cons_bivariate.c
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18 * @brief constraint handler for bivariate nonlinear constraints \f$\textrm{lhs} \leq f(x,y) + c z \leq \textrm{rhs}\f$
24 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
71 #define CONSHDLR_DESC "constraint handler for constraints of the form lhs <= f(x,y) + c*z <= rhs where f(x,y) is a bivariate function"
73 #define CONSHDLR_ENFOPRIORITY -55 /**< priority of the constraint handler for constraint enforcing */
74 #define CONSHDLR_CHECKPRIORITY -3600000 /**< priority of the constraint handler for checking feasibility */
75 #define CONSHDLR_SEPAFREQ 1 /**< frequency for separating cuts; zero means to separate only in the root node */
76 #define CONSHDLR_PROPFREQ 1 /**< frequency for propagating domains; zero means only preprocessing propagation */
77 #define CONSHDLR_EAGERFREQ 100 /**< frequency for using all instead of only the useful constraints in separation,
79 #define CONSHDLR_MAXPREROUNDS -1 /**< maximal number of presolving rounds the constraint handler participates in (-1: no limit) */
80 #define CONSHDLR_DELAYSEPA FALSE /**< should separation method be delayed, if other separators found cuts? */
81 #define CONSHDLR_DELAYPROP FALSE /**< should propagation method be delayed, if other propagators found reductions? */
82 #define CONSHDLR_NEEDSCONS TRUE /**< should the constraint handler be skipped, if no constraints are available? */
89 #define INITLPMAXVARVAL 1000.0 /**< maximal absolute value of variable for still generating a linearization cut at that point in initlp */
91 #define QUADCONSUPGD_PRIORITY 5000 /**< priority of the constraint handler for upgrading of quadratic constraints */
92 #define NONLINCONSUPGD_PRIORITY 10000 /**< priority of the constraint handler for upgrading of nonlinear constraints */
94 /* activate the following define to get output on number of bivariate constraints for each convexity-type during INITSOL */
129 unsigned int mayincreasez:1; /**< whether z can be increased without harming other constraints */
130 unsigned int maydecreasez:1; /**< whether z can be decreased without harming other constraints */
133 SCIP_EXPRGRAPHNODE* exprgraphnode; /**< node in expression graph corresponding to bivariate function */
135 SEPADATA_CONVEXCONCAVE sepaconvexconcave; /**< separation data for convex-concave constraints */
143 SCIP_Real cutmaxrange; /**< maximal range (maximal coef / minimal coef) of a cut in order to be added to LP */
145 int maxproprounds; /**< limit on number of propagation rounds for a single constraint within one round of SCIP propagation */
146 int ninitlprefpoints; /**< number of reference points in each direction where to compute linear support for envelope in LP initialization */
147 SCIP_Bool enfocutsremovable; /**< are cuts added during enforcement removable from the LP in the same node? */
156 SCIP_Bool isremovedfixings; /**< whether variable fixations have been removed from the expression graph */
157 SCIP_Bool ispropagated; /**< whether the bounds on the variables in the expression graph have been propagated */
160 SCIP_NODE* lastenfonode; /**< the node for which enforcement was called the last time (and some constraint was violated) */
178 {
226 /* if right hand side is finite, then a tightening in the lower bound of coef*linvar is of interest */
234 /* if left hand side is finite, then a tightening in the upper bound of coef*linvar is of interest */
241 SCIP_CALL( SCIPcatchVarEvent(scip, consdata->z, eventtype, conshdlrdata->linvareventhdlr, (SCIP_EVENTDATA*)cons, &consdata->eventfilterpos) );
278 /* if right hand side is finite, then a tightening in the lower bound of coef*linvar is of interest */
286 /* if left hand side is finite, then a tightening in the upper bound of coef*linvar is of interest */
293 SCIP_CALL( SCIPdropVarEvent(scip, consdata->z, eventtype, conshdlrdata->linvareventhdlr, (SCIP_EVENTDATA*)cons, consdata->eventfilterpos) );
303 {
323 SCIPvarGetName(SCIPeventGetVar(event)), SCIPeventGetOldbound(event), SCIPeventGetNewbound(event));
350 {
366 SCIP_CALL( SCIPcatchVarEvent(conshdlrdata->scip, (SCIP_VAR*)var, SCIP_EVENTTYPE_BOUNDCHANGED | SCIP_EVENTTYPE_VARFIXED, conshdlrdata->nonlinvareventhdlr, (SCIP_EVENTDATA*)varnode, NULL) );
367 SCIPdebugMessage("catch boundchange events on new expression graph variable <%s>\n", SCIPvarGetName(var_));
371 -infty2infty(SCIPinfinity(conshdlrdata->scip), INTERVALINFTY, -MIN(SCIPvarGetLbLocal(var_), SCIPvarGetUbLocal(var_))), /*lint !e666*/
372 +infty2infty(SCIPinfinity(conshdlrdata->scip), INTERVALINFTY, MAX(SCIPvarGetLbLocal(var_), SCIPvarGetUbLocal(var_))) /*lint !e666*/
388 {
402 SCIP_CALL( SCIPdropVarEvent(conshdlrdata->scip, var_, SCIP_EVENTTYPE_BOUNDCHANGED | SCIP_EVENTTYPE_VARFIXED, conshdlrdata->nonlinvareventhdlr, (SCIP_EVENTDATA*)varnode, -1) );
403 SCIPdebugMessage("drop boundchange events on expression graph variable <%s>\n", SCIPvarGetName(var_));
432 SCIP_CALL( SCIPlockVarCons(scip, var, cons, !SCIPisInfinity(scip, -consdata->lhs), !SCIPisInfinity(scip, consdata->rhs)) );
436 SCIP_CALL( SCIPlockVarCons(scip, var, cons, !SCIPisInfinity(scip, consdata->rhs), !SCIPisInfinity(scip, -consdata->lhs)) );
463 SCIP_CALL( SCIPunlockVarCons(scip, var, cons, !SCIPisInfinity(scip, -consdata->lhs), !SCIPisInfinity(scip, consdata->rhs)) );
467 SCIP_CALL( SCIPunlockVarCons(scip, var, cons, !SCIPisInfinity(scip, consdata->rhs), !SCIPisInfinity(scip, -consdata->lhs)) );
480 SCIP_Bool* isupgraded /**< buffer to store whether the constraint has been upgraded (and deleted) */
512 if( consdata->z != NULL && !SCIPvarIsActive(consdata->z) && SCIPvarGetStatus(consdata->z) != SCIP_VARSTATUS_MULTAGGR )
557 * in the latter case, we just do nothing, which may not be most efficient, but should still work
676 /* mark that variables in constraint should not be multiaggregated (bad for bound tightening and branching) */
745 SCIP_CALL( SCIPgetProbvarLinearSum(scip, vars, coefs, &nvars, varssize, &constant, &requsize, TRUE) );
752 SCIP_CALL( SCIPgetProbvarLinearSum(scip, vars, coefs, &nvars, varssize, &constant, &requsize, TRUE) );
765 SCIP_CALL( SCIPexprgraphReplaceVarByLinearSum(conshdlrdata->exprgraph, var, nvars, coefs, (void**)vars, constant) );
839 /* project point onto box if from LP or very close to bounds to avoid eval error when function is not defined slightly outside bounds */
844 /* @todo handle case where variables are outside of bounds as in other constraint handlers, see also #627 */
871 SCIP_CALL( SCIPexprintEval(conshdlrdata->exprinterpreter, consdata->f, xyvals, &consdata->activity) );
918 SCIP_CONS** maxviolcon /**< buffer to store constraint with largest violation, or NULL if solution is feasible */
956 /** setup vred(s;x0,y0,ylb,yub) for a given f(x,y) for computing a convex-concave underestimator
957 * vred(s;x0,y0,ylb,yub) = (yub-y0)/(yub-ylb) f((yub-ylb)/(yub-y0)x0 - (y0-ylb)/(yub-y0)*s, ylb) + (y0-ylb)/(yub-ylb) f(s,yub)
981 assert(SCIPexprGetOperator(SCIPexprtreeGetRoot(f)) != SCIP_EXPR_VARIDX); /* substitute cannot substitute the root node, but f should not be a single variable anyway */
983 /* setup vred(s;x0,y0,ylb,yub) for computing a convex-concave underestimator in the case where y is not at one of its bounds
984 * vred(s;x0,y0,ylb,yub) = (yub-y0)/(yub-ylb) f((yub-ylb)/(yub-y0)x0 - (y0-ylb)/(yub-y0)*s, ylb) + (y0-ylb)/(yub-ylb) f(s,yub)
998 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &e5, SCIP_EXPR_DIV, e3, e4) ); /* x0(yub-ylb)/(yub-y0) */
1012 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &e6, SCIP_EXPR_DIV, e3, e4) ); /* s(y0-ylb)/(yub-y0) */
1041 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &e5, SCIP_EXPR_DIV, e3, e4) ); /* (yub-y0)/(yub-ylb) */
1046 SCIP_CALL( SCIPexprCreateLinear(SCIPblkmem(scip), &e6, 1, &e1, &minusone, 1.0) ); /* 1 - (yub-y0)/(yub-ylb) */
1106 /* setup f(x,yfixed) for computing a convex-concave underestimator in the case where y is at one of its bounds */
1107 SCIP_CALL( SCIPexprtreeCopy(SCIPblkmem(scip), &consdata->sepaconvexconcave.f_yfixed, consdata->f) );
1128 /* setup vred(s;x0,y0,ylb,yub) for computing a convex-concave underestimator in the case where y is not at one of its bounds
1129 * vred(s;x0,y0,ylb,yub) = (yub-y0)/(yub-ylb) f((yub-ylb)/(yub-y0)x0 - (y0-ylb)/(yub-y0)*s, ylb) + (y0-ylb)/(yub-ylb) f(s,yub)
1164 SCIP_CALL( SCIPexprtreeCreate(SCIPblkmem(scip), &consdata->sepaconvexconcave.f_neg_swapped, minusf, 2, 0, NULL) );
1172 /* setup -f(y, xfixed) for computing a convex-concave overestimator in the case where x is at on of it's bounds */
1173 SCIP_CALL( SCIPexprtreeCopy(SCIPblkmem(scip), &consdata->sepaconvexconcave.f_neg_swapped_yfixed, consdata->sepaconvexconcave.f_neg_swapped) );
1182 SCIP_CALL( SCIPexprtreeSubstituteVars(consdata->sepaconvexconcave.f_neg_swapped_yfixed, subst) );
1192 SCIP_CALL( SCIPexprintCompile(exprinterpreter, consdata->sepaconvexconcave.f_neg_swapped_yfixed) );
1194 /* setup vred(s;y0,x0,xlb,xub) for computing a convex-concave underestimator in the case where x is not at one of its bounds */
1195 SCIP_CALL( initSepaDataCreateVred(scip, &consdata->sepaconvexconcave.vred_neg_swapped, consdata->sepaconvexconcave.f_neg_swapped) );
1196 SCIP_CALL( SCIPexprintCompile(exprinterpreter, consdata->sepaconvexconcave.vred_neg_swapped) );
1286 /** solves an equation f'(s) = constant for a univariate convex or concave function f with respect to bounds on s
1287 * if there is no s between the bounds such that f'(s) = constant, then it returns the closest bound (and still claims success)
1359 /* SCIPdebugMsg(scip, "s = %.15g [%g,%g] f(s) = %g grad = %g (perturbed by %g)\n", s, lb, ub, fval, grad, iter <= 65 ? 0.1 / (1<<iter) : 1e-20); */
1382 /* if f cannot be two times differentiated at s, take the Hessian from another point close by */
1395 * (multiply instead of divide by hess for the case that hess is zero and since only the sign matters
1418 /* if grad is targetvalue (w.r.t. feastol) and step length would be almost 0, then we are also done */
1447 /** generates a cut for f(x,y) + c*z <= rhs with f(x,y) being convex or 1-convex with x or y fixed or convex-concave with y fixed
1456 SCIP_Bool newxy, /**< whether the last evaluation of f(x,y) with the expression interpreter was at (x0, y0) */
1487 (consdata->convextype == SCIP_BIVAR_1CONVEX_INDEFINITE && (SCIPisEQ(scip, SCIPvarGetLbLocal(x), SCIPvarGetUbLocal(x)) || SCIPisEQ(scip, SCIPvarGetLbLocal(y), SCIPvarGetUbLocal(y)))) ||
1488 (consdata->convextype == SCIP_BIVAR_CONVEX_CONCAVE && SCIPisEQ(scip, SCIPvarGetLbLocal(y), SCIPvarGetUbLocal(y))) );
1511 (void) SCIPsnprintf(rowname, SCIP_MAXSTRLEN, "%s_linearization_%d", SCIPconsGetName(cons), SCIPgetNLPs(scip));
1513 SCIP_CALL( SCIPcreateEmptyRowCons(scip, row, cons, rowname, -SCIPinfinity(scip), rhs, FALSE, FALSE /* modifiable */, TRUE /* removable */) );
1523 /** given a convex (concave, resp.) bivariate function, computes an over- (under-, resp.) estimating hyperplane
1531 SCIP_Bool doover, /**< whether to compute an overestimator (TRUE) or an underestimator (FALSE) */
1536 SCIP_Bool* success /**< pointer to indicate whether coefficients where successfully computed */
1587 if( SCIPisInfinity(scip, -xlb) || SCIPisInfinity(scip, xub) || SCIPisInfinity(scip, -ylb) || SCIPisInfinity(scip, yub) )
1589 SCIPdebugMsg(scip, "skip estimating hyperplane since <%s> or <%s> is unbounded\n", SCIPvarGetName(x), SCIPvarGetName(y));
1595 SCIPdebugMsg(scip, "skip estimating hyperplane since both <%s> and <%s> are fixed\n", SCIPvarGetName(x), SCIPvarGetName(y));
1623 if( !SCIPisFinite(p1val) || SCIPisInfinity(scip, REALABS(p1val)) || !SCIPisFinite(p4val) || SCIPisInfinity(scip, REALABS(p4val)) )
1646 if( !SCIPisFinite(p1val) || SCIPisInfinity(scip, REALABS(p1val)) || !SCIPisFinite(p2val) || SCIPisInfinity(scip, REALABS(p2val)) )
1666 /* if we want an underestimator, flip f(x,y), i.e., do as if we compute an overestimator for -f(x,y) */
1680 if( !SCIPisFinite(p1val) || SCIPisInfinity(scip, REALABS(p1val)) || !SCIPisFinite(p2val) || SCIPisInfinity(scip, REALABS(p2val)) ||
1681 ! SCIPisFinite(p3val) || SCIPisInfinity(scip, REALABS(p3val)) || !SCIPisFinite(p4val) || SCIPisInfinity(scip, REALABS(p4val)) )
1691 * Since we assume that f is convex, we then know that all points (x,y,f(x,y)) are below this hyperplane, i.e.,
1700 SCIP_CALL( SCIPcomputeHyperplaneThreePoints(scip, p1[0], p1[1], p1val, p2[0], p2[1], p2val, p3[0], p3[1], p3val, &alpha,
1703 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p1[0] + beta * p1[1] + gamma_ * p1val, delta));
1704 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p2[0] + beta * p2[1] + gamma_ * p2val, delta));
1705 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p3[0] + beta * p3[1] + gamma_ * p3val, delta));
1707 /* if hyperplane through p1,p2,p3 does not overestimate f(p4), then it must be the other variant */
1713 SCIP_CALL( SCIPcomputeHyperplaneThreePoints(scip, p1[0], p1[1], p1val, p3[0], p3[1], p3val, p4[0], p4[1], p4val, &alpha,
1716 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p1[0] + beta * p1[1] + gamma_ * p1val, delta));
1717 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p3[0] + beta * p3[1] + gamma_ * p3val, delta));
1718 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p4[0] + beta * p4[1] + gamma_ * p4val, delta));
1720 /* if hyperplane through p1,p3,p4 does not overestimate f(p2), then it must be the other variant */
1729 SCIP_CALL( SCIPcomputeHyperplaneThreePoints(scip, p1[0], p1[1], p1val, p2[0], p2[1], p2val, p4[0], p4[1], p4val,
1733 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p1[0] + beta * p1[1] + gamma_ * p1val, delta));
1734 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p2[0] + beta * p2[1] + gamma_ * p2val, delta));
1735 assert(SCIPisInfinity(scip, delta) || SCIPisFeasLE(scip, alpha * p3[0] + beta * p3[1] + gamma_ * p3val, delta));
1736 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p4[0] + beta * p4[1] + gamma_ * p4val, delta));
1740 SCIP_CALL( SCIPcomputeHyperplaneThreePoints(scip, p2[0], p2[1], p2val, p3[0], p3[1], p3val, p4[0], p4[1], p4val,
1744 assert(SCIPisInfinity(scip, delta) || SCIPisFeasLE(scip, alpha * p1[0] + beta * p1[1] + gamma_ * p1val, delta));
1745 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p2[0] + beta * p2[1] + gamma_ * p2val, delta));
1746 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p3[0] + beta * p3[1] + gamma_ * p3val, delta));
1747 assert(SCIPisInfinity(scip, delta) || SCIPisFeasEQ(scip, alpha * p4[0] + beta * p4[1] + gamma_ * p4val, delta));
1751 SCIPdebugMsg(scip, "alpha = %g, beta = %g, gamma = %g, delta = %g\n", alpha, beta, gamma_, delta);
1795 SCIP_CALL( generateEstimatingHyperplane(scip, exprinterpreter, consdata->f, TRUE, x0y0, &coefs[0], &coefs[1], &constant, &success) );
1804 SCIP_CALL( SCIPcreateRowCons(scip, row, cons, "bivaroveresthyperplanecut", 0, NULL, NULL, consdata->lhs - constant, SCIPinfinity(scip), TRUE, FALSE, TRUE) );
1812 SCIPdebugMsg(scip, "failed to compute overestimator for all-convex constraint <%s>\n", SCIPconsGetName(cons));
1904 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e1, SCIPexprtreeGetRoot(f)) ); /* e1 = f(x,y) */
1907 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp2, SCIP_EXPR_CONST, 1.0 - 1.0 / t) ); /* tmp2 = 1-1/t */
1908 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_MUL, tmp, tmp2) ); /* tmp = (1-1/t)*s */
1911 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp2, SCIP_EXPR_CONST, 1/t*xval) ); /* tmp2 = 1/t*xval */
1912 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_PLUS, tmp, tmp2) ); /* tmp = 1/t*xval + (1-1/t)*s */
1916 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[1], SCIP_EXPR_CONST, ylb) ); /* tmp = ylb */
1918 assert(SCIPexprGetOperator(e1) != SCIP_EXPR_VARIDX); /* substitute cannot substitute the root node, but f should not be a single variable anyway */
1919 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e1, subst) ); /* e1 = f(1/t*xval + (1-1/t)*s, ylb) */
1925 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e2, SCIPexprtreeGetRoot(f)) ); /* e2 = f(x,y) */
1931 assert(SCIPexprGetOperator(e2) != SCIP_EXPR_VARIDX); /* substitute cannot substitute the root node, but f should not be a single variable anyway */
1938 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &e1, SCIP_EXPR_MUL, e1, tmp) ); /* e1 = t * f(1/t*xval+(1-1/t)*s,ylb) */
1940 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_CONST, 1.0 - t) ); /* tmp = 1 - t */
1941 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &e2, SCIP_EXPR_MUL, e2, tmp) ); /* e2 = (1-t) * f(s, yub) */
1958 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vredtree, 0.0, slb, sub, &sval, success) );
2026 SCIPdebugMsg(scip, "Parallel: r=%g in [%g,%g], s=%g in [%g,%g], f(r,ylb)=%g, f(xlb,s)=%g\n",rval,xlb,xub,sval,ylb,yub,frval,fsval);
2027 SCIPdebugMsg(scip, "(r,ylb)=(%g,%g), (s,yub)=(%g,%g), vredval=%g\n",rval,ylb,sval,yub,*convenvvalue);
2041 SCIPdebugMsg(scip, "Parallel: cutcoeff[0]=%g, cutcoeff[1]=%g, cutcoeff[2]=1.0, cutcoeff[3]=%g\n",cutcoeff[0]/cutcoeff[2],cutcoeff[1]/cutcoeff[2],cutcoeff[3]/cutcoeff[2]);
2131 SCIPdebugMsg(scip, "%s[%g,%g] = %g %s[%g,%g] = %g\n", SCIPvarGetName(x), xlb, xub, xval, SCIPvarGetName(y), ylb, yub, yval);
2141 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_CONST, yval-ylb) ); /* tmp = yval-ylb */
2142 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, tmp, expr) ); /* expr = (yval-ylb) / t */
2146 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_PLUS, expr, tmp) ); /* expr = ylb + (yval-ylb) / t */
2150 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[0], SCIP_EXPR_CONST, xlb) ); /* subst[0] = xlb */
2152 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e1, SCIPexprtreeGetRoot(f)) ); /* e1 = f(x,y) */
2153 assert(SCIPexprGetOperator(e1) != SCIP_EXPR_VARIDX); /* expr substitute vars cannot substitute the root node, but f should not be a single variable anyway */
2154 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e1, subst) ); /* e1 = f(xlb, ylb + (yval-ylb)/t) */
2162 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MINUS, tmp, expr1) ); /* expr1 = 1-t */
2166 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, expr2, tmp) ); /* expr2 = xlb * t */
2168 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MINUS, tmp, expr2) ); /* expr2 = xval - xlb * t */
2170 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, expr2, expr1) ); /* expr = (xval-t*xlb)/(1-t) */
2173 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[1], SCIP_EXPR_CONST, ylb) ); /* subst[0] = ylb */
2175 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e2, SCIPexprtreeGetRoot(f)) ); /* e2 = f(x,y) */
2176 assert(SCIPexprGetOperator(e2) != SCIP_EXPR_VARIDX); /* expr substitute vars cannot substitute the root node, but f should not be a single variable anyway */
2177 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e2, subst) ); /* e2 = f((xval-xlb*t)/(1-t), ylb) */
2185 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MUL, expr, e1) ); /* expr1 = t * e1*/
2189 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_MINUS, tmp, expr) ); /* expr = 1 - t */
2190 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, expr, e2) ); /* expr2 = (1-t) * e2 */
2201 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vredtree, 0.0, tlb, tub, &tval, success) );
2267 if( !SCIPisFinite(grad_sval[0]) || !SCIPisFinite(grad_rval[0]) || SCIPisInfinity(scip, REALABS(MIN(grad_sval[0],grad_rval[0]))) )
2269 /* FIXME maybe it is sufficient to have one of them finite, using that one for the MIN below? */
2280 SCIPdebugMsg(scip, "LowerLeft: r=%g in [%g,%g], s=%g in [%g,%g], f(s,ylb)=%g, f(xlb,r)=%g\n",rval,xlb,xub,sval,ylb,yub,fsval,frval);
2281 SCIPdebugMsg(scip, "(s,ylb)=(%g,%g) (xlb,r)=(%g,%g) t=%g, vredval=%g\n",sval,ylb,xlb,rval,tval,*convenvvalue);
2282 SCIPdebugMsg(scip, "LowerLeft: cutcoeff[0]=%g, cutcoeff[1]=%g,cutcoeff[2]=%g,cutcoeff[3]=%g\n",cutcoeff[0],cutcoeff[1],cutcoeff[2],cutcoeff[3]);
2291 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_CONST, yval-yub) ); /* tmp = yval-yub*/
2292 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, tmp, expr) ); /* expr = (yval-yub) / t */
2296 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_PLUS, expr, tmp) ); /* expr = yub + (yval-yub)/t */
2300 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[0], SCIP_EXPR_CONST, xub) ); /* tmp = xub */
2302 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e1, SCIPexprtreeGetRoot(f)) ); /* e1 = f(x,y) */
2304 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e1, subst) ); /* e1 = f(xub, yub + (yval-yub)/t) */
2312 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MINUS, tmp, expr1) ); /* expr1 = 1-t */
2316 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, expr2, tmp) ); /* expr2 = xub * t */
2318 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MINUS, tmp, expr2) ); /* expr2 = xval - xub * t */
2320 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, expr2, expr1) ); /* expr = (xval-t*xub)/(1-t) */
2323 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[1], SCIP_EXPR_CONST, yub) ); /* tmp = yub */
2325 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e2, SCIPexprtreeGetRoot(f)) ); /* e2 = f(x,y) */
2327 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e2, subst) ); /* e2 = f((xval-t*xub)/(1-t), yub) */
2334 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MUL, e1, expr) ); /* expr1 = t * e1*/
2338 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_MINUS, tmp, expr) ); /* expr = 1-t */
2340 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, e2, expr) ); /* expr2 = (1-t) * e2*/
2351 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vredtree, 0.0, tlb, tub, &tval, success) );
2423 if( !SCIPisFinite(grad_sval[0]) || !SCIPisFinite(grad_rval[0]) || SCIPisInfinity(scip, REALABS(MIN(grad_sval[0],grad_rval[0]))) )
2425 /* FIXME maybe it is sufficient to have one of them finite, using that one for the MIN below? */
2437 SCIPdebugMsg(scip, "UpperRight: r=%g in [%g,%g], s=%g in [%g,%g], f(r,yub)=%g, f(xub,s)=%g\n",rval,xlb,xub,sval,ylb,yub,frval,fsval);
2438 SCIPdebugMsg(scip, "(s,yub)=(%g,%g) (xub,r)=(%g,%g) t=%g, vredval=%g\n",sval,yub,xub,rval,tval,*convenvvalue);
2439 SCIPdebugMsg(scip, "UpperRight: cutcoeff[0]=%g, cutcoeff[1]=%g, cutcoeff[2]=%g, cutcoeff[3]=%g\n",cutcoeff[0],cutcoeff[1],cutcoeff[2],cutcoeff[3]);
2535 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_CONST, xval-xub) ); /* tmp = xval-xub */
2536 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, tmp, expr) ); /* expr = (xval-xub)/t */
2540 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_PLUS, expr, tmp) ); /* expr = xub + (xval-xub)/t */
2544 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[1], SCIP_EXPR_CONST, ylb) ); /* subst[1] = ylb */
2546 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e1, SCIPexprtreeGetRoot(f)) ); /* e1 = f(x,y) */
2548 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e1, subst) ); /* e1 = f(xub + (xval-xub)/t, ylb) */
2556 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MINUS, tmp, expr1) ); /* expr1 = 1-t */
2560 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, expr2, tmp) ); /* expr2 = ylb * t */
2562 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MINUS, tmp, expr2) ); /* expr2 = yval - ylb * t */
2565 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, expr2, expr1) ); /* expr = (yval-t*ylb)/(1-t) */
2568 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[0], SCIP_EXPR_CONST, xub) ); /* subst[0] = xub */
2570 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e2, SCIPexprtreeGetRoot(f)) ); /* e2 = f(x,y) */
2572 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e2, subst) ); /* e2 = f(xub, (yval-t*ylb)/(1-t)) */
2579 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MUL, e1, expr) ); /* expr1 = t * e1*/
2583 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_MINUS, tmp, expr) ); /* expr = 1-t */
2584 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, e2, expr) ); /* expr2 = (1-t) * e2*/
2595 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vredtree, 0.0, tlb, tub, &tval, success) );
2658 if( !SCIPisFinite(grad_sval[0]) || !SCIPisFinite(grad_rval[0]) || SCIPisInfinity(scip, REALABS(MIN(grad_sval[0],grad_rval[0]))) )
2660 /* FIXME maybe it is sufficient to have one of them finite, using that one for the MIN below? */
2671 SCIPdebugMsg(scip, "LowerRight: t=%g in [%g,%g], r=%g in [%g,%g], s=%g in [%g,%g]\n",tval,tlb,tub,rval,xlb,xub,sval,ylb,yub);
2672 SCIPdebugMsg(scip, "LowerRight: (r,ylb)=(%g,%g) (xub,sval)=(%g,%g) vredval=%g\n",rval,ylb,xub,sval,*convenvvalue);
2673 SCIPdebugMsg(scip, "LowerRight: cutcoeff[0]=%g, cutcoeff[1]=%g,cutcoeff[2]=1.0,cutcoeff[3]=%g\n",cutcoeff[0]/cutcoeff[2],cutcoeff[1]/cutcoeff[2],cutcoeff[3]/cutcoeff[2]);
2682 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &tmp, SCIP_EXPR_CONST, xval-xlb) ); /* tmp = xval-xlb */
2683 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, tmp, expr) ); /* expr = (xval-xlb)/lambda */
2687 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_PLUS, expr, tmp) ); /* expr = xlb + (xval-xlb)/t */
2691 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[1], SCIP_EXPR_CONST, yub) ); /* subst[1] = yub */
2693 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e1, SCIPexprtreeGetRoot(f)) ); /* e1 = f(x,y) */
2695 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e1, subst) ); /* e1 = f(xlb + (xval-xlb)/t, yub) */
2703 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MINUS, tmp, expr1) ); /* expr1 = 1-t */
2707 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, expr2, tmp) ); /* expr2 = yub * t */
2709 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MINUS, tmp, expr2) ); /* expr2 = yval - yub * t */
2712 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_DIV, expr2, expr1) ); /* expr = (yval-t*yub)/(1-t) */
2715 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &subst[0], SCIP_EXPR_CONST, xlb) ); /* subst[0] = xlb */
2717 SCIP_CALL( SCIPexprCopyDeep(SCIPblkmem(scip), &e2, SCIPexprtreeGetRoot(f)) ); /* e2 = f(x,y) */
2718 SCIP_CALL( SCIPexprSubstituteVars(SCIPblkmem(scip), e2, subst) ); /* e2 = f( xlb , (yval-t*yub)/(1-t) ) */
2725 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr1, SCIP_EXPR_MUL, e1, expr) ); /* expr1 = t * e1*/
2729 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr, SCIP_EXPR_MINUS, tmp, expr) ); /* expr = 1-t */
2730 SCIP_CALL( SCIPexprCreate(SCIPblkmem(scip), &expr2, SCIP_EXPR_MUL, e2, expr) ); /* expr2 = (1-t) * e2*/
2741 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vredtree, 0.0, tlb, tub, &tval, success) );
2804 if( !SCIPisFinite(grad_sval[0]) || !SCIPisFinite(grad_rval[0]) || SCIPisInfinity(scip, REALABS(MIN(grad_rval[0],grad_sval[0]))) )
2806 /* FIXME maybe it is sufficient to have one of them finite, using that one for the MIN below? */
2817 SCIPdebugMsg(scip, "UpperLeft: r=%g in [%g,%g], s=%g in [%g,%g], f(r,yub)=%g, f(xlb,s)=%g\n",rval,xlb,xub,sval,ylb,yub,frval,fsval);
2818 SCIPdebugMsg(scip, "t=%g in [%g,%g], (r,yub)=(%g,%g) (xlb,sval)=(%g,%g) vredval=%g\n",tval,tlb,tub,rval,yub,xlb,sval,*convenvvalue);
2819 SCIPdebugMsg(scip, "UpperLeft: cutcoeff[0]=%g, cutcoeff[1]=%g,cutcoeff[2]=1.0,cutcoeff[3]=%g\n",cutcoeff[0]/cutcoeff[2],cutcoeff[1]/cutcoeff[2],cutcoeff[3]/cutcoeff[2]);
2826 /** generates a linear underestimator for f(x,y) with f(x,y) being STRICTLY convex in x and concave in y
2827 * generate coefficients cutcoeff = (alpha, beta, gamma, delta), such that alpha * x + beta * y - delta <= gamma * f(x,y)
2956 SCIPdebugMsg(scip, "cannot evaluate function or derivative in (xval,ylb), also after perturbation\n");
2994 if( !SCIPisFinite(gradylb[0]) || !SCIPisFinite(gradyub[0]) || !SCIPisFinite(fvalylb) || !SCIPisFinite(fvalyub) ||
3051 SCIPdebug( SCIP_CALL( SCIPexprtreePrintWithNames(f_yfixed, SCIPgetMessagehdlr(scip), NULL) ) );
3057 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, f_yfixed, grad[0], xlb, xub, &xtilde, success) );
3064 /* if we could not find an xtilde such that f'(xtilde,yub) = f'(xval,ylb), then probably because f'(x,yub) is constant
3065 * in this case, choose xtilde from {xlb, xub} such that it maximizes f'(xtilde, yub) - grad[0]*xtilde
3072 SCIPdebugMsg(scip, "couldn't solve deriv equ, compare f(%g,%g) - %g*%g = %g and f(%g,%g) - %g*%g = %g\n",
3106 SCIPdebugMsg(scip, "alpha: %g, beta: %g, gamma: %g, delta: %g\n", cutcoeff[0], cutcoeff[1], cutcoeff[2], cutcoeff[3]);
3143 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, f_yfixed, grad[0], xlb, xub, &xtilde, success) );
3150 /* if we could not find an xtilde such that f'(xtilde,ylb) = f'(xval,yub), then probably because f'(x,ylb) is constant
3151 * in this case, choose xtilde from {xlb, xub} such that it maximizes f'(xtilde, yub) - grad[0]*xtilde
3158 SCIPdebugMsg(scip, "couldn't solve deriv equ, compare f(%g,%g) - %g*%g = %g and f(%g,%g) - %g*%g = %g\n",
3192 SCIPdebugMsg(scip, "alpha: %g, beta: %g, gamma: %g, delta: %g\n", cutcoeff[0], cutcoeff[1], cutcoeff[2], cutcoeff[3]);
3254 SCIP_CALL( solveDerivativeEquation(scip, exprinterpreter, vred, 0.0, slb, sub, &sval, success) );
3317 SCIPdebugMsg(scip, "Parallel: r=%g s=%g in [%g,%g], y in [%g,%g], f(r,ylb)=%g, f(xlb,s)=%g\n",rval,sval,xlb,xub,ylb,yub,frval,fsval);
3318 SCIPdebugMsg(scip, "(r,ylb)=(%g,%g), (s,yub)=(%g,%g), vredval=%g\n",rval,ylb,sval,yub,*convenvvalue);
3333 SCIPdebugMsg(scip, "Parallel: cutcoeff[0]=%g, cutcoeff[1]=%g,cutcoeff[2]=1.0,cutcoeff[3]=%g\n",cutcoeff[0]/cutcoeff[2],cutcoeff[1]/cutcoeff[2],cutcoeff[3]/cutcoeff[2]);
3341 /** generates a cut for one side of lhs <= f(x,y) + c*z <= rhs with f(x,y) being convex in x and concave in y */
3385 SCIP_CALL( generateEstimatingHyperplane(scip, exprinterpreter, consdata->f, TRUE, xyref, &coefs[0], &coefs[1], &constant, &success) );
3393 (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "%s_overesthyperplanecut_%d", SCIPconsGetName(cons), SCIPgetNLPs(scip));
3394 SCIP_CALL( SCIPcreateRowCons(scip, row, cons, cutname, 0, NULL, NULL, consdata->lhs - constant, SCIPinfinity(scip), TRUE, FALSE, TRUE) );
3407 /* f is strictly concave in y -> can compute overestimator by applying generateConvexConcaveUnderstimator on -f(y,x) */
3412 SCIP_CALL( generateConvexConcaveUnderestimator(scip, exprinterpreter, consdata->sepaconvexconcave.f_neg_swapped, consdata->sepaconvexconcave.f_neg_swapped_yfixed, consdata->sepaconvexconcave.vred_neg_swapped, xyref_, cutcoeff, &dummy, &success) );
3429 (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "%s_convexconcaveoverest_%d", SCIPconsGetName(cons), SCIPgetNLPs(scip));
3430 SCIP_CALL( SCIPcreateEmptyRowCons(scip, row, cons, cutname, consdata->lhs - cutcoeff[3]/cutcoeff[2], SCIPinfinity(scip),
3451 SCIP_CALL( generateEstimatingHyperplane(scip, exprinterpreter, consdata->f, FALSE, xyref, &coefs[0], &coefs[1], &constant, &success) );
3459 (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "%s_underesthyperplanecut_%d", SCIPconsGetName(cons), SCIPgetNLPs(scip));
3460 SCIP_CALL( SCIPcreateRowCons(scip, row, cons, cutname, 0, NULL, NULL, -SCIPinfinity(scip), consdata->rhs - constant, TRUE, FALSE, TRUE) );
3471 /* f is strictly convex in x -> can compute underestimator by applying generateConvexConcaveUnderstimator */
3472 assert(!consdata->sepaconvexconcave.linearinx); /* generateConvexConcaveUnderestimator assumes that if f is strictly convex in x */
3474 SCIP_CALL( generateConvexConcaveUnderestimator(scip, exprinterpreter, consdata->f, consdata->sepaconvexconcave.f_yfixed, consdata->sepaconvexconcave.vred, xyref, cutcoeff, &dummy, &success) );
3492 (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "%s_convexconcaveunderest_%d", SCIPconsGetName(cons), SCIPgetNLPs(scip));
3493 SCIP_CALL( SCIPcreateEmptyRowCons(scip, row, cons, cutname, -SCIPinfinity(scip), consdata->rhs + cutcoeff[3]/cutcoeff[2],
3508 /** computes an underestimating hyperplane for functions that are convex in x and y if the point to cut off lies on the boundary */
3596 /** generate a linear underestimator for f(x,y) with f(x,y) being convex in x and convex in y and the point to cut off lies on the boundary
3597 * generate coefficients cutcoeff = (alpha, beta, gamma, delta), such that alpha * x + beta * y - delta <= gamma * f(x,y)
3705 SCIP_CALL( lifting(scip,exprinterpreter,f,xval,yval,xlb,xlb,ylb,yub,-1,cutcoeff,convenvvalue,success) );
3722 SCIP_CALL( lifting(scip,exprinterpreter,f,xval,yval,xlb,xub,ylb,ylb,-1,cutcoeff,convenvvalue,success) );
3747 SCIP_CALL( lifting(scip,exprinterpreter,f,xval,yval,xub,xub,ylb,yub,1,cutcoeff,convenvvalue,success) );
3764 SCIP_CALL( lifting(scip,exprinterpreter,f,xval,yval,xlb,xub,yub,yub,1,cutcoeff,convenvvalue,success) );
3778 SCIPerrorMessage("Tries to compute underestimator for a point at the boundary. But point is not on the boundary!\n");
3782 /** generates a linear underestimator for f(x,y) with f(x,y) being convex in x and convex in y but indefinite
3783 * This is for the case where the cone of the concave directions is (R_+ x R_-) union (R_\- x R_+).
3856 if( !SCIPisFinite(fval_xub_ylb) || SCIPisInfinity(scip, REALABS(fval_xub_ylb)) || !SCIPisFinite(fval_xlb_yub) || SCIPisInfinity(scip, REALABS(fval_xlb_yub)) )
3872 SCIPdebugMsg(scip, "xval=%g in [%g,%g], yval=%g in [%g,%g]\n", xyref[0], xlb, xub, xyref[1], ylb, yub);
3903 SCIP_CALL( generateOrthogonal_lx_ly_Underestimator(scip, exprinterpreter, f, xyref, all_cutcoeff[0], &all_convenvvalue[0], &all_success[0]) );
3905 SCIP_CALL( generateUnderestimatorParallelYFacets(scip, exprinterpreter, f, xyref, all_cutcoeff[1], &all_convenvvalue[1], &all_success[1]) );
3918 SCIP_CALL( generateOrthogonal_lx_ly_Underestimator(scip, exprinterpreter, fswapped, xyref_, all_cutcoeff[0], &all_convenvvalue[0], &all_success[0]) ); /*lint !e644*/
3920 SCIP_CALL( generateUnderestimatorParallelYFacets(scip, exprinterpreter, fswapped, xyref_, all_cutcoeff[1], &all_convenvvalue[1], &all_success[1]) );
3977 /** generates a linear underestimator for f(x,y) with f(x,y) being convex in x and convex in y but indefinite
3978 * This is for the case where the cone of the concave directions is (R_+ x R_+) union (R_- x R_-).
3987 * Generates coefficients cutcoeff = (alpha, beta, gamma, delta), such that alpha * x + beta * y - delta <= gamma * f(x,y)
4056 if( !SCIPisFinite(fval_xlb_ylb) || SCIPisInfinity(scip, REALABS(fval_xlb_ylb)) || !SCIPisFinite(fval_xub_yub) || SCIPisInfinity(scip, REALABS(fval_xub_yub)) )
4068 SCIPdebugMsg(scip, "xval=%g in [%g,%g], yval=%g in [%g,%g]\n",xyref[0],xlb,xub,xyref[1],ylb,yub);
4071 if( SCIPisGE( scip, fval_xlb_ylb+(yub-ylb)*grad_xlb_ylb[1], fval_xub_yub+(xlb-xub)*grad_xub_yub[0] ) )
4098 SCIP_CALL( generateOrthogonal_lx_uy_Underestimator(scip, exprinterpreter, f, xyref, all_cutcoeff[0], &all_convenvvalue[0], &all_success[0]) );
4100 SCIP_CALL( generateUnderestimatorParallelYFacets(scip, exprinterpreter, f, xyref, all_cutcoeff[1], &all_convenvvalue[1], &all_success[1]) );
4112 SCIP_CALL( generateOrthogonal_lx_uy_Underestimator(scip, exprinterpreter, fswapped, xyref_, all_cutcoeff[0], &all_convenvvalue[0], &all_success[0]) ); /*lint !e644*/
4114 SCIP_CALL( generateUnderestimatorParallelYFacets(scip, exprinterpreter, fswapped, xyref_, all_cutcoeff[1], &all_convenvvalue[1], &all_success[1]) );
4171 /** generates a linear underestimator for f(x,y) with f(x,y) being convex in x and convex in y but indefinite
4172 * generate coefficients cutcoeff = (alpha, beta, gamma, delta), such that alpha * x + beta * y - delta <= gamma * f(x,y)
4229 if( SCIPisInfinity(scip, -xlb) || SCIPisInfinity(scip, xub) || SCIPisInfinity(scip, -ylb) || SCIPisInfinity(scip, yub) )
4231 SCIPdebugMsg(scip, "skip underestimate for 1-convex indefinite constraint <%s> since <%s> or <%s> is unbounded\n", SCIPconsGetName(cons), SCIPvarGetName(x), SCIPvarGetName(y));
4242 if( SCIPisFeasEQ(scip,xyref[0],xlb) || SCIPisFeasEQ(scip,xyref[0],xub) || SCIPisFeasEQ(scip,xyref[1],ylb) || SCIPisFeasEQ(scip,xyref[1],yub) )
4244 SCIP_CALL( generate1ConvexIndefiniteUnderestimatorAtBoundary(scip, exprinterpreter, f, xyref, cutcoeff, &convenvvalue, &success) );
4267 SCIP_CALL( generate1ConvexIndefiniteUnderestimatorInTheInteriorPatternA(scip, exprinterpreter, f, xyref, cutcoeff, &convenvvalue, &success) );
4273 SCIP_CALL( generate1ConvexIndefiniteUnderestimatorInTheInteriorPatternB(scip, exprinterpreter, f, xyref, cutcoeff, &convenvvalue, &success) );
4309 SCIP_CALL( SCIPcreateEmptyRowCons(scip, row, cons, "1ConvexUnderest", -SCIPinfinity(scip), rhs,
4311 SCIP_CALL( SCIPaddVarToRow(scip, *row, SCIPexprtreeGetVars(consdata->f)[0], cutcoeff[0] / cutcoeff[2]) );
4312 SCIP_CALL( SCIPaddVarToRow(scip, *row, SCIPexprtreeGetVars(consdata->f)[1], cutcoeff[1] / cutcoeff[2]) );
4363 SCIPdebugMsg(scip, "generate cut for constraint <%s> with %s hand side violated by %g\n", SCIPconsGetName(cons), violside == SCIP_SIDETYPE_LEFT ? "left" : "right", violside == SCIP_SIDETYPE_LEFT ? consdata->lhsviol : consdata->rhsviol);
4369 SCIPdebugMsgPrint(scip, ", %s = %g with bounds [%g, %g]", SCIPvarGetName(consdata->z), SCIPgetSolVal(scip, sol, consdata->z), SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z));
4439 SCIPdebugMsg(scip, "cut coefficients for constraint <%s> have very large range: mincoef = %g maxcoef = %g\n", SCIPconsGetName(cons), mincoef, maxcoef);
4441 /* if minimal coefficient is given by z, then give up (probably the maximal coefficient is the problem) */
4444 SCIPdebugMsg(scip, "could not eliminate small coefficient, since it comes from linear part\n");
4459 if( ((coef > 0.0 && violside == SCIP_SIDETYPE_RIGHT) || (coef < 0.0 && violside == SCIP_SIDETYPE_LEFT)) && !SCIPisInfinity(scip, -SCIPvarGetLbLocal(var)) )
4461 SCIPdebugMsg(scip, "eliminate coefficient %g for <%s> = %g [%g, %g]\n", coef, SCIPvarGetName(var), SCIPgetSolVal(scip, sol, var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var));
4468 if( ((coef < 0.0 && violside == SCIP_SIDETYPE_RIGHT) || (coef > 0.0 && violside == SCIP_SIDETYPE_LEFT)) && !SCIPisInfinity(scip, SCIPvarGetUbLocal(var)) )
4470 SCIPdebugMsg(scip, "eliminate coefficient %g for <%s> = %g [%g, %g]\n", coef, SCIPvarGetName(var), SCIPgetSolVal(scip, sol, var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var));
4504 SCIPdebugMsg(scip, "drop row for constraint <%s> because range of coefficients is too large: mincoef = %g, maxcoef = %g -> range = %g\n",
4512 SCIPdebugMsg(scip, "drop row for constraint <%s> because of very large side: %g\n", SCIPconsGetName(cons), violside == SCIP_SIDETYPE_LEFT ? -SCIProwGetLhs(*row) : SCIProwGetRhs(*row));
4521 * i.e., if side == RIGHT, then returns whether constraint function is convex w.r.t. local bounds
4565 return (side == SCIP_SIDETYPE_RIGHT && SCIPisEQ(scip, SCIPvarGetLbLocal(xy[1]), SCIPvarGetUbLocal(xy[1]))) ||
4566 (side == SCIP_SIDETYPE_LEFT && SCIPisEQ(scip, SCIPvarGetLbLocal(xy[0]), SCIPvarGetUbLocal(xy[0])));
4599 SCIPinfoMessage(scip, NULL, "splot [%g:%g] [%g:%g] ", SCIPvarGetLbLocal(x), SCIPvarGetUbLocal(x), SCIPvarGetLbLocal(y), SCIPvarGetUbLocal(y));
4601 SCIPinfoMessage(scip, NULL, "%+g", side == SCIP_SIDETYPE_LEFT ? consdata->lhs : consdata->rhs);
4603 SCIPinfoMessage(scip, NULL, ", %g", SCIPisInfinity(scip, SCIProwGetRhs(row)) ? -SCIProwGetLhs(row) : -SCIProwGetRhs(row));
4615 SCIPinfoMessage(scip, NULL, ", \"< echo '%g %g %g'\" with circles", SCIPgetSolVal(scip, sol, x), SCIPgetSolVal(scip, sol, y), consdata->activity);
4636 SCIP_Real* bestefficacy /**< buffer to store best efficacy of a cut that was added to the LP, if found; or NULL if not of interest */
4667 if( SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) || SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
4673 violside = SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) ? SCIP_SIDETYPE_LEFT : SCIP_SIDETYPE_RIGHT;
4676 SCIP_CALL( generateCut(scip, conshdlrdata->exprinterpreter, conss[c], sol, violside, conshdlrdata->cutmaxrange, &row) );
4688 /* if cut is strong enough or it's weak but we separate on a convex function and accept weak cuts there, add cut to SCIP */
4690 (inenforcement && SCIPisGT(scip, efficacy, SCIPfeastol(scip)) && isConvexLocal(scip, conss[c], violside))) &&
4699 SCIPdebugMsg(scip, "cut for constraint <%s> is infeasible -> cutoff.\n", SCIPconsGetName(conss[c]));
4704 SCIPdebugMsg(scip, "added cut with efficacy %g for constraint <%s> violated by %g\n", efficacy, SCIPconsGetName(conss[c]), MAX(consdata->lhsviol, consdata->rhsviol));
4716 SCIPdebugMsg(scip, "abandon cut since efficacy %g is too small or not applicable\n", efficacy);
4726 * others are only checked and enforced if we are still feasible or have not found a separating cut yet
4735 /** processes the event that a new primal solution has been found adds linearizations of all-convex constraints to the cutpool */
4738 {
4769 /* we are only interested in solution coming from some heuristic other than trysol, but not from the tree
4770 * the reason for ignoring trysol solutions is that they may come from an NLP solve in sepalp, where we already added linearizations,
4779 SCIPdebugMsg(scip, "catched new sol event %" SCIP_EVENTTYPE_FORMAT " from heur <%s>; have %d conss\n", SCIPeventGetType(event), SCIPheurGetName(SCIPsolGetHeur(sol)), nconss);
4794 SCIP_CALL( generateLinearizationCut(scip, conshdlrdata->exprinterpreter, conss[c], x0y0, TRUE, &row) );
4811 /** registers unfixed variables in nonlinear terms of violated constraints as external branching candidates
4812 * We score the variables by their gap between the convex envelope and the bivariate function in the current (x,y).
4813 * This value is given by the constraint violation, since we assume that cuts have been generated which support
4838 SCIPdebugMsg(scip, "cons <%s> violation: %g %g\n", SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4852 /* regarding left hand side, we are concave in x and convex in y, so branch on x, if not fixed */
4855 SCIPdebugMsg(scip, "register variable x = <%s>[%g,%g] in convex-concave <%s> with violation %g %g\n", SCIPvarGetName(xy[0]), SCIPvarGetLbLocal(xy[0]), SCIPvarGetUbLocal(xy[0]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4862 /* regarding right hand side, we are convex in x and concave in y, so branch on y, if not fixed */
4865 SCIPdebugMsg(scip, "register variable y = <%s>[%g,%g] in convex-concave <%s> with violation %g %g\n", SCIPvarGetName(xy[1]), SCIPvarGetLbLocal(xy[1]), SCIPvarGetUbLocal(xy[1]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4876 if( SCIPisEQ(scip, SCIPvarGetLbLocal(xy[0]), SCIPvarGetUbLocal(xy[0])) || SCIPisEQ(scip, SCIPvarGetLbLocal(xy[1]), SCIPvarGetUbLocal(xy[1])) )
4882 SCIPdebugMsg(scip, "register variable x = <%s>[%g,%g] in 1-convex <%s> with violation %g %g\n", SCIPvarGetName(xy[0]), SCIPvarGetLbLocal(xy[0]), SCIPvarGetUbLocal(xy[0]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4889 SCIPdebugMsg(scip, "register variable y = <%s>[%g,%g] in 1-convex <%s> with violation %g %g\n", SCIPvarGetName(xy[1]), SCIPvarGetLbLocal(xy[1]), SCIPvarGetUbLocal(xy[1]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4908 SCIPdebugMsg(scip, "register variable x = <%s>[%g,%g] in allconvex <%s> with violation %g %g\n", SCIPvarGetName(xy[0]), SCIPvarGetLbLocal(xy[0]), SCIPvarGetUbLocal(xy[0]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4915 SCIPdebugMsg(scip, "register variable y = <%s>[%g,%g] in allconvex <%s> with violation %g %g\n", SCIPvarGetName(xy[1]), SCIPvarGetLbLocal(xy[1]), SCIPvarGetUbLocal(xy[1]), SCIPconsGetName(conss[c]), consdata->lhsviol, consdata->rhsviol);
4926 /** registers a nonlinear variable from a violated constraint as branching candidate that has a large absolute value in the relaxation */
4956 if( !SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) && !SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
4982 /** enforces violated bivariate constraints where both nonlinear variables can be assumed to be fixed
5014 if( !SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) && !SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
5021 /* if all variables are fixed (at least up to epsilson), then the activity of the nonlinear part should be bounded */
5043 SCIPdebugMsg(scip, "Linear constraint with one variable: %g <= %g <%s> <= %g\n", lhs, coef, SCIPvarGetName(consdata->z), rhs);
5067 SCIPdebugMsg(scip, "Linear constraint is a bound: %g <= <%s> <= %g\n", lhs, SCIPvarGetName(consdata->z), rhs);
5137 SCIPdebugMsg(scip, "found <%s> infeasible due to domain propagation for variable <%s>\n", cons != NULL ? SCIPconsGetName(cons) : "???", SCIPvarGetName(var)); /*lint !e585*/
5142 if( !SCIPisInfinity(scip, -SCIPintervalGetInf(bounds)) && SCIPvarGetStatus(var) != SCIP_VARSTATUS_MULTAGGR )
5148 SCIPdebugMsg(scip, "found <%s> infeasible due to domain propagation for variable <%s>\n", cons != NULL ? SCIPconsGetName(cons) : "???", SCIPvarGetName(var)); /*lint !e585*/
5154 SCIPdebugMsg(scip, "tightened lower bound of variable <%s> in constraint <%s> to %g\n", SCIPvarGetName(var), cons != NULL ? SCIPconsGetName(cons) : "???", SCIPvarGetLbLocal(var)); /*lint !e585*/
5160 if( !SCIPisInfinity(scip, SCIPintervalGetSup(bounds)) && SCIPvarGetStatus(var) != SCIP_VARSTATUS_MULTAGGR )
5166 SCIPdebugMsg(scip, "found <%s> infeasible due to domain propagation for variable <%s>\n", cons != NULL ? SCIPconsGetName(cons) : "???", SCIPvarGetName(var)); /*lint !e585*/
5172 SCIPdebugMsg(scip, "tightened upper bound of variable <%s> in constraint <%s> to %g\n", SCIPvarGetName(var), cons != NULL ? SCIPconsGetName(cons) : "???", SCIPvarGetUbLocal(var)); /*lint !e585*/
5191 SCIP_Bool* redundant /**< buffer where to store whether constraint has been found to be redundant */
5219 /* extend interval by epsilon to avoid cutoff in forward propagation if constraint is only almost feasible */
5221 -infty2infty(SCIPinfinity(scip), INTERVALINFTY, -consdata->lhs+SCIPepsilon(scip)), /*lint !e666*/
5222 +infty2infty(SCIPinfinity(scip), INTERVALINFTY, consdata->rhs+SCIPepsilon(scip)) ); /*lint !e666*/
5232 -infty2infty(SCIPinfinity(scip), INTERVALINFTY, -MIN(SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z))), /*lint !e666*/
5233 +infty2infty(SCIPinfinity(scip), INTERVALINFTY, MAX(SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z)))); /*lint !e666*/
5247 SCIPdebugMsg(scip, "found constraint <%s> to be redundant: sides: [%g, %g], activity: [%g, %g]\n",
5248 SCIPconsGetName(cons), consdata->lhs, consdata->rhs, SCIPintervalGetInf(consactivity), SCIPintervalGetSup(consactivity));
5256 SCIPdebugMsg(scip, "found constraint <%s> to be infeasible; sides: [%g, %g], activity: [%g, %g], infeas: %g\n",
5257 SCIPconsGetName(cons), consdata->lhs, consdata->rhs, SCIPintervalGetInf(consactivity), SCIPintervalGetSup(consactivity),
5258 MAX(consdata->lhs - SCIPintervalGetSup(consactivity), SCIPintervalGetInf(consactivity) - consdata->rhs)); /*lint !e666*/
5280 -infty2infty(SCIPinfinity(scip), INTERVALINFTY, -MIN(SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z))), /*lint !e666*/
5281 +infty2infty(SCIPinfinity(scip), INTERVALINFTY, MAX(SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z)))); /*lint !e666*/
5288 SCIPexprgraphTightenNodeBounds(conshdlrdata->exprgraph, consdata->exprgraphnode, tmp, 0.05, INTERVALINFTY, &cutoff);
5291 SCIPdebugMsg(scip, "found constraint <%s> infeasible%s\n", SCIPconsGetName(cons), SCIPinProbing(scip) ? " in probing" : "");
5308 int* ndelconss /**< buffer where to increase if a constraint was deleted (locally) due to redundancy */
5363 SCIPdebugMsg(scip, "starting domain propagation round %d for %d constraints\n", roundnr, nconss);
5369 * @todo could give FALSE if no linear variable in the constraints had been relaxed since last time
5371 SCIP_CALL( SCIPexprgraphPropagateVarBounds(conshdlrdata->exprgraph, INTERVALINFTY, roundnr == 0, &domainerror) );
5415 SCIPdebugMsg(scip, "backward propagation found problem infeasible%s\n", SCIPinProbing(scip) ? " in probing" : "");
5427 SCIP_CALL( propagateBoundsTightenVar(scip, vars[i], SCIPexprgraphGetNodeBounds(varnodes[i]), NULL, &propresult, nchgbds) );
5441 /** Given a solution where every bivariate constraint is either feasible or can be made feasible by
5442 * moving the linear variable, construct the corresponding feasible solution and pass it to the trysol heuristic.
5443 * The method assumes that this is always possible and that not all constraints are feasible already.
5452 SCIP_Bool* success /**< buffer to store whether we succeeded to construct a solution that satisfies all provided constraints */
5496 /* recompute violation of constraint in case solution newsol is not identical to sol anymore */
5531 SCIPdebugMsg(scip, "increase <%s> by %g to %g\n", SCIPvarGetName(var), delta, SCIPgetSolVal(scip, newsol, var));
5563 SCIPdebugMsg(scip, "increase <%s> by %g to %g\n", SCIPvarGetName(var), delta, SCIPgetSolVal(scip, newsol, var));
5578 if( SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) || SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
5582 if( !SCIPisInfinity(scip, SCIPgetUpperbound(scip)) && !SCIPisSumLT(scip, SCIPgetSolTransObj(scip, newsol), SCIPgetUpperbound(scip)) )
5586 /* if we have a solution that should satisfy all nonlinear constraints and has a better objective than the current upper bound,
5590 SCIPdebugMsg(scip, "pass solution with objective value %g to trysol heuristic\n", SCIPgetSolTransObj(scip, newsol));
5602 * lhs <= xsqrcoef * x^2 + xlincoef * x + ysqrcoef * y^2 + ylincoef * y + bilincoef * x*y + zcoef * z <= rhs
5732 SCIP_CALL( SCIPexprCreateQuadratic(SCIPblkmem(scip), &e, 2, children, 0.0, (coefx != 0.0 || coefy != 0.0) ? lincoefs : NULL, nquadelems, quadelems) ); /*lint !e826*/
5754 SCIPdebugMsg(scip, "upgrading constraint <%s> to bivariate constraint <%s> with convexity type %d\n", SCIPconsGetName(srccons), name, convextype);
5769 /** creates expression tree for monomial of the form coef * x^p * y^q with x >= 0 and y >= 0 and checks its convexity type */
5802 *mult = coef < 0.0 ? -1.0 : 1.0; /* for the check, assume that monomial has positive coefficient */
5810 else if( (p > 1.0 && q > 1.0) || (p + q < 1.0 && ((p > 1.0 && q < 0.0) || (p < 0.0 && q > 1.0))) )
5852 assert(*convextype != SCIP_BIVAR_UNKNOWN); /* there should be no case where this can still happen */
5873 SCIP_CALL( SCIPexprCreateMonomial(SCIPblkmem(scip), &monomial, *mult*coef, 2, childidxs, exponents) );
5875 SCIP_CALL( SCIPexprCreatePolynomial(SCIPblkmem(scip), &e, 2, children, 1, &monomial, 0.0, FALSE) );
5884 /** creates bivariate constraint from monomial of the form coef * x^p * y^q with x >= 0 and y >= 0
5919 SCIP_CALL( createExprtreeFromMonomial(scip, x, y, coef, p, q, &exprtree, &mult, &convextype) );
5934 SCIPdebugMsg(scip, "upgrading monomial %g<%s>^%g<%s>^%g from constraint <%s> to bivariate constraint with convexity type %d\n", /*lint !e585*/
5935 coef, SCIPvarGetName(x), p, SCIPvarGetName(y), q, srccons != NULL ? SCIPconsGetName(srccons) : "n/a", convextype); /*lint !e585*/
5968 SCIP_Bool solinfeasible, /**< was the solution already declared infeasible by a constraint handler? */
6001 /* if we are above the 100'th enforcement round for this node, something is strange (maybe the relaxation does not
6002 * think that the cuts we add are violated, or we do ECP on a high-dimensional convex function) in this case, check
6003 * if some limit is hit or SCIP should stop for some other reason and terminate enforcement by creating a dummy node
6004 * (in optimized more, returning SCIP_INFEASIBLE in *result would be sufficient, but in debug mode this would give an
6005 * assert in scip.c) the reason to wait for 100 rounds is to avoid calls to SCIPisStopped in normal runs, which may
6016 SCIP_CALL( SCIPcreateChild(scip, &child, 1.0, SCIPnodeGetEstimate(SCIPgetCurrentNode(scip))) );
6036 SCIPdebugMsg(scip, "enforcement with max violation %g in cons <%s> for %s solution\n", maxviol, SCIPconsGetName(maxviolcons),
6048 /* we would like a cut that is efficient enough that it is not redundant in the LP (>lpfeastol)
6050 * thus, in the latter case, we are also happy if the efficacy is at least, say, 75% of the maximal violation
6055 SCIP_CALL( separatePoint(scip, conshdlr, conss, nconss, nusefulconss, sol, minefficacy, TRUE, &separateresult,
6059 SCIPdebugMessage("separation succeeded (bestefficacy = %g, minefficacy = %g, cutoff = %d)\n", sepaefficacy,
6069 SCIPdebugMsg(scip, "separation failed (bestefficacy = %g < %g = minefficacy ); max viol: %g\n", sepaefficacy,
6079 SCIP_CALL( separatePoint(scip, conshdlr, conss, nconss, nusefulconss, sol, leastpossibleefficacy, TRUE,
6090 /* fallback 2: separation probably failed because of numerical difficulties with a convex constraint;
6091 * if noone declared solution infeasible yet and we had not even found a weak cut, try to resolve by branching
6097 /* fallback 3: all nonlinear variables in all violated constraints seem to be fixed -> treat as linear
6104 /* if the linear constraints are actually feasible, then adding them and returning SCIP_CONSADDED confuses SCIP
6105 * when it enforces the new constraints again and nothing resolves the infeasiblity that we declare here thus,
6106 * we only add them if considered violated, and otherwise claim the solution is feasible (but print a warning)
6115 SCIPwarningMessage(scip, "could not enforce feasibility by separating or branching; declaring solution with viol %g as feasible\n", maxviol);
6121 SCIPdebugMsg(scip, "Could not find any usual branching variable candidate. Proposed variable <%s> with LP value %g for branching.\n",
6151 /** destructor of constraint handler to free constraint handler data (called when SCIP is exiting) */
6197 /** deinitialization method of constraint handler (called before transformed problem is freed) */
6215 /** presolving initialization method of constraint handler (called when presolving is about to begin) */
6230 /* reset may{in,de}creasez to FALSE in case some values are still set from a previous solve round */
6241 /** presolving deinitialization method of constraint handler (called after presolving has been finished) */
6281 assert(consdata->z == NULL || SCIPvarIsActive(consdata->z) || SCIPvarGetStatus(consdata->z) == SCIP_VARSTATUS_MULTAGGR);
6292 /** solving process initialization method of constraint handler (called when branch and bound process is about to begin) */
6363 consdata->convextype == SCIP_BIVAR_ALLCONVEX ? SCIP_EXPRCURV_CONVEX : SCIP_EXPRCURV_UNKNOWN) ); /*lint !e826 !e613*/
6388 SCIP_CALL( SCIPcatchEvent(scip, SCIP_EVENTTYPE_SOLFOUND, eventhdlr, (SCIP_EVENTDATA*)conshdlr, &conshdlrdata->newsoleventfilterpos) );
6410 SCIPverbMessage(scip, SCIP_VERBLEVEL_HIGH, NULL, "%4d left and %4d right bivariate constraints of type [%s]\n", nconvextypeslhs[c], nconvextypesrhs[c], typename);
6422 /** solving process deinitialization method of constraint handler (called before branch and bound process data is freed) */
6442 SCIP_CALL( SCIPdropEvent(scip, SCIP_EVENTTYPE_SOLFOUND, eventhdlr, (SCIP_EVENTDATA*)conshdlr, conshdlrdata->newsoleventfilterpos) );
6474 /* expression should have been removed from expression graph when constraint was deactivated */
6514 SCIPconsIsInitial(sourcecons), SCIPconsIsSeparated(sourcecons), SCIPconsIsEnforced(sourcecons),
6516 SCIPconsIsModifiable(sourcecons), SCIPconsIsDynamic(sourcecons), SCIPconsIsRemovable(sourcecons),
6522 /** LP initialization method of constraint handler (called before the initial LP relaxation at a node is solved) */
6574 * For a missing bound, we either reflect the other bound at 0.0 if finite and on the right side,
6625 SCIPvarGetLbGlobal(SCIPexprtreeGetVars(consdata->f)[0]), SCIPvarGetUbGlobal(SCIPexprtreeGetVars(consdata->f)[0]),
6627 SCIPvarGetLbGlobal(SCIPexprtreeGetVars(consdata->f)[1]), SCIPvarGetUbGlobal(SCIPexprtreeGetVars(consdata->f)[1])
6635 if( !SCIPisInfinity(scip, -consdata->lhs) && !unbounded[0] && !unbounded[1] && (ix == 0 || ix == nref-1) && (iy == 0 || iy == nref-1) )
6641 SCIP_CALL( generateOverestimatingHyperplaneCut(scip, conshdlrdata->exprinterpreter, conss[c], xy, &row1) ); /*lint !e613*/
6646 SCIP_CALL( generateLinearizationCut(scip, conshdlrdata->exprinterpreter, conss[c], xy, TRUE, &row2) ); /*lint !e613*/
6656 SCIP_CALL( generateConvexConcaveEstimator(scip, conshdlrdata->exprinterpreter, conss[c], xy, SCIP_SIDETYPE_LEFT, &row1) ); /*lint !e613*/
6661 SCIP_CALL( generateConvexConcaveEstimator(scip, conshdlrdata->exprinterpreter, conss[c], xy, SCIP_SIDETYPE_RIGHT, &row2) ); /*lint !e613*/
6668 if( !SCIPisInfinity(scip, -consdata->lhs) && !unbounded[0] && !unbounded[1] && (ix == 0 || ix == nref-1) && (iy == 0 || iy == nref-1) )
6674 SCIP_CALL( generateOverestimatingHyperplaneCut(scip, conshdlrdata->exprinterpreter, conss[c], xy, &row1) ); /*lint !e613*/
6678 SCIP_CALL( generate1ConvexIndefiniteUnderestimator(scip, conshdlrdata->exprinterpreter, conss[c], xy, &row2) ); /*lint !e613*/
6685 SCIPwarningMessage(scip, "initlp for convexity type %d not implemented\n", consdata->convextype);
6692 if( SCIPgetRowMaxCoef(scip, row1) / SCIPgetRowMinCoef(scip, row1) > conshdlrdata->cutmaxrange )
6694 SCIPdebugMsg(scip, "drop row1 for constraint <%s> because range of coefficients is too large: mincoef = %g, maxcoef = %g -> range = %g\n",
6695 SCIPconsGetName(conss[c]), SCIPgetRowMinCoef(scip, row1), SCIPgetRowMaxCoef(scip, row1), SCIPgetRowMaxCoef(scip, row1) / SCIPgetRowMinCoef(scip, row1)); /*lint !e613*/
6701 SCIPdebugMsg(scip, "drop row1 for constraint <%s> because of very large lhs: %g\n", SCIPconsGetName(conss[c]), SCIProwGetLhs(row1)); /*lint !e613*/
6714 if( SCIPgetRowMaxCoef(scip, row2) / SCIPgetRowMinCoef(scip, row2) > conshdlrdata->cutmaxrange )
6716 SCIPdebugMsg(scip, "drop row2 for constraint <%s> because range of coefficients is too large: mincoef = %g, maxcoef = %g -> range = %g\n",
6717 SCIPconsGetName(conss[c]), SCIPgetRowMinCoef(scip, row2), SCIPgetRowMaxCoef(scip, row2), SCIPgetRowMaxCoef(scip, row2) / SCIPgetRowMinCoef(scip, row2)); /*lint !e613*/
6723 SCIPdebugMsg(scip, "drop row2 for constraint <%s> because of very large rhs: %g\n", SCIPconsGetName(conss[c]), SCIProwGetLhs(row2)); /*lint !e613*/
6762 SCIP_CALL( separatePoint(scip, conshdlr, conss, nconss, nusefulconss, NULL, SCIPgetSepaMinEfficacy(scip), FALSE, result, NULL) );
6785 SCIP_CALL( separatePoint(scip, conshdlr, conss, nconss, nusefulconss, sol, SCIPgetSepaMinEfficacy(scip), FALSE, result, NULL) );
6794 SCIP_CALL( enforceConstraint(scip, conshdlr, conss, nconss, nusefulconss, NULL, solinfeasible, result) );
6803 SCIP_CALL( enforceConstraint(scip, conshdlr, conss, nconss, nusefulconss, sol, solinfeasible, result) );
6857 if( !SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) && !SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
6860 /* if nonlinear variables are fixed, z should be propagated such that the constraint becomes feasible,
6863 if( consdata->z != NULL && !SCIPisRelEQ(scip, SCIPvarGetLbLocal(consdata->z), SCIPvarGetUbLocal(consdata->z)) )
6865 SCIP_CALL( SCIPaddExternBranchCand(scip, consdata->z, MAX(consdata->lhsviol, consdata->rhsviol), SCIP_INVALID) );
6874 SCIP_CALL( SCIPaddExternBranchCand(scip, var, MAX(consdata->lhsviol, consdata->rhsviol), SCIP_INVALID) );
6882 SCIPdebugMsg(scip, "All variables in violated constraints fixed (up to epsilon). Cannot find branching candidate. Forcing solution of LP.\n");
6920 if( SCIPisGT(scip, consdata->lhsviol, SCIPfeastol(scip)) || SCIPisGT(scip, consdata->rhsviol, SCIPfeastol(scip)) )
6928 SCIPinfoMessage(scip, NULL, "violation: left hand side is violated by %.15g\n", consdata->lhsviol);
6932 SCIPinfoMessage(scip, NULL, "violation: right hand side is violated by %.15g\n", consdata->rhsviol);
6942 /* do not try to shift linear variables if activity is at infinity (leads to setting variable to infinity in solution, which is not allowed) */
6952 if( !(consdata->mayincreasez && consdata->zcoef > 0.0) && !(consdata->maydecreasez && consdata->zcoef < 0.0) )
6960 if( !(consdata->mayincreasez && consdata->zcoef < 0.0) && !(consdata->maydecreasez && consdata->zcoef > 0.0) )
6978 if( *result == SCIP_INFEASIBLE && conshdlrdata->subnlpheur != NULL && sol != NULL && !SCIPisInfinity(scip, maxviol) )
7144 SCIPdebugMsg(scip, "activate %scons <%s>\n", SCIPconsIsTransformed(cons) ? "transformed " : "", SCIPconsGetName(cons));
7147 SCIP_CALL( SCIPexprgraphAddExprtreeSum(conshdlrdata->exprgraph, 1, &consdata->f, NULL, &consdata->exprgraphnode, &exprtreeisnew) );
7150 /* mark that variables in constraint should not be multiaggregated (bad for bound tightening and branching) */
7187 SCIPdebugMsg(scip, "deactivate %scons <%s>\n", SCIPconsIsTransformed(cons) ? "transformed " : "", SCIPconsGetName(cons));
7215 SCIPdebugMsg(scip, "enable %scons <%s>\n", SCIPconsIsTransformed(cons) ? "transformed " : "", SCIPconsGetName(cons));
7246 SCIPdebugMsg(scip, "disable %scons <%s>\n", SCIPconsIsTransformed(cons) ? "transformed " : "", SCIPconsGetName(cons));
7344 SCIP_CALL( SCIPgetVarCopy(sourcescip, scip, consdata->z, &z, varmap, consmap, global, valid) );
7352 SCIP_CALL( SCIPgetVarCopy(sourcescip, scip, SCIPexprtreeGetVars(consdata->f)[0], &xy[0], varmap, consmap, global, valid) );
7358 SCIP_CALL( SCIPgetVarCopy(sourcescip, scip, SCIPexprtreeGetVars(consdata->f)[1], &xy[1], varmap, consmap, global, valid) );
7374 initial, separate, enforce, check, propagate, local, modifiable, dynamic, removable, stickingatnode) );
7410 /** constraint method of constraint handler which returns the number of variables (if possible) */
7506 x, y, z, coefxx, coefx, coefyy, coefy, coefxy, zcoef, SCIPgetLhsQuadratic(scip, cons), SCIPgetRhsQuadratic(scip, cons)) );
7529 /* check if we find at least one bilinear term for which we would create a bivariate constraint
7530 * thus, we search for a variable that has a square term and is involved in at least one bivariate term */
7564 /* require enough space here already, so we do not create and add aux vars that we cannot get rid of easily later */
7571 /* initial remaining quadratic constraint: take linear part and constraint sides from original constraint */
7573 SCIPgetNLinearVarsQuadratic(scip, cons), SCIPgetLinearVarsQuadratic(scip, cons), SCIPgetCoefsLinearVarsQuadratic(scip, cons),
7581 /* remember for each quadratic variable whether its linear and square part has been moved into a bivariate constraint */
7587 /* check for each bilinear term, whether we want to create a bivariate constraint for it and associated square terms */
7650 /* need to enforce new constraints, as relation auxvar = f(x,y) is not redundant, even if original constraint is */
7663 SCIP_CALL( SCIPdebugAddSolVal(scip, auxvar, coefxx * xval * xval + coefyy * yval * yval + coefxy * xval * yval + coefx * xval + coefy * yval) );
7680 /* complete quadcons: check for unmarked quadvarterms and add their linear and square coefficients to quadcons */
7689 * if the variable appears in a bilinear term, then this term should have been added to quadcons above, so the variable is there
7702 SCIP_CALL( SCIPaddQuadVarQuadratic(scip, quadcons, x, quadvarterms[i].lincoef, quadvarterms[i].sqrcoef) );
7729 SCIPgetNLinearVarsQuadratic(scip, cons), SCIPgetLinearVarsQuadratic(scip, cons), SCIPgetCoefsLinearVarsQuadratic(scip, cons),
7755 {
7773 /* could also upgrade bivariate quadratic, but if we don't then node will appear in cons_quadratic later, from which we also upgrade...
7782 /* we are only interested in monomials that are not convex or concave, since cons_nonlinear can handle these the same was as we do */
7789 /* @todo we could also do some more complex reformulation for n-variate monomials, something better than what reformMonomial in cons_nonlinear is doing */
7801 /* so far only support variables as arguments @todo could allow more here, e.g., f(x)^pg(y)^q */
7811 if( SCIPisNegative(scip, SCIPvarGetLbGlobal(x)) || SCIPisNegative(scip, SCIPvarGetLbGlobal(y)) )
7818 SCIP_CALL( SCIPcreateVar(scip, &auxvar, name, SCIPexprgraphGetNodeBounds(node).inf, SCIPexprgraphGetNodeBounds(node).sup,
7824 SCIPexprGetMonomialCoef(monomial), expx, expy, -1.0, -SCIPexprgraphGetNodePolynomialConstant(node), -SCIPexprgraphGetNodePolynomialConstant(node)) );
7888 SCIP_CALL( SCIPsetConshdlrPresol(scip, conshdlr, consPresolBivariate, CONSHDLR_MAXPREROUNDS, CONSHDLR_PRESOLTIMING) );
7890 SCIP_CALL( SCIPsetConshdlrProp(scip, conshdlr, consPropBivariate, CONSHDLR_PROPFREQ, CONSHDLR_DELAYPROP,
7892 SCIP_CALL( SCIPsetConshdlrSepa(scip, conshdlr, consSepalpBivariate, consSepasolBivariate, CONSHDLR_SEPAFREQ,
7898 SCIP_CALL( SCIPincludeQuadconsUpgrade(scip, quadconsUpgdBivariate, QUADCONSUPGD_PRIORITY, FALSE, CONSHDLR_NAME) );
7901 SCIP_CALL( SCIPincludeNonlinconsUpgrade(scip, NULL, exprgraphnodeReformBivariate, NONLINCONSUPGD_PRIORITY, FALSE, CONSHDLR_NAME) );
7905 "maximal coef range of a cut (maximal coefficient divided by minimal coefficient) in order to be added to LP relaxation",
7909 "whether to try to make solutions in check function feasible by shifting a linear variable (esp. useful if constraint was actually objective function)",
7913 "limit on number of propagation rounds for a single constraint within one round of SCIP propagation",
7917 "number of reference points in each direction where to compute linear support for envelope in LP initialization",
7925 SCIP_CALL( SCIPincludeEventhdlrBasic(scip, &(conshdlrdata->linvareventhdlr), CONSHDLR_NAME"_boundchange", "signals a bound tightening in a linear variable to a bivariate constraint",
7930 SCIP_CALL( SCIPincludeEventhdlrBasic(scip, &(conshdlrdata->nonlinvareventhdlr), CONSHDLR_NAME"_boundchange2", "signals a bound change in a nonlinear variable to the bivariate constraint handler",
7934 SCIP_CALL( SCIPincludeEventhdlrBasic(scip, NULL, CONSHDLR_NAME"_newsolution", "handles the event that a new primal solution has been found",
7953 * @note the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()
7983 SCIP_Bool removable, /**< should the relaxation be removed from the LP due to aging or cleanup?
7985 SCIP_Bool stickingatnode /**< should the constraint always be kept at the node where it was added, even
8025 SCIP_CALL( SCIPcreateCons(scip, cons, name, conshdlr, consdata, initial, separate, enforce, check, propagate,
8032 * in its most basic version, i. e., all constraint flags are set to their basic value as explained for the
8033 * method SCIPcreateConsBivariate(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h
8037 * @note the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()
8059 /** gets the linear variable of a bivariate constraint, or NULL if no such variable */ /*lint -e{715}*/
SCIP_RETCODE SCIPupdateStartpointHeurSubNlp(SCIP *scip, SCIP_HEUR *heur, SCIP_SOL *solcand, SCIP_Real violation)
Definition: heur_subnlp.c:2502
static SCIP_DECL_CONSENFOLP(consEnfolpBivariate)
Definition: cons_bivariate.c:6793
SCIP_Bool SCIPisEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:438
void SCIPintervalDivScalar(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_Real operand2)
Definition: intervalarith.c:1130
SCIP_Real SCIPexprgraphGetNodeVal(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13355
static SCIP_RETCODE createExprtreeFromMonomial(SCIP *scip, SCIP_VAR *x, SCIP_VAR *y, SCIP_Real coef, SCIP_Real p, SCIP_Real q, SCIP_EXPRTREE **exprtree, SCIP_Real *mult, SCIP_BIVAR_CONVEXITY *convextype)
Definition: cons_bivariate.c:5772
SCIP_RETCODE SCIPexprgraphPropagateVarBounds(SCIP_EXPRGRAPH *exprgraph, SCIP_Real infinity, SCIP_Bool clearreverseprop, SCIP_Bool *domainerror)
Definition: expr.c:15861
SCIP_Bool SCIPisRelEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:1149
SCIP_RETCODE SCIPexprgraphReplaceVarByLinearSum(SCIP_EXPRGRAPH *exprgraph, void *var, int ncoefs, SCIP_Real *coefs, void **vars, SCIP_Real constant)
Definition: expr.c:15542
Definition: type_result.h:33
static SCIP_RETCODE catchLinearVarEvents(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:198
Definition: type_result.h:37
static SCIP_RETCODE computeViolation(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS *cons, SCIP_SOL *sol)
Definition: cons_bivariate.c:781
SCIP_RETCODE SCIPcreateChild(SCIP *scip, SCIP_NODE **node, SCIP_Real nodeselprio, SCIP_Real estimate)
Definition: scip_branch.c:1008
static SCIP_RETCODE generateConvexConcaveEstimator(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons, SCIP_Real xyref[2], SCIP_SIDETYPE violside, SCIP_ROW **row)
Definition: cons_bivariate.c:3344
void SCIPexprgraphSetVarNodeValue(SCIP_EXPRGRAPHNODE *varnode, SCIP_Real value)
Definition: expr.c:14997
SCIP_RETCODE SCIPheurPassSolTrySol(SCIP *scip, SCIP_HEUR *heur, SCIP_SOL *sol)
Definition: heur_trysol.c:243
SCIP_RETCODE SCIPsetConshdlrTrans(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSTRANS((*constrans)))
Definition: scip_cons.c:586
SCIP_RETCODE SCIPexprSubstituteVars(BMS_BLKMEM *blkmem, SCIP_EXPR *expr, SCIP_EXPR **substexprs)
Definition: expr.c:8147
SCIP_Bool SCIPintervalIsEmpty(SCIP_Real infinity, SCIP_INTERVAL operand)
Definition: intervalarith.c:452
SCIP_Real SCIPgetLinearCoefBivariate(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:8073
primal heuristic that tries a given solution
SCIP_EXPORT SCIP_RETCODE SCIPexprintNewParametrization(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree)
Definition: exprinterpret_cppad.cpp:2279
SCIP_RETCODE SCIPaddExternBranchCand(SCIP *scip, SCIP_VAR *var, SCIP_Real score, SCIP_Real solval)
Definition: scip_branch.c:656
SCIP_CONSHDLR * SCIPfindConshdlr(SCIP *scip, const char *name)
Definition: scip_cons.c:877
static SCIP_DECL_CONSPRESOL(consPresolBivariate)
Definition: cons_bivariate.c:7006
Definition: intervalarith.h:37
public methods for SCIP parameter handling
static SCIP_DECL_QUADCONSUPGD(quadconsUpgdBivariate)
Definition: cons_bivariate.c:7427
static SCIP_RETCODE initSepaData(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons)
Definition: cons_bivariate.c:1061
SCIP_RETCODE SCIPexprgraphAddVars(SCIP_EXPRGRAPH *exprgraph, int nvars, void **vars, SCIP_EXPRGRAPHNODE **varnodes)
Definition: expr.c:15281
methods to interpret (evaluate) an expression tree "fast"
static SCIP_RETCODE registerLargeRelaxValueVariableForBranching(SCIP *scip, SCIP_CONS **conss, int nconss, SCIP_SOL *sol, SCIP_VAR **brvar)
Definition: cons_bivariate.c:4929
void SCIPexprtreePrint(SCIP_EXPRTREE *tree, SCIP_MESSAGEHDLR *messagehdlr, FILE *file, const char **varnames, const char **paramnames)
Definition: expr.c:8758
public methods for branch and bound tree
SCIP_RETCODE SCIPwriteVarName(SCIP *scip, FILE *file, SCIP_VAR *var, SCIP_Bool type)
Definition: scip_var.c:221
SCIP_RETCODE SCIPsetConshdlrExitsol(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSEXITSOL((*consexitsol)))
Definition: scip_cons.c:453
SCIP_Bool SCIPisGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:490
Definition: struct_scip.h:59
SCIP_RETCODE SCIPtightenVarLb(SCIP *scip, SCIP_VAR *var, SCIP_Real newbound, SCIP_Bool force, SCIP_Bool *infeasible, SCIP_Bool *tightened)
Definition: scip_var.c:5184
SCIP_RETCODE SCIPcreateCons(SCIP *scip, SCIP_CONS **cons, const char *name, SCIP_CONSHDLR *conshdlr, SCIP_CONSDATA *consdata, 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)
Definition: scip_cons.c:934
static SCIP_DECL_EXPRGRAPHNODEREFORM(exprgraphnodeReformBivariate)
Definition: cons_bivariate.c:7755
static SCIP_RETCODE generateOverestimatingHyperplaneCut(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons, SCIP_Real *x0y0, SCIP_ROW **row)
Definition: cons_bivariate.c:1774
SCIP_BILINTERM * SCIPgetBilinTermsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15112
SCIP_EXPORT int SCIPvarGetNLocksUpType(SCIP_VAR *var, SCIP_LOCKTYPE locktype)
Definition: var.c:3250
public methods for memory management
SCIP_RETCODE SCIPsetConshdlrEnforelax(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSENFORELAX((*consenforelax)))
Definition: scip_cons.c:308
static SCIP_RETCODE propagateBoundsCons(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS *cons, SCIP_RESULT *result, int *nchgbds, SCIP_Bool *redundant)
Definition: cons_bivariate.c:5186
int SCIPexprgraphGetNodeNChildren(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:12991
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)
Definition: cons_bivariate.c:8040
SCIP_RETCODE SCIPmarkConsPropagate(SCIP *scip, SCIP_CONS *cons)
Definition: scip_cons.c:1951
SCIP_RETCODE SCIPincludeConshdlrBasic(SCIP *scip, SCIP_CONSHDLR **conshdlrptr, const char *name, const char *desc, int enfopriority, int chckpriority, int eagerfreq, SCIP_Bool needscons, SCIP_DECL_CONSENFOLP((*consenfolp)), SCIP_DECL_CONSENFOPS((*consenfops)), SCIP_DECL_CONSCHECK((*conscheck)), SCIP_DECL_CONSLOCK((*conslock)), SCIP_CONSHDLRDATA *conshdlrdata)
Definition: scip_cons.c:166
SCIP_RETCODE SCIPaddVarLocksType(SCIP *scip, SCIP_VAR *var, SCIP_LOCKTYPE locktype, int nlocksdown, int nlocksup)
Definition: scip_var.c:4263
static SCIP_RETCODE dropLinearVarEvents(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:251
SCIP_RETCODE SCIPsetConshdlrActive(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSACTIVE((*consactive)))
Definition: scip_cons.c:655
static SCIP_RETCODE removeFixedNonlinearVariables(SCIP *scip, SCIP_CONSHDLR *conshdlr)
Definition: cons_bivariate.c:705
SCIP_RETCODE SCIPgetTransformedVars(SCIP *scip, int nvars, SCIP_VAR **vars, SCIP_VAR **transvars)
Definition: scip_var.c:1484
SCIP_EVENTHDLR * SCIPfindEventhdlr(SCIP *scip, const char *name)
Definition: scip_event.c:225
SCIP_RETCODE SCIPcreateNlRow(SCIP *scip, SCIP_NLROW **nlrow, const char *name, SCIP_Real constant, int nlinvars, SCIP_VAR **linvars, SCIP_Real *lincoefs, int nquadvars, SCIP_VAR **quadvars, int nquadelems, SCIP_QUADELEM *quadelems, SCIP_EXPRTREE *expression, SCIP_Real lhs, SCIP_Real rhs, SCIP_EXPRCURV curvature)
Definition: scip_nlp.c:1194
void SCIPwarningMessage(SCIP *scip, const char *formatstr,...)
Definition: scip_message.c:123
Definition: type_result.h:49
SCIP_RETCODE SCIPsetConshdlrGetVars(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSGETVARS((*consgetvars)))
Definition: scip_cons.c:816
SCIP_RETCODE SCIPaddSquareCoefQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real coef)
Definition: cons_quadratic.c:14840
type definitions for expression interpreter
SCIP_Real SCIPgetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var)
Definition: scip_sol.c:1353
SCIP_RETCODE SCIPtightenVarUb(SCIP *scip, SCIP_VAR *var, SCIP_Real newbound, SCIP_Bool force, SCIP_Bool *infeasible, SCIP_Bool *tightened)
Definition: scip_var.c:5301
SCIP_RETCODE SCIPcheckCurvatureQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15191
SCIP_RETCODE SCIPprintRow(SCIP *scip, SCIP_ROW *row, FILE *file)
Definition: scip_lp.c:2152
static SCIP_RETCODE computeViolations(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS **conss, int nconss, SCIP_SOL *sol, SCIP_CONS **maxviolcon)
Definition: cons_bivariate.c:913
SCIP_RETCODE SCIPexprCreateMonomial(BMS_BLKMEM *blkmem, SCIP_EXPRDATA_MONOMIAL **monomial, SCIP_Real coef, int nfactors, int *childidxs, SCIP_Real *exponents)
Definition: expr.c:7037
void SCIPexprgraphSetVarNodeBounds(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *varnode, SCIP_INTERVAL varbounds)
Definition: expr.c:15041
static SCIP_RETCODE separatePoint(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS **conss, int nconss, int nusefulconss, SCIP_SOL *sol, SCIP_Real minefficacy, SCIP_Bool inenforcement, SCIP_RESULT *result, SCIP_Real *bestefficacy)
Definition: cons_bivariate.c:4627
SCIP_RETCODE SCIPsetConshdlrPrint(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSPRINT((*consprint)))
Definition: scip_cons.c:770
Definition: struct_var.h:198
static SCIP_DECL_CONSHDLRCOPY(conshdlrCopyBivariate)
Definition: cons_bivariate.c:6138
Definition: cons_quadratic.h:104
Definition: type_message.h:45
void SCIPverbMessage(SCIP *scip, SCIP_VERBLEVEL msgverblevel, FILE *file, const char *formatstr,...)
Definition: scip_message.c:216
void SCIPexprgraphPropagateNodeBounds(SCIP_EXPRGRAPH *exprgraph, SCIP_Real infinity, SCIP_Real minstrength, SCIP_Bool *cutoff)
Definition: expr.c:15915
SCIP_RETCODE SCIPcreateEmptyRowCons(SCIP *scip, SCIP_ROW **row, SCIP_CONS *cons, const char *name, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool removable)
Definition: scip_lp.c:1368
SCIP_Real SCIPgetLhsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15125
SCIP_EXPRGRAPHNODE ** SCIPexprgraphGetVarNodes(SCIP_EXPRGRAPH *exprgraph)
Definition: expr.c:14987
SCIP_QUADVARTERM * SCIPgetQuadVarTermsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15047
SCIP_Real SCIPgetRhsBivariate(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:8109
SCIP_RETCODE SCIPdelConsLocal(SCIP *scip, SCIP_CONS *cons)
Definition: scip_prob.c:3468
SCIP_EXPORT SCIP_RETCODE SCIPexprintGrad(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree, SCIP_Real *varvals, SCIP_Bool new_varvals, SCIP_Real *val, SCIP_Real *gradient)
Definition: exprinterpret_cppad.cpp:2432
SCIP_RETCODE SCIPexprtreeCopy(BMS_BLKMEM *blkmem, SCIP_EXPRTREE **targettree, SCIP_EXPRTREE *sourcetree)
Definition: expr.c:8814
SCIP_Real SCIPgetLhsBivariate(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:8097
SCIP_INTERVAL SCIPexprgraphGetNodeBounds(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13345
SCIP_RETCODE SCIPsetConshdlrDelete(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSDELETE((*consdelete)))
Definition: scip_cons.c:563
void SCIPexprReindexVars(SCIP_EXPR *expr, int *newindices)
Definition: expr.c:8185
void SCIPintervalSetBounds(SCIP_INTERVAL *resultant, SCIP_Real inf, SCIP_Real sup)
Definition: intervalarith.c:427
SCIP_Bool SCIPisFeasLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:799
static SCIP_RETCODE solveDerivativeEquation(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real targetvalue, SCIP_Real lb, SCIP_Real ub, SCIP_Real *val, SCIP_Bool *success)
Definition: cons_bivariate.c:1291
public methods for problem variables
static SCIP_DECL_CONSGETNVARS(consGetNVarsBivariate)
Definition: cons_bivariate.c:7413
SCIP_RETCODE SCIPaddBoolParam(SCIP *scip, const char *name, const char *desc, SCIP_Bool *valueptr, SCIP_Bool isadvanced, SCIP_Bool defaultvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:48
Definition: type_expr.h:100
Definition: type_lp.h:55
Definition: type_expr.h:40
SCIP_Bool SCIPintervalIsNegativeInfinity(SCIP_Real infinity, SCIP_INTERVAL operand)
Definition: intervalarith.c:494
Definition: type_result.h:40
SCIP_RETCODE SCIPexprgraphAddExprtreeSum(SCIP_EXPRGRAPH *exprgraph, int nexprtrees, SCIP_EXPRTREE **exprtrees, SCIP_Real *coefs, SCIP_EXPRGRAPHNODE **rootnode, SCIP_Bool *rootnodeisnew)
Definition: expr.c:15401
SCIP_RETCODE SCIPsetConshdlrPresol(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSPRESOL((*conspresol)), int maxprerounds, SCIP_PRESOLTIMING presoltiming)
Definition: scip_cons.c:525
static SCIP_RETCODE createConsFromMonomial(SCIP *scip, SCIP_CONS *srccons, SCIP_CONS **cons, const char *name, SCIP_VAR *x, SCIP_VAR *y, SCIP_VAR *z, SCIP_Real coef, SCIP_Real p, SCIP_Real q, SCIP_Real zcoef, SCIP_Real lhs, SCIP_Real rhs)
Definition: cons_bivariate.c:5889
static SCIP_DECL_CONSACTIVE(consActiveBivariate)
Definition: cons_bivariate.c:7126
SCIP_RETCODE SCIPexprtreeCreate(BMS_BLKMEM *blkmem, SCIP_EXPRTREE **tree, SCIP_EXPR *root, int nvars, int nparams, SCIP_Real *params)
Definition: expr.c:8773
static SCIP_RETCODE generate1ConvexIndefiniteUnderestimatorAtBoundary(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real xyref[2], SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:3601
static SCIP_RETCODE generateOrthogonal_lx_ly_Underestimator(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real *xyref, SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:2058
SCIP_RETCODE SCIPsetConshdlrInit(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSINIT((*consinit)))
Definition: scip_cons.c:381
static SCIP_RETCODE createConsFromQuadTerm(SCIP *scip, SCIP_CONS *srccons, SCIP_CONS **cons, const char *name, SCIP_VAR *x, SCIP_VAR *y, SCIP_VAR *z, SCIP_Real coefxx, SCIP_Real coefx, SCIP_Real coefyy, SCIP_Real coefy, SCIP_Real coefxy, SCIP_Real coefz, SCIP_Real lhs, SCIP_Real rhs)
Definition: cons_bivariate.c:5606
SCIP_RETCODE SCIPsetConsEnforced(SCIP *scip, SCIP_CONS *cons, SCIP_Bool enforce)
Definition: scip_cons.c:1258
SCIP_RETCODE SCIPsetConshdlrGetNVars(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSGETNVARS((*consgetnvars)))
Definition: scip_cons.c:839
void SCIPexprtreeSetParamVal(SCIP_EXPRTREE *tree, int paramidx, SCIP_Real paramval)
Definition: expr.c:8644
public methods for SCIP variables
SCIP_RETCODE SCIPsetConshdlrExitpre(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSEXITPRE((*consexitpre)))
Definition: scip_cons.c:501
SCIP_RETCODE SCIPfindQuadVarTermQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, int *pos)
Definition: cons_quadratic.c:15078
SCIP_Real SCIPgetRowSolFeasibility(SCIP *scip, SCIP_ROW *row, SCIP_SOL *sol)
Definition: scip_lp.c:2107
public methods for separator plugins
SCIP_EXPRTREE * SCIPgetExprtreeBivariate(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:8085
SCIP_RETCODE SCIPlockVarCons(SCIP *scip, SCIP_VAR *var, SCIP_CONS *cons, SCIP_Bool lockdown, SCIP_Bool lockup)
Definition: scip_var.c:4354
Definition: type_expr.h:46
int SCIPgetNQuadVarTermsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15032
Definition: struct_tree.h:132
int SCIPexprgraphGetNodePolynomialNMonomials(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13214
SCIP_RETCODE SCIPsetConshdlrFree(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSFREE((*consfree)))
Definition: scip_cons.c:357
public methods for numerical tolerances
SCIP_RETCODE SCIPaddQuadVarQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real lincoef, SCIP_Real sqrcoef)
Definition: cons_quadratic.c:14757
void SCIPupdateSolConsViolation(SCIP *scip, SCIP_SOL *sol, SCIP_Real absviol, SCIP_Real relviol)
Definition: scip_sol.c:265
static SCIP_RETCODE registerBranchingVariables(SCIP *scip, SCIP_CONS **conss, int nconss, int *nnotify)
Definition: cons_bivariate.c:4818
public methods for expressions, expression trees, expression graphs, and related stuff ...
SCIP_Bool SCIPintervalIsPositiveInfinity(SCIP_Real infinity, SCIP_INTERVAL operand)
Definition: intervalarith.c:485
int SCIPexprGetMonomialNFactors(SCIP_EXPRDATA_MONOMIAL *monomial)
Definition: expr.c:5912
public methods for querying solving statistics
Definition: struct_sol.h:64
SCIP_Bool SCIPisLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:464
static SCIP_DECL_CONSENFORELAX(consEnforelaxBivariate)
Definition: cons_bivariate.c:6802
public methods for the branch-and-bound tree
SCIP_RETCODE SCIPgetVarCopy(SCIP *sourcescip, SCIP *targetscip, SCIP_VAR *sourcevar, SCIP_VAR **targetvar, SCIP_HASHMAP *varmap, SCIP_HASHMAP *consmap, SCIP_Bool global, SCIP_Bool *success)
Definition: scip_copy.c:697
SCIP_RETCODE SCIPaddQuadVarLinearCoefQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real coef)
Definition: cons_quadratic.c:14787
SCIP_EVENTHDLRDATA * SCIPeventhdlrGetData(SCIP_EVENTHDLR *eventhdlr)
Definition: event.c:325
SCIP_EXPROP SCIPexprgraphGetNodeOperator(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13051
SCIP_EXPRDATA_MONOMIAL ** SCIPexprgraphGetNodePolynomialMonomials(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13202
SCIP_RETCODE SCIPexprgraphCreate(BMS_BLKMEM *blkmem, SCIP_EXPRGRAPH **exprgraph, int varssizeinit, int depthinit, SCIP_DECL_EXPRGRAPHVARADDED((*exprgraphvaradded)), SCIP_DECL_EXPRGRAPHVARREMOVE((*exprgraphvarremove)), SCIP_DECL_EXPRGRAPHVARCHGIDX((*exprgraphvarchgidx)), void *userdata)
Definition: expr.c:15109
Definition: type_expr.h:47
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)
Definition: cons_bivariate.c:7956
Definition: type_expr.h:49
Definition: cons_bivariate.h:77
SCIP_RETCODE SCIPcreateSolCopy(SCIP *scip, SCIP_SOL **sol, SCIP_SOL *sourcesol)
Definition: scip_sol.c:610
SCIP_RETCODE SCIPreleaseNlRow(SCIP *scip, SCIP_NLROW **nlrow)
Definition: scip_nlp.c:1302
SCIP_RETCODE SCIPmarkDoNotMultaggrVar(SCIP *scip, SCIP_VAR *var)
Definition: scip_var.c:8648
public methods for managing constraints
SCIP_RETCODE SCIPgetProbvarLinearSum(SCIP *scip, SCIP_VAR **vars, SCIP_Real *scalars, int *nvars, int varssize, SCIP_Real *constant, int *requiredsize, SCIP_Bool mergemultiples)
Definition: scip_var.c:1742
SCIP_Real SCIPexprgraphGetNodePolynomialConstant(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13226
SCIP_RETCODE SCIPsetConshdlrExit(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSEXIT((*consexit)))
Definition: scip_cons.c:405
SCIP_EXPRCURV SCIPexprgraphGetNodeCurvature(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13365
SCIP_RETCODE SCIPexprCreateQuadratic(BMS_BLKMEM *blkmem, SCIP_EXPR **expr, int nchildren, SCIP_EXPR **children, SCIP_Real constant, SCIP_Real *lincoefs, int nquadelems, SCIP_QUADELEM *quadelems)
Definition: expr.c:6586
Definition: type_result.h:35
Definition: struct_cons.h:37
SCIP_RETCODE SCIPcreateRowCons(SCIP *scip, SCIP_ROW **row, SCIP_CONS *cons, const char *name, int len, SCIP_COL **cols, SCIP_Real *vals, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool removable)
Definition: scip_lp.c:1205
interval arithmetics for provable bounds
SCIP_Bool SCIPisConvexQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15205
SCIP_RETCODE SCIPincSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var, SCIP_Real incval)
Definition: scip_sol.c:1310
Definition: struct_cons.h:117
static SCIP_RETCODE unlockLinearVariable(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real coef)
Definition: cons_bivariate.c:445
static SCIP_DECL_CONSINITSOL(consInitsolBivariate)
Definition: cons_bivariate.c:6295
public methods for event handler plugins and event handlers
SCIP_Real SCIPintervalGetInf(SCIP_INTERVAL interval)
Definition: intervalarith.c:399
SCIP_Bool SCIPisFeasEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:773
static SCIP_RETCODE proposeFeasibleSolution(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS **conss, int nconss, SCIP_SOL *sol, SCIP_Bool *success)
Definition: cons_bivariate.c:5447
SCIP_RETCODE SCIPcatchEvent(SCIP *scip, SCIP_EVENTTYPE eventtype, SCIP_EVENTHDLR *eventhdlr, SCIP_EVENTDATA *eventdata, int *filterpos)
Definition: scip_event.c:277
SCIP_RETCODE SCIPexprtreePrintWithNames(SCIP_EXPRTREE *tree, SCIP_MESSAGEHDLR *messagehdlr, FILE *file)
Definition: nlp.c:174
SCIP_RETCODE SCIPexprCopyDeep(BMS_BLKMEM *blkmem, SCIP_EXPR **targetexpr, SCIP_EXPR *sourceexpr)
Definition: expr.c:6143
SCIP_RETCODE SCIPsetConshdlrInitsol(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSINITSOL((*consinitsol)))
Definition: scip_cons.c:429
SCIP_RETCODE SCIPsetConshdlrDisable(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSDISABLE((*consdisable)))
Definition: scip_cons.c:724
SCIP_RETCODE SCIPgetTransformedVar(SCIP *scip, SCIP_VAR *var, SCIP_VAR **transvar)
Definition: scip_var.c:1443
Definition: type_result.h:36
public methods for expression handlers
static SCIP_DECL_CONSDELETE(consDeleteBivariate)
Definition: cons_bivariate.c:6460
static SCIP_DECL_EXPRGRAPHVARADDED(exprgraphVarAdded)
Definition: cons_bivariate.c:350
constraint handler for quadratic constraints
static SCIP_DECL_CONSENFOPS(consEnfopsBivariate)
Definition: cons_bivariate.c:6812
SCIP_EXPORT SCIP_RETCODE SCIPexprintFree(SCIP_EXPRINT **exprint)
Definition: exprinterpret_cppad.cpp:2177
static SCIP_RETCODE propagateBounds(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS **conss, int nconss, SCIP_RESULT *result, int *nchgbds, int *ndelconss)
Definition: cons_bivariate.c:5302
Definition: type_retcode.h:33
public methods for problem copies
public methods for primal CIP solutions
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)
Definition: cons_nonlinear.c:9462
SCIP_RETCODE SCIPsetConshdlrInitpre(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSINITPRE((*consinitpre)))
Definition: scip_cons.c:477
static SCIP_DECL_EXPRGRAPHVARREMOVE(exprgraphVarRemove)
Definition: cons_bivariate.c:388
SCIP_RETCODE SCIPaddBilinTermQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var1, SCIP_VAR *var2, SCIP_Real coef)
Definition: cons_quadratic.c:14897
SCIP_RETCODE SCIPexprCreatePolynomial(BMS_BLKMEM *blkmem, SCIP_EXPR **expr, int nchildren, SCIP_EXPR **children, int nmonomials, SCIP_EXPRDATA_MONOMIAL **monomials, SCIP_Real constant, SCIP_Bool copymonomials)
Definition: expr.c:6634
static SCIP_RETCODE lockLinearVariable(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real coef)
Definition: cons_bivariate.c:414
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)
Definition: cons_quadratic.c:14610
Definition: type_result.h:42
SCIP_RETCODE SCIPincludeQuadconsUpgrade(SCIP *scip, SCIP_DECL_QUADCONSUPGD((*quadconsupgd)), int priority, SCIP_Bool active, const char *conshdlrname)
Definition: cons_quadratic.c:14321
void SCIPintervalSet(SCIP_INTERVAL *resultant, SCIP_Real value)
Definition: intervalarith.c:415
void SCIPexprgraphTightenNodeBounds(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *node, SCIP_INTERVAL nodebounds, SCIP_Real minstrength, SCIP_Real infinity, SCIP_Bool *cutoff)
Definition: expr.c:14724
static SCIP_RETCODE freeSepaData(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:1217
static SCIP_RETCODE enforceConstraint(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS **conss, int nconss, int nusefulconss, SCIP_SOL *sol, SCIP_Bool solinfeasible, SCIP_RESULT *result)
Definition: cons_bivariate.c:5962
Definition: cons_bivariate.h:79
SCIP_VAR ** SCIPgetLinearVarsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15003
Definition: struct_heur.h:88
SCIP_EXPORT SCIP_RETCODE SCIPexprintCreate(BMS_BLKMEM *blkmem, SCIP_EXPRINT **exprint)
Definition: exprinterpret_cppad.cpp:2160
public methods for primal heuristic plugins and divesets
public methods for constraint handler plugins and constraints
public methods for NLP management
Definition: type_retcode.h:34
static SCIP_DECL_CONSDEACTIVE(consDeactiveBivariate)
Definition: cons_bivariate.c:7170
Definition: struct_expr.h:46
static SCIP_DECL_EVENTEXEC(processLinearVarEvent)
Definition: cons_bivariate.c:178
static SCIP_DECL_CONSSEPALP(consSepalpBivariate)
Definition: cons_bivariate.c:6746
SCIP_RETCODE SCIPsetConshdlrSepa(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSSEPALP((*conssepalp)), SCIP_DECL_CONSSEPASOL((*conssepasol)), int sepafreq, int sepapriority, SCIP_Bool delaysepa)
Definition: scip_cons.c:220
public data structures and miscellaneous methods
static SCIP_RETCODE lifting(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real xval, SCIP_Real yval, SCIP_Real xlb, SCIP_Real xub, SCIP_Real ylb, SCIP_Real yub, int min_max, SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:3511
SCIP_RETCODE SCIPunlockVarCons(SCIP *scip, SCIP_VAR *var, SCIP_CONS *cons, SCIP_Bool lockdown, SCIP_Bool lockup)
Definition: scip_var.c:4439
Definition: type_expr.h:85
SCIP_EXPORT SCIP_RETCODE SCIPexprintEval(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree, SCIP_Real *varvals, SCIP_Real *val)
Definition: exprinterpret_cppad.cpp:2298
SCIP_RETCODE SCIPdropVarEvent(SCIP *scip, SCIP_VAR *var, SCIP_EVENTTYPE eventtype, SCIP_EVENTHDLR *eventhdlr, SCIP_EVENTDATA *eventdata, int filterpos)
Definition: scip_event.c:391
Definition: type_expr.h:39
SCIP_Bool SCIPisSumLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:685
void SCIPexprgraphSetVarNodeLb(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *varnode, SCIP_Real lb)
Definition: expr.c:15061
SCIP_RETCODE SCIPsetConshdlrCopy(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSHDLRCOPY((*conshdlrcopy)), SCIP_DECL_CONSCOPY((*conscopy)))
Definition: scip_cons.c:332
static SCIP_Bool isConvexLocal(SCIP *scip, SCIP_CONS *cons, SCIP_SIDETYPE side)
Definition: cons_bivariate.c:4526
SCIP_RETCODE SCIPexprtreeSetVars(SCIP_EXPRTREE *tree, int nvars, SCIP_VAR **vars)
Definition: nlp.c:113
SCIP_RETCODE SCIPprintCons(SCIP *scip, SCIP_CONS *cons, FILE *file)
Definition: scip_cons.c:2473
SCIP_EXPRINTDATA * SCIPexprtreeGetInterpreterData(SCIP_EXPRTREE *tree)
Definition: expr.c:8659
constraint handler for nonlinear constraints
static SCIP_DECL_CONSDISABLE(consDisableBivariate)
Definition: cons_bivariate.c:7229
SCIP_CONSHDLRDATA * SCIPconshdlrGetData(SCIP_CONSHDLR *conshdlr)
Definition: cons.c:4199
SCIP_RETCODE SCIPcreateLPSol(SCIP *scip, SCIP_SOL **sol, SCIP_HEUR *heur)
Definition: scip_sol.c:362
SCIP_Bool SCIPisCutApplicable(SCIP *scip, SCIP_ROW *cut)
Definition: scip_cut.c:178
Definition: struct_lp.h:192
SCIP_RETCODE SCIPcreateVar(SCIP *scip, SCIP_VAR **var, const char *name, SCIP_Real lb, SCIP_Real ub, SCIP_Real obj, SCIP_VARTYPE vartype, SCIP_Bool initial, SCIP_Bool removable, SCIP_DECL_VARDELORIG((*vardelorig)), SCIP_DECL_VARTRANS((*vartrans)), SCIP_DECL_VARDELTRANS((*vardeltrans)), SCIP_DECL_VARCOPY((*varcopy)), SCIP_VARDATA *vardata)
Definition: scip_var.c:105
methods for debugging
public methods for LP management
void SCIPexprgraphSetVarNodeUb(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *varnode, SCIP_Real ub)
Definition: expr.c:15081
Definition: cons_quadratic.h:121
SCIP_RETCODE SCIPexprCreate(BMS_BLKMEM *blkmem, SCIP_EXPR **expr, SCIP_EXPROP op,...)
Definition: expr.c:5975
public methods for cuts and aggregation rows
SCIP_RETCODE SCIPincludeConshdlrBivariate(SCIP *scip)
Definition: cons_bivariate.c:7853
Definition: type_set.h:41
static SCIP_RETCODE removeFixedVariables(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_CONS *cons, SCIP_Bool *ischanged, SCIP_Bool *isupgraded)
Definition: cons_bivariate.c:476
Definition: struct_expr.h:116
static SCIP_DECL_CONSEXITSOL(consExitsolBivariate)
Definition: cons_bivariate.c:6425
Definition: type_var.h:45
void SCIPintervalAdd(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_INTERVAL operand2)
Definition: intervalarith.c:625
SCIP_EXPORT SCIP_Real SCIPnodeGetEstimate(SCIP_NODE *node)
Definition: tree.c:7450
void SCIPexprgraphDisableNode(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:14598
SCIP_Real SCIPintervalGetSup(SCIP_INTERVAL interval)
Definition: intervalarith.c:407
SCIP_Bool SCIPintervalAreDisjoint(SCIP_INTERVAL operand1, SCIP_INTERVAL operand2)
Definition: intervalarith.c:522
static SCIP_DECL_CONSINITPRE(consInitpreBivariate)
Definition: cons_bivariate.c:6218
Definition: type_set.h:45
constraint handler for bivariate nonlinear constraints
Definition: struct_expr.h:89
SCIP_Bool SCIPisFeasGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:825
SCIP_EXPORT SCIP_RETCODE SCIPexprintHessianDense(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree, SCIP_Real *varvals, SCIP_Bool new_varvals, SCIP_Real *val, SCIP_Real *hessian)
Definition: exprinterpret_cppad.cpp:2602
SCIP_Real SCIPexprGetMonomialCoef(SCIP_EXPRDATA_MONOMIAL *monomial)
Definition: expr.c:5902
SCIP_RETCODE SCIPincludeEventhdlrBasic(SCIP *scip, SCIP_EVENTHDLR **eventhdlrptr, const char *name, const char *desc, SCIP_DECL_EVENTEXEC((*eventexec)), SCIP_EVENTHDLRDATA *eventhdlrdata)
Definition: scip_event.c:95
SCIP_RETCODE SCIPaddRealParam(SCIP *scip, const char *name, const char *desc, SCIP_Real *valueptr, SCIP_Bool isadvanced, SCIP_Real defaultvalue, SCIP_Real minvalue, SCIP_Real maxvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:130
SCIP_RETCODE SCIPunmarkConsPropagate(SCIP *scip, SCIP_CONS *cons)
Definition: scip_cons.c:1979
void * SCIPexprgraphGetNodeVar(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13083
public methods for the LP relaxation, rows and columns
SCIP_Bool SCIPisConcaveQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15238
static SCIP_DECL_CONSSEPASOL(consSepasolBivariate)
Definition: cons_bivariate.c:6770
SCIP_EXPORT int SCIPvarGetNLocksDownType(SCIP_VAR *var, SCIP_LOCKTYPE locktype)
Definition: var.c:3193
public methods for nonlinear relaxations
SCIP_RETCODE SCIPaddLinearVarQuadratic(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real coef)
Definition: cons_quadratic.c:14732
Definition: type_set.h:39
SCIP_RETCODE SCIPgetSolVals(SCIP *scip, SCIP_SOL *sol, int nvars, SCIP_VAR **vars, SCIP_Real *vals)
Definition: scip_sol.c:1390
Definition: cons_bivariate.h:76
public methods for branching rule plugins and branching
SCIP_RETCODE SCIPaddRow(SCIP *scip, SCIP_ROW *row, SCIP_Bool forcecut, SCIP_Bool *infeasible)
Definition: scip_cut.c:221
public methods for managing events
general public methods
SCIP_Bool SCIPisFeasGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:812
SCIP_RETCODE SCIPincludeNonlinconsUpgrade(SCIP *scip, SCIP_DECL_NONLINCONSUPGD((*nonlinconsupgd)), SCIP_DECL_EXPRGRAPHNODEREFORM((*nodereform)), int priority, SCIP_Bool active, const char *conshdlrname)
Definition: cons_nonlinear.c:9377
public methods for solutions
SCIP_RETCODE SCIPchgRowRhs(SCIP *scip, SCIP_ROW *row, SCIP_Real rhs)
Definition: scip_lp.c:1553
SCIP_RETCODE SCIPchgRowLhs(SCIP *scip, SCIP_ROW *row, SCIP_Real lhs)
Definition: scip_lp.c:1529
static SCIP_DECL_CONSINITLP(consInitlpBivariate)
Definition: cons_bivariate.c:6525
SCIP_RETCODE SCIPdropEvent(SCIP *scip, SCIP_EVENTTYPE eventtype, SCIP_EVENTHDLR *eventhdlr, SCIP_EVENTDATA *eventdata, int filterpos)
Definition: scip_event.c:311
int SCIPgetNLinearVarsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:14988
Definition: type_expr.h:86
public methods for the probing mode
SCIP_Bool SCIPisFeasLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:786
SCIP_RETCODE SCIPsetConshdlrDeactive(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSDEACTIVE((*consdeactive)))
Definition: scip_cons.c:678
SCIP_RETCODE SCIPaddVarToRow(SCIP *scip, SCIP_ROW *row, SCIP_VAR *var, SCIP_Real val)
Definition: scip_lp.c:1641
static SCIP_DECL_CONSGETVARS(consGetVarsBivariate)
Definition: cons_bivariate.c:7388
SCIP_CONS ** SCIPconshdlrGetConss(SCIP_CONSHDLR *conshdlr)
Definition: cons.c:4551
int SCIPgetNBilinTermsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15097
public methods for message output
NLP local search primal heuristic using sub-SCIPs.
SCIP_Real SCIPgetSolTransObj(SCIP *scip, SCIP_SOL *sol)
Definition: scip_sol.c:1483
SCIP_RETCODE SCIPexprgraphReleaseNode(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE **node)
Definition: expr.c:14452
Definition: type_var.h:84
SCIP_RETCODE SCIPaddIntParam(SCIP *scip, const char *name, const char *desc, int *valueptr, SCIP_Bool isadvanced, int defaultvalue, int minvalue, int maxvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:74
static SCIP_RETCODE generateEstimatingHyperplane(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Bool doover, SCIP_Real *x0y0, SCIP_Real *coefx, SCIP_Real *coefy, SCIP_Real *constant, SCIP_Bool *success)
Definition: cons_bivariate.c:1528
static SCIP_RETCODE generateOrthogonal_lx_uy_Underestimator(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real *xyref, SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:2451
static SCIP_RETCODE generateConvexConcaveUnderestimator(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_EXPRTREE *f_yfixed, SCIP_EXPRTREE *vred, SCIP_Real xyref[2], SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:2831
static SCIP_RETCODE propagateBoundsTightenVar(SCIP *scip, SCIP_VAR *var, SCIP_INTERVAL bounds, SCIP_CONS *cons, SCIP_RESULT *result, int *nchgbds)
Definition: cons_bivariate.c:5114
static SCIP_RETCODE generate1ConvexIndefiniteUnderestimatorInTheInteriorPatternB(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real xyref[2], SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:3991
void SCIPintervalMulScalar(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_Real operand2)
Definition: intervalarith.c:1050
Definition: type_lp.h:56
Definition: struct_nlp.h:63
SCIP_Real SCIPgetRhsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15138
SCIP_EXPORT SCIP_RETCODE SCIPexprintHessianSparsityDense(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree, SCIP_Real *varvals, SCIP_Bool *sparsity)
Definition: exprinterpret_cppad.cpp:2529
public methods for message handling
SCIP_Bool SCIPisGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:477
SCIP_EXPRGRAPHNODE ** SCIPexprgraphGetNodeChildren(SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:13001
SCIP_Real SCIPgetRowLPFeasibility(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1950
SCIP_Real * SCIPexprGetMonomialExponents(SCIP_EXPRDATA_MONOMIAL *monomial)
Definition: expr.c:5932
SCIP_RETCODE SCIPexprtreeSubstituteVars(SCIP_EXPRTREE *tree, SCIP_EXPR **substexprs)
Definition: expr.c:9047
Definition: type_retcode.h:45
static SCIP_DECL_CONSENABLE(consEnableBivariate)
Definition: cons_bivariate.c:7197
Definition: type_expr.h:75
static SCIP_RETCODE generate1ConvexIndefiniteUnderestimatorInTheInteriorPatternA(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real xyref[2], SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:3795
Definition: type_set.h:44
SCIP_RETCODE SCIPgetProbvarSum(SCIP *scip, SCIP_VAR **var, SCIP_Real *scalar, SCIP_Real *constant)
Definition: scip_var.c:1798
Definition: struct_expr.h:155
SCIP_RETCODE SCIPcatchVarEvent(SCIP *scip, SCIP_VAR *var, SCIP_EVENTTYPE eventtype, SCIP_EVENTHDLR *eventhdlr, SCIP_EVENTDATA *eventdata, int *filterpos)
Definition: scip_event.c:345
static SCIP_RETCODE generateCut(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons, SCIP_SOL *sol, SCIP_SIDETYPE violside, SCIP_Real cutmaxrange, SCIP_ROW **row)
Definition: cons_bivariate.c:4324
SCIP_RETCODE SCIPevalExprtreeLocalBounds(SCIP *scip, SCIP_EXPRTREE *tree, SCIP_Real infinity, SCIP_INTERVAL *val)
Definition: scip_expr.c:234
void SCIPintervalSub(SCIP_Real infinity, SCIP_INTERVAL *resultant, SCIP_INTERVAL operand1, SCIP_INTERVAL operand2)
Definition: intervalarith.c:732
Definition: type_result.h:45
static SCIP_RETCODE enforceViolatedFixedNonlinear(SCIP *scip, SCIP_CONS **conss, int nconss, SCIP_Bool *reduceddom, SCIP_Bool *infeasible)
Definition: cons_bivariate.c:4987
SCIP_Real * SCIPgetCoefsLinearVarsQuadratic(SCIP *scip, SCIP_CONS *cons)
Definition: cons_quadratic.c:15018
SCIP_VAR * SCIPgetLinearVarBivariate(SCIP *scip, SCIP_CONS *cons)
Definition: cons_bivariate.c:8061
Definition: type_result.h:46
static SCIP_RETCODE generateLinearizationCut(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons, SCIP_Real *x0y0, SCIP_Bool newxy, SCIP_ROW **row)
Definition: cons_bivariate.c:1452
Definition: struct_expr.h:55
static SCIP_RETCODE generate1ConvexIndefiniteUnderestimator(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_CONS *cons, SCIP_Real *xyref, SCIP_ROW **row)
Definition: cons_bivariate.c:4179
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)
Definition: cons_quadratic.c:14397
SCIP_Bool SCIPconsIsMarkedPropagate(SCIP_CONS *cons)
Definition: cons.c:8298
public methods for primal heuristics
SCIP_RETCODE SCIPaddVarsToRow(SCIP *scip, SCIP_ROW *row, int nvars, SCIP_VAR **vars, SCIP_Real *vals)
Definition: scip_lp.c:1667
void SCIPinfoMessage(SCIP *scip, FILE *file, const char *formatstr,...)
Definition: scip_message.c:199
Definition: type_retcode.h:43
SCIP_RETCODE SCIPreleaseCons(SCIP *scip, SCIP_CONS **cons)
Definition: scip_cons.c:1110
SCIP_RETCODE SCIPexprCreateLinear(BMS_BLKMEM *blkmem, SCIP_EXPR **expr, int nchildren, SCIP_EXPR **children, SCIP_Real *coefs, SCIP_Real constant)
Definition: expr.c:6504
static SCIP_RETCODE generateUnderestimatorParallelYFacets(SCIP *scip, SCIP_EXPRINT *exprinterpreter, SCIP_EXPRTREE *f, SCIP_Real *xyref, SCIP_Real cutcoeff[4], SCIP_Real *convenvvalue, SCIP_Bool *success)
Definition: cons_bivariate.c:1826
Definition: objbenders.h:33
SCIP_RETCODE SCIPsetConshdlrProp(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSPROP((*consprop)), int propfreq, SCIP_Bool delayprop, SCIP_PROPTIMING proptiming)
Definition: scip_cons.c:266
public methods for global and local (sub)problems
void SCIPmarkRowNotRemovableLocal(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1808
Definition: type_var.h:43
static SCIP_RETCODE initSepaDataCreateVred(SCIP *scip, SCIP_EXPRTREE **vred, SCIP_EXPRTREE *f)
Definition: cons_bivariate.c:961
SCIP_Real SCIPadjustedVarLb(SCIP *scip, SCIP_VAR *var, SCIP_Real lb)
Definition: scip_var.c:4614
SCIP_RETCODE SCIPexprtreeSetParams(SCIP_EXPRTREE *tree, int nparams, SCIP_Real *paramvals)
Definition: expr.c:8878
SCIP_RETCODE SCIPsetConshdlrEnable(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSENABLE((*consenable)))
Definition: scip_cons.c:701
static void perturb(SCIP_Real *val, SCIP_Real lb, SCIP_Real ub, SCIP_Real amount)
Definition: cons_bivariate.c:1266
#define SCIPduplicateBlockMemory(scip, ptr, source)
Definition: scip_mem.h:90
static SCIP_DECL_CONSEXITPRE(consExitpreBivariate)
Definition: cons_bivariate.c:6244
Definition: exprinterpret_cppad.cpp:311
Definition: type_result.h:39
Definition: struct_event.h:195
SCIP_RETCODE SCIPsetConshdlrInitlp(SCIP *scip, SCIP_CONSHDLR *conshdlr, SCIP_DECL_CONSINITLP((*consinitlp)))
Definition: scip_cons.c:609
SCIP_Bool SCIPintervalIsSubsetEQ(SCIP_Real infinity, SCIP_INTERVAL operand1, SCIP_INTERVAL operand2)
Definition: intervalarith.c:503
SCIP_EXPORT SCIP_RETCODE SCIPexprintCompile(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree)
Definition: exprinterpret_cppad.cpp:2190
SCIP_RETCODE SCIPexprtreeEval(SCIP_EXPRTREE *tree, SCIP_Real *varvals, SCIP_Real *val)
Definition: expr.c:8725
Definition: cons_bivariate.h:78
Definition: type_expr.h:48
SCIP_RETCODE SCIPsetConsChecked(SCIP *scip, SCIP_CONS *cons, SCIP_Bool check)
Definition: scip_cons.c:1283
Definition: type_expr.h:41
void SCIPexprgraphEnableNode(SCIP_EXPRGRAPH *exprgraph, SCIP_EXPRGRAPHNODE *node)
Definition: expr.c:14571
memory allocation routines
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)
Definition: cons_nonlinear.c:10109
Definition: type_var.h:58