConss(), printRangeSection(), SCIP_DECL_CONSCOPY(), SCIPconsGetRhs(), SCIPgetLhsVarbound(), SCIPmatrixCreate(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePip(), writeFzn(), and writeOpbConstraints().

◆ SCIPgetVarVarbound()

SCIP_VAR* SCIPgetVarVarbound	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets bounded variable x of variable bound constraint lhs <= x + c*y <= rhs

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 4931 of file cons_varbound.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVbdvarVarbound().

Referenced by addVarboundConstraints(), checkVarbound(), computeSymmetryGroup(), createAltLP(), presolveAddKKTVarboundConss(), SCIP_DECL_CONSCOPY(), SCIPgetRhsVarbound(), SCIPmatrixCreate(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), writeFzn(), and writeOpbConstraints().

◆ SCIPgetVbdvarVarbound()

SCIP_VAR* SCIPgetVbdvarVarbound	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets bounding variable y of variable bound constraint lhs <= x + c*y <= rhs

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 4952 of file cons_varbound.c.

References CONSHDLR_NAME, NULL, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVbdcoefVarbound().

Referenced by addVarboundConstraints(), checkVarbound(), computeSymmetryGroup(), createAltLP(), presolveAddKKTVarboundConss(), SCIP_DECL_CONSCOPY(), SCIPgetVarVarbound(), SCIPmatrixCreate(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), writeFzn(), and writeOpbConstraints().

◆ SCIPgetVbdcoefVarbound()

SCIP_Real SCIPgetVbdcoefVarbound	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets bound coefficient c of variable bound constraint lhs <= x + c*y <= rhs

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 4973 of file cons_varbound.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetDualsolVarbound().

Referenced by addVarboundConstraints(), checkVarbound(), computeSymmetryGroup(), createAltLP(), presolveAddKKTVarboundConss(), SCIP_DECL_CONSCOPY(), SCIPgetConsVals(), SCIPgetVbdvarVarbound(), SCIPmatrixCreate(), SCIPwriteCcg(), SCIPwriteGms(), SCIPwriteLp(), SCIPwriteMps(), SCIPwritePbm(), SCIPwritePip(), SCIPwritePpm(), writeFzn(), and writeOpbConstraints().

◆ SCIPgetDualsolVarbound()

SCIP_Real SCIPgetDualsolVarbound	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the dual solution of the variable bound constraint in the current LP

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 4994 of file cons_varbound.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIP_Real, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPgetDualfarkasVarbound(), and SCIProwGetDualsol().

Referenced by SCIPconsGetDualsol(), and SCIPgetVbdcoefVarbound().

◆ SCIPgetDualfarkasVarbound()

SCIP_Real SCIPgetDualfarkasVarbound	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the dual Farkas value of the variable bound constraint in the current infeasible LP

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5018 of file cons_varbound.c.

References CONSHDLR_NAME, NULL, SCIP_INVALID, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, SCIPgetRowVarbound(), and SCIProwGetDualfarkas().

Referenced by SCIPconsGetDualfarkas(), and SCIPgetDualsolVarbound().

◆ SCIPgetRowVarbound()

SCIP_ROW* SCIPgetRowVarbound	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

returns the linear relaxation of the given variable bound constraint; may return NULL if no LP row was yet created; the user must not modify the row!

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5044 of file cons_varbound.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by SCIPconsGetRow(), and SCIPgetDualfarkasVarbound().

◆ SCIPcreateConsXor()

SCIP_RETCODE SCIPcreateConsXor	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_Bool	rhs,
		int	nvars,
		SCIP_VAR **	vars,
		SCIP_Bool	initial,
		SCIP_Bool	separate,
		SCIP_Bool	enforce,
		SCIP_Bool	check,
		SCIP_Bool	propagate,
		SCIP_Bool	local,
		SCIP_Bool	modifiable,
		SCIP_Bool	dynamic,
		SCIP_Bool	removable,
		SCIP_Bool	stickingatnode
	)

creates and captures an xor constraint

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a xor constraint x_0 xor ... xor x_{k-1} = rhs

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
rhs	right hand side of the constraint
nvars	number of operator variables in the constraint
vars	array with operator variables of constraint
initial	should the LP relaxation of constraint be in the initial LP? Usually set to TRUE. Set to FALSE for 'lazy constraints'.
separate	should the constraint be separated during LP processing? Usually set to TRUE.
enforce	should the constraint be enforced during node processing? TRUE for model constraints, FALSE for additional, redundant constraints.
check	should the constraint be checked for feasibility? TRUE for model constraints, FALSE for additional, redundant constraints.
propagate	should the constraint be propagated during node processing? Usually set to TRUE.
local	is constraint only valid locally? Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints.
modifiable	is constraint modifiable (subject to column generation)? Usually set to FALSE. In column generation applications, set to TRUE if pricing adds coefficients to this constraint.
dynamic	is constraint subject to aging? Usually set to FALSE. Set to TRUE for own cuts which are separated as constraints.
removable	should the relaxation be removed from the LP due to aging or cleanup? Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'.
stickingatnode	should the constraint always be kept at the node where it was added, even if it may be moved to a more global node? Usually set to FALSE. Set to TRUE to for constraints that represent node data.

Definition at line 5796 of file cons_xor.c.

References consdataCreate(), CONSHDLR_NAME, NULL, SCIP_CALL, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIPcreateCons(), SCIPcreateConsBasicXor(), SCIPerrorMessage, and SCIPfindConshdlr().

Referenced by CREATE_CONSTRAINT(), SCIP_DECL_CONSPARSE(), SCIPcreateConsBasicXor(), SCIPincludeConshdlrXor(), and tryUpgradingXor().

◆ SCIPcreateConsBasicXor()

SCIP_RETCODE SCIPcreateConsBasicXor	(	SCIP *	scip,
		SCIP_CONS **	cons,
		const char *	name,
		SCIP_Bool	rhs,
		int	nvars,
		SCIP_VAR **	vars
	)

creates and captures an xor constraint in its most basic version, i. e., all constraint flags are set to their basic value as explained for the method SCIPcreateConsXor(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h

See also: SCIPcreateConsXor() for information about the basic constraint flag configuration

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

creates and captures a xor constraint x_0 xor ... xor x_{k-1} = rhs with all constraint flags set to their default values

Note: the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()

Parameters

scip	SCIP data structure
cons	pointer to hold the created constraint
name	name of constraint
rhs	right hand side of the constraint
nvars	number of operator variables in the constraint
vars	array with operator variables of constraint

Definition at line 5854 of file cons_xor.c.

References FALSE, SCIP_CALL, SCIP_OKAY, SCIPcreateConsXor(), SCIPgetNVarsXor(), and TRUE.

Referenced by createMIP(), and SCIPcreateConsXor().

◆ SCIPgetNVarsXor()

int SCIPgetNVarsXor	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets number of variables in xor constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5870 of file cons_xor.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetVarsXor().

Referenced by computeSymmetryGroup(), and SCIPcreateConsBasicXor().

◆ SCIPgetVarsXor()

SCIP_VAR** SCIPgetVarsXor	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets array of variables in xor constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5891 of file cons_xor.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetIntVarXor().

Referenced by computeSymmetryGroup(), and SCIPgetNVarsXor().

◆ SCIPgetIntVarXor()

SCIP_VAR* SCIPgetIntVarXor	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets integer variable in xor constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5912 of file cons_xor.c.

References CONSHDLR_NAME, NULL, SCIP_Bool, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), SCIPerrorMessage, and SCIPgetRhsXor().

Referenced by computeSymmetryGroup(), and SCIPgetVarsXor().

◆ SCIPgetRhsXor()

SCIP_Bool SCIPgetRhsXor	(	SCIP *	scip,
		SCIP_CONS *	cons
	)

gets the right hand side of the xor constraint

Parameters

scip	SCIP data structure
cons	constraint data

Definition at line 5933 of file cons_xor.c.

References CONSHDLR_NAME, NULL, SCIPABORT, SCIPconsGetData(), SCIPconsGetHdlr(), SCIPconshdlrGetName(), and SCIPerrorMessage.

Referenced by computeSymmetryGroup(), SCIP_DECL_CONSCOPY(), and SCIPgetIntVarXor().

SCIP

Detailed Description

Data Structures

Modules

Files

Absolute Power Constraints

AND Constraints

Benders Constraints

Bivariate Constraints

Bound Disjunction Constraints

Cardinality Constraints

Conjunction Constraints

Constraint Handler for counting solutions

Cumulative Constraints

Disjunction Constraints

Indicator Constraints

Knapsack Constraints

Linear Constraints

Linking Constraints

Logicor Constraints

Nonlinear Constraints

OR Constraints

Orbisack Constraints

Orbitope Constraints

Pseudoboolean Constraints

Quadratic Constraints

Set Packing/Partitioning/Covering Constraints

Second Order Cone Constraints

Specially Ordered Set (SOS) Type 1 Constraints

Specially Ordered Set (SOS) Type 2 Constraints

Superindicator Constraints

Symresack Constraints

Variable Bound Constraints

XOR Constraints

Macro Definition Documentation

◆ SCIP_DECL_SOLVECUMULATIVE

◆ SCIP_DECL_LINCONSUPGD

◆ SCIP_DECL_QUADCONSUPGD

Typedef Documentation

◆ SCIP_LINCONSUPGRADE

◆ SCIP_ORBITOPETYPE

◆ SCIP_LINEARCONSTYPE

◆ SCIP_QUADVAREVENTDATA

◆ SCIP_QUADVARTERM

◆ SCIP_BILINTERM

◆ SCIP_ROWPREP

◆ SCIP_SETPPCTYPE

Enumeration Type Documentation

◆ SCIP_BIVAR_CONVEXITY

◆ SCIP_OrbitopeType

◆ SCIP_LinearConsType

◆ SCIP_SetppcType

Function Documentation

◆ SCIPcreateConsAbspower()

◆ SCIPcreateConsBasicAbspower()

◆ SCIPgetNlRowAbspower()

◆ SCIPgetNonlinearVarAbspower()

◆ SCIPgetLinearVarAbspower()

◆ SCIPgetExponentAbspower()

◆ SCIPgetOffsetAbspower()

◆ SCIPgetCoefLinearAbspower()

◆ SCIPgetLhsAbspower()

◆ SCIPgetRhsAbspower()

◆ SCIPgetViolationAbspower()

◆ SCIPcreateConsAnd()

◆ SCIPcreateConsBasicAnd()

◆ SCIPgetNVarsAnd()

◆ SCIPgetVarsAnd()

◆ SCIPgetResultantAnd()

◆ SCIPisAndConsSorted()

◆ SCIPsortAndCons()

◆ SCIPchgAndConsCheckFlagWhenUpgr()

◆ SCIPchgAndConsRemovableFlagWhenUpgr()

◆ SCIPconsBendersEnforceSolution()

◆ SCIPcreateConsBivariate()

◆ SCIPcreateConsBasicBivariate()

◆ SCIPgetLinearVarBivariate()

◆ SCIPgetLinearCoefBivariate()

◆ SCIPgetExprtreeBivariate()

◆ SCIPgetLhsBivariate()