Scippy

SCIP

Solving Constraint Integer Programs

branch_relpscost.c
Go to the documentation of this file.
1 /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
2 /* */
3 /* This file is part of the program and library */
4 /* SCIP --- Solving Constraint Integer Programs */
5 /* */
6 /* Copyright (c) 2002-2023 Zuse Institute Berlin (ZIB) */
7 /* */
8 /* Licensed under the Apache License, Version 2.0 (the "License"); */
9 /* you may not use this file except in compliance with the License. */
10 /* You may obtain a copy of the License at */
11 /* */
12 /* http://www.apache.org/licenses/LICENSE-2.0 */
13 /* */
14 /* Unless required by applicable law or agreed to in writing, software */
15 /* distributed under the License is distributed on an "AS IS" BASIS, */
16 /* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. */
17 /* See the License for the specific language governing permissions and */
18 /* limitations under the License. */
19 /* */
20 /* You should have received a copy of the Apache-2.0 license */
21 /* along with SCIP; see the file LICENSE. If not visit scipopt.org. */
22 /* */
23 /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
24 
25 /**@file branch_relpscost.c
26  * @ingroup DEFPLUGINS_BRANCH
27  * @brief reliable pseudo costs branching rule
28  * @author Tobias Achterberg
29  * @author Timo Berthold
30  * @author Gerald Gamrath
31  * @author Marc Pfetsch
32  */
33 
34 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
35 
36 #include "blockmemshell/memory.h"
37 #include "scip/branch_relpscost.h"
38 #include "scip/treemodel.h"
39 #include "scip/cons_and.h"
40 #include "scip/pub_branch.h"
41 #include "scip/pub_cons.h"
42 #include "scip/pub_message.h"
43 #include "scip/pub_misc.h"
44 #include "scip/pub_sol.h"
45 #include "scip/pub_tree.h"
46 #include "scip/pub_var.h"
47 #include "scip/scip_branch.h"
48 #include "scip/scip_cons.h"
49 #include "scip/scip_general.h"
50 #include "scip/scip_lp.h"
51 #include "scip/scip_mem.h"
52 #include "scip/scip_message.h"
53 #include "scip/scip_nlp.h"
54 #include "scip/scip_numerics.h"
55 #include "scip/scip_param.h"
56 #include "scip/scip_prob.h"
57 #include "scip/scip_randnumgen.h"
58 #include "scip/scip_sol.h"
59 #include "scip/scip_solvingstats.h"
60 #include "scip/scip_tree.h"
61 #include "scip/scip_var.h"
62 #include "scip/prop_symmetry.h"
63 #include "scip/symmetry.h"
64 #include <string.h>
65 
66 #define BRANCHRULE_NAME "relpscost"
67 #define BRANCHRULE_DESC "reliability branching on pseudo cost values"
68 #define BRANCHRULE_PRIORITY 10000
69 #define BRANCHRULE_MAXDEPTH -1
70 #define BRANCHRULE_MAXBOUNDDIST 1.0
71 
72 #define DEFAULT_CONFLICTWEIGHT 0.01 /**< weight in score calculations for conflict score */
73 #define DEFAULT_CONFLENGTHWEIGHT 0.0 /**< weight in score calculations for conflict length score*/
74 #define DEFAULT_INFERENCEWEIGHT 0.0001 /**< weight in score calculations for inference score */
75 #define DEFAULT_CUTOFFWEIGHT 0.0001 /**< weight in score calculations for cutoff score */
76 #define DEFAULT_PSCOSTWEIGHT 1.0 /**< weight in score calculations for pseudo cost score */
77 #define DEFAULT_NLSCOREWEIGHT 0.1 /**< weight in score calculations for nlcount score */
78 #define DEFAULT_MINRELIABLE 1.0 /**< minimal value for minimum pseudo cost size to regard pseudo cost value as reliable */
79 #define DEFAULT_MAXRELIABLE 5.0 /**< maximal value for minimum pseudo cost size to regard pseudo cost value as reliable */
80 #define DEFAULT_SBITERQUOT 0.5 /**< maximal fraction of strong branching LP iterations compared to normal iterations */
81 #define DEFAULT_SBITEROFS 100000 /**< additional number of allowed strong branching LP iterations */
82 #define DEFAULT_MAXLOOKAHEAD 9 /**< maximal number of further variables evaluated without better score */
83 #define DEFAULT_INITCAND 100 /**< maximal number of candidates initialized with strong branching per node */
84 #define DEFAULT_INITITER 0 /**< iteration limit for strong branching initialization of pseudo cost entries (0: auto) */
85 #define DEFAULT_MAXBDCHGS 5 /**< maximal number of bound tightenings before the node is reevaluated (-1: unlimited) */
86 #define DEFAULT_MAXPROPROUNDS -2 /**< maximum number of propagation rounds to be performed during strong branching
87  * before solving the LP (-1: no limit, -2: parameter settings) */
88 #define DEFAULT_PROBINGBOUNDS TRUE /**< should valid bounds be identified in a probing-like fashion during strong
89  * branching (only with propagation)? */
90 #define DEFAULT_USERELERRORFORRELIABILITY FALSE /**< should reliability be based on relative errors? */
91 #define DEFAULT_LOWERRORTOL 0.05 /**< lowest tolerance beneath which relative errors are reliable */
92 #define DEFAULT_HIGHERRORTOL 1.0 /**< highest tolerance beneath which relative errors are reliable */
93 #define DEFAULT_USEHYPTESTFORRELIABILITY FALSE /**< should the strong branching decision be based on a hypothesis test? */
94 #define DEFAULT_USEDYNAMICCONFIDENCE FALSE /**< should the confidence level be adjusted dynamically? */
95 #define DEFAULT_STORESEMIINITCOSTS FALSE /**< should strong branching result be considered for pseudo costs if the other direction was infeasible? */
96 #define DEFAULT_USESBLOCALINFO FALSE /**< should the scoring function use only local cutoff and inference information obtained for strong branching candidates? */
97 #define DEFAULT_CONFIDENCELEVEL 2 /**< The confidence level for statistical methods, between 0 (Min) and 4 (Max). */
98 #define DEFAULT_SKIPBADINITCANDS TRUE /**< should branching rule skip candidates that have a low probability to be
99  * better than the best strong-branching or pseudo-candidate? */
100 #define DEFAULT_STARTRANDSEED 5 /**< start random seed for random number generation */
101 #define DEFAULT_RANDINITORDER FALSE /**< should slight perturbation of scores be used to break ties in the prior scores? */
102 #define DEFAULT_USESMALLWEIGHTSITLIM FALSE /**< should smaller weights be used for pseudo cost updates after hitting the LP iteration limit? */
103 #define DEFAULT_DYNAMICWEIGHTS TRUE /**< should the weights of the branching rule be adjusted dynamically during solving based
104  * infeasible and objective leaf counters? */
105 #define DEFAULT_DEGENERACYAWARE 1 /**< should degeneracy be taken into account to update weights and skip strong branching? (0: off, 1: after root, 2: always)*/
106 
107 /* symmetry handling */
108 #define DEFAULT_FILTERCANDSSYM FALSE /**< Use symmetry to filter branching candidates? */
109 #define DEFAULT_TRANSSYMPSCOST FALSE /**< Transfer pscost information to symmetric variables if filtering is performed? */
110 
111 /** branching rule data */
112 struct SCIP_BranchruleData
113 {
114  SCIP_Real conflictweight; /**< weight in score calculations for conflict score */
115  SCIP_Real conflengthweight; /**< weight in score calculations for conflict length score */
116  SCIP_Real inferenceweight; /**< weight in score calculations for inference score */
117  SCIP_Real cutoffweight; /**< weight in score calculations for cutoff score */
118  SCIP_Real pscostweight; /**< weight in score calculations for pseudo cost score */
119  SCIP_Real nlscoreweight; /**< weight in score calculations for nlcount score */
120  SCIP_Real minreliable; /**< minimal value for minimum pseudo cost size to regard pseudo cost value as reliable */
121  SCIP_Real maxreliable; /**< maximal value for minimum pseudo cost size to regard pseudo cost value as reliable */
122  SCIP_Real sbiterquot; /**< maximal fraction of strong branching LP iterations compared to normal iterations */
123  int sbiterofs; /**< additional number of allowed strong branching LP iterations */
124  int maxlookahead; /**< maximal number of further variables evaluated without better score */
125  int initcand; /**< maximal number of candidates initialized with strong branching per node */
126  int inititer; /**< iteration limit for strong branching initialization of pseudo cost entries (0: auto) */
127  int maxbdchgs; /**< maximal number of bound tightenings before the node is reevaluated (-1: unlimited) */
128  int maxproprounds; /**< maximum number of propagation rounds to be performed during strong branching
129  * before solving the LP (-1: no limit, -2: parameter settings) */
130  SCIP_Bool probingbounds; /**< should valid bounds be identified in a probing-like fashion during strong
131  * branching (only with propagation)? */
132  SCIP_Bool userelerrorforreliability; /**< should reliability be based on relative errors? */
133  SCIP_Real lowerrortol; /**< lowest tolerance beneath which relative errors are reliable */
134  SCIP_Real higherrortol; /**< highest tolerance beneath which relative errors are reliable */
135  SCIP_Bool usehyptestforreliability; /**< should the strong branching decision be based on a hypothesis test? */
136  SCIP_Bool usedynamicconfidence; /**< should the confidence level be adjusted dynamically? */
137  SCIP_Bool storesemiinitcosts; /**< should strong branching result be considered for pseudo costs if the
138  * other direction was infeasible? */
139  SCIP_Bool usesblocalinfo; /**< should the scoring function disregard cutoffs for variable if sb-lookahead was feasible ? */
140  SCIP_Bool skipbadinitcands; /**< should branching rule skip candidates that have a low probability to be
141  * better than the best strong-branching or pseudo-candidate? */
142  SCIP_Bool dynamicweights; /**< should the weights of the branching rule be adjusted dynamically during
143  * solving based on objective and infeasible leaf counters? */
144  int degeneracyaware; /**< should degeneracy be taken into account to update weights and skip strong branching? (0: off, 1: after root, 2: always) */
145  int confidencelevel; /**< The confidence level for statistical methods, between 0 (Min) and 4 (Max). */
146  int* nlcount; /**< array to store nonlinear count values */
147  int nlcountsize; /**< length of nlcount array */
148  int nlcountmax; /**< maximum entry in nlcount array or 1 if NULL */
149  SCIP_Bool randinitorder; /**< should slight perturbation of scores be used to break ties in the prior scores? */
150  SCIP_RANDNUMGEN* randnumgen; /**< random number generator */
151  int startrandseed; /**< start random seed for random number generation */
152  SCIP_Bool usesmallweightsitlim; /**< should smaller weights be used for pseudo cost updates after hitting the LP iteration limit? */
153  SCIP_TREEMODEL* treemodel; /**< Parameters for the Treemodel branching rules */
154 
155  /* for symmetry */
156  SCIP_Bool filtercandssym; /**< Use symmetry to filter branching candidates? */
157  SCIP_Bool transsympscost; /**< Transfer pscost information to symmetric variables? */
158 
159  SCIP_Bool nosymmetry; /**< No symmetry present? */
160  int* orbits; /**< array of non-trivial orbits */
161  int* orbitbegins; /**< array containing begin positions of new orbits in orbits array */
162  int norbits; /**< pointer to number of orbits currently stored in orbits */
163  int* varorbitmap; /**< array for storing indices of the containing orbit for each variable */
164  int* orbitrep; /**< representative variable of each orbit */
165  SCIP_VAR** permvars; /**< variables on which permutations act */
166  int npermvars; /**< number of variables for permutations */
167  SCIP_HASHMAP* permvarmap; /**< map of variables to indices in permvars array */
168 };
169 
170 /*
171  * local methods
172  */
173 
174 /** initialize orbits */
175 static
176 SCIP_RETCODE initOrbits(
177  SCIP* scip, /**< SCIP data structure */
178  SCIP_BRANCHRULEDATA* branchruledata /**< branching rule data */
179  )
180 {
181  int** permstrans = NULL;
182  int* components = NULL;
183  int* componentbegins = NULL;
184  int* vartocomponent = NULL;
185  int ncomponents = 0;
186  int nperms = -1;
187 
188  assert( scip != NULL );
189  assert( branchruledata != NULL );
190  assert( branchruledata->filtercandssym );
191 
192  /* exit if no symmetry or orbits already available */
193  if( branchruledata->nosymmetry || branchruledata->orbits != NULL )
194  return SCIP_OKAY;
195 
196  assert( branchruledata->orbitbegins == NULL );
197  assert( branchruledata->varorbitmap == NULL );
198  assert( branchruledata->orbitrep == NULL );
199 
200  /* obtain symmetry including permutations */
201  SCIP_CALL( SCIPgetSymmetry(scip, &branchruledata->npermvars, &branchruledata->permvars, &branchruledata->permvarmap,
202  &nperms, NULL, &permstrans, NULL, NULL, &components, &componentbegins, &vartocomponent, &ncomponents) );
203 
204  /* turn off symmetry handling if there is no symmetry or the number of variables is not equal */
205  if( nperms <= 0 || branchruledata->npermvars != SCIPgetNVars(scip) )
206  {
207  branchruledata->nosymmetry = TRUE;
208  return SCIP_OKAY;
209  }
210  assert( branchruledata->permvars != NULL );
211  assert( branchruledata->permvarmap != NULL );
212  assert( branchruledata->npermvars > 0 );
213  assert( permstrans != NULL );
214  assert( components != NULL );
215  assert( componentbegins != NULL );
216  assert( vartocomponent != NULL );
217  assert( ncomponents > 0 );
218 
219  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &branchruledata->orbits, branchruledata->npermvars) );
220  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &branchruledata->orbitbegins, branchruledata->npermvars) );
221  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &branchruledata->varorbitmap, branchruledata->npermvars) );
222  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &branchruledata->orbitrep, branchruledata->npermvars) );
223 
224  /* Compute orbits on all variables, since this might help for branching and this computation is only done once. */
225  SCIP_CALL( SCIPcomputeOrbitsComponentsSym(scip, branchruledata->npermvars, permstrans, nperms,
226  components, componentbegins, vartocomponent, ncomponents,
227  branchruledata->orbits, branchruledata->orbitbegins, &branchruledata->norbits, branchruledata->varorbitmap) );
228  assert( branchruledata->norbits < branchruledata->npermvars );
229 
230  return SCIP_OKAY;
231 }
232 
233 /** filter out symmetric variables from branching variables */
234 static
235 SCIP_RETCODE filterSymmetricVariables(
236  SCIP* scip, /**< SCIP data structure */
237  SCIP_BRANCHRULEDATA* branchruledata, /**< branching rule data */
238  SCIP_VAR** origbranchcands, /**< original branching candidates */
239  SCIP_Real* origbranchcandssol, /**< original solution value for the branching candidates */
240  SCIP_Real* origbranchcandsfrac,/**< original fractional part of the branching candidates */
241  int norigbranchcands, /**< original number of branching candidates */
242  SCIP_VAR** branchcands, /**< branching candidates */
243  SCIP_Real* branchcandssol, /**< solution value for the branching candidates */
244  SCIP_Real* branchcandsfrac, /**< fractional part of the branching candidates */
245  int* branchorbitidx, /**< array of indices of orbit of branching candidates */
246  int* nbranchcands /**< pointer to store number of branching candidates */
247  )
248 {
249  int i;
250 
251  assert( scip != NULL );
252  assert( branchruledata != NULL );
253  assert( origbranchcands != NULL );
254  assert( origbranchcandssol != NULL );
255  assert( origbranchcandsfrac != NULL );
256  assert( branchcands != NULL );
257  assert( branchcandssol != NULL );
258  assert( branchcandsfrac != NULL );
259  assert( nbranchcands != NULL );
260 
261  assert( ! branchruledata->nosymmetry );
262  assert( branchruledata->orbitbegins != NULL );
263  assert( branchruledata->orbits != NULL );
264  assert( branchruledata->permvarmap != NULL );
265  assert( branchruledata->varorbitmap != NULL );
266  assert( branchruledata->orbitrep != NULL );
267  assert( branchruledata->norbits < branchruledata->npermvars );
268 
269  /* init representatives (used to see whether variable is the first in an orbit) */
270  for( i = 0; i < branchruledata->norbits; ++i )
271  branchruledata->orbitrep[i] = -1;
272 
273  /* loop through branching variables, determine orbit and whether they are the first ones */
274  *nbranchcands = 0;
275  for( i = 0; i < norigbranchcands; ++i )
276  {
277  int orbitidx = -1;
278  int varidx;
279 
280  varidx = SCIPhashmapGetImageInt(branchruledata->permvarmap, (void*) origbranchcands[i]);
281  if( varidx != INT_MAX )
282  {
283  assert( 0 <= varidx && varidx < branchruledata->npermvars );
284  orbitidx = branchruledata->varorbitmap[varidx];
285  }
286  assert( -1 <= orbitidx && orbitidx < branchruledata->norbits );
287 
288  /* Check whether the variable is not present (can happen if variable was added after computing symmetries or is in
289  * a singleton orbit). */
290  if( orbitidx == -1 )
291  {
292  branchcands[*nbranchcands] = origbranchcands[i];
293  branchcandssol[*nbranchcands] = origbranchcandssol[i];
294  branchcandsfrac[*nbranchcands] = origbranchcandsfrac[i];
295  branchorbitidx[*nbranchcands] = -1;
296  ++(*nbranchcands);
297  }
298  else if( branchruledata->orbitrep[orbitidx] == -1 )
299  {
300  /* if variable is the first in a nontrivial orbit */
301  assert( 0 <= varidx && varidx < branchruledata->npermvars );
302  branchruledata->orbitrep[orbitidx] = varidx;
303  branchcands[*nbranchcands] = origbranchcands[i];
304  branchcandssol[*nbranchcands] = origbranchcandssol[i];
305  branchcandsfrac[*nbranchcands] = origbranchcandsfrac[i];
306  branchorbitidx[*nbranchcands] = orbitidx;
307  ++(*nbranchcands);
308  }
309  }
310 
311  SCIPdebugMsg(scip, "Filtered out %d variables by symmetry.\n", norigbranchcands - *nbranchcands);
312 
313  return SCIP_OKAY;
314 }
315 
316 /** updates the pseudo costs of the given variable and all its symmetric variables */
317 static
318 SCIP_RETCODE SCIPupdateVarPseudocostSymmetric(
319  SCIP* scip, /**< SCIP data structure */
320  SCIP_BRANCHRULEDATA* branchruledata, /**< branching rule data */
321  SCIP_VAR* branchvar, /**< branching variable candidate */
322  int* branchorbitidx, /**< array of orbit indices */
323  int branchvaridx, /**< index of variable in branchorbitidx */
324  SCIP_Real solvaldelta, /**< difference of variable's new LP value - old LP value */
325  SCIP_Real objdelta, /**< difference of new LP's objective value - old LP's objective value */
326  SCIP_Real weight /**< weight in (0,1] of this update in pseudo cost sum */
327  )
328 {
329  int orbitidx;
330  int j;
331 
332  assert( scip != NULL );
333  assert( branchruledata != NULL );
334 
335  if( branchruledata->nosymmetry || ! branchruledata->transsympscost || branchorbitidx == NULL )
336  {
337  /* use original update function */
338  SCIP_CALL( SCIPupdateVarPseudocost(scip, branchvar, solvaldelta, objdelta, weight) );
339  return SCIP_OKAY;
340  }
341 
342  assert( branchruledata->orbitbegins != NULL );
343  assert( branchruledata->orbits != NULL );
344  assert( 0 <= branchvaridx && branchvaridx < branchruledata->npermvars );
345 
346  orbitidx = branchorbitidx[branchvaridx];
347  if( orbitidx < 0 )
348  {
349  /* only update given variable */
350  SCIP_CALL( SCIPupdateVarPseudocost(scip, branchvar, solvaldelta, objdelta, weight) );
351  return SCIP_OKAY;
352  }
353  assert( 0 <= orbitidx && orbitidx < branchruledata->norbits );
354 
355  /* loop through orbit containing variable and update pseudo costs for all variables */
356  for( j = branchruledata->orbitbegins[orbitidx]; j < branchruledata->orbitbegins[orbitidx+1]; ++j )
357  {
358  SCIP_VAR* var;
359  int idx;
360 
361  idx = branchruledata->orbits[j];
362  assert( 0 <= idx && idx < branchruledata->npermvars );
363 
364  var = branchruledata->permvars[idx];
365  assert( var != NULL );
366 
367  if( SCIPvarIsActive(var) )
368  {
369  SCIP_CALL( SCIPupdateVarPseudocost(scip, var, solvaldelta, objdelta, weight) );
370  }
371  }
372 
373  return SCIP_OKAY;
374 }
375 
376 /**! [SnippetCodeStyleStaticAsserts] */
377 
378 /** return probindex of variable or corresponding active variable (if negated or aggregated) or -1 (if multiaggregated) */
379 static
380 SCIP_RETCODE binvarGetActiveProbindex(
381  SCIP* scip, /**< SCIP data structure */
382  SCIP_VAR* var, /**< binary variable */
383  int* probindex /**< buffer to store probindex */
384  )
385 {
386  assert(scip != NULL);
387  assert(var != NULL);
388  assert(SCIPvarIsBinary(var));
389  assert(probindex != NULL);
390 
391 /**! [SnippetCodeStyleStaticAsserts] */
392 
393  *probindex = SCIPvarGetProbindex(var);
394 
395  /* if variable is not active, try to find active representative */
396  if( *probindex == -1 )
397  {
398  SCIP_VAR* repvar;
399  SCIP_Bool negated;
400 
401  SCIP_CALL( SCIPgetBinvarRepresentative(scip, var, &repvar, &negated) );
402  assert(repvar != NULL);
403  assert(SCIPvarGetStatus(repvar) != SCIP_VARSTATUS_FIXED);
404 
405  if( SCIPvarIsActive(repvar) )
406  *probindex = SCIPvarGetProbindex(repvar);
407  else if( SCIPvarIsNegated(repvar) )
408  *probindex = SCIPvarGetProbindex(SCIPvarGetNegationVar(repvar));
409  }
410 
411  return SCIP_OKAY;
412 }
413 
414 /**! [SnippetCodeStyleDeclaration] */
415 
416 /** counts number of nonlinear constraints in which each variable appears */
417 static
418 SCIP_RETCODE countNonlinearities(
419  SCIP* scip, /**< SCIP data structure */
420  int* nlcount, /**< pointer to array for storing count values */
421  int nlcountsize, /**< buffer for storing length of nlcount array */
422  int* nlcountmax /**< buffer for storing maximum value in nlcount array */
423  )
424 {
425  SCIP_CONSHDLR* andconshdlr;
426  SCIP_VAR** vars;
427  int nvars;
428  int i;
429 
430 /**! [SnippetCodeStyleDeclaration] */
431 
432  assert(scip != NULL);
433  assert(nlcount != NULL);
434  assert(nlcountmax != NULL);
435 
436  SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
437  assert(nlcountsize >= nvars);
438 
439  /* get nonlinearity for constraints in NLP */
440  if( SCIPisNLPConstructed(scip) )
441  {
442  assert(SCIPgetNNLPVars(scip) == nvars);
443  SCIP_CALL( SCIPgetNLPVarsNonlinearity(scip, nlcount) );
444  }
445  else
446  {
447  BMSclearMemoryArray(nlcount, nvars);
448  }
449 
450  /* increase counters for and constraints */
451  andconshdlr = SCIPfindConshdlr(scip, "and");
452  if( andconshdlr != NULL )
453  {
454  int c;
455 
456  for( c = 0; c < SCIPconshdlrGetNActiveConss(andconshdlr); c++ )
457  {
458  SCIP_CONS* andcons;
459  SCIP_VAR** andvars;
460  SCIP_VAR* andres;
461  int probindex;
462  int nandvars;
463  int v;
464 
465  /* get constraint and variables */
466  andcons = SCIPconshdlrGetConss(andconshdlr)[c];
467  nandvars = SCIPgetNVarsAnd(scip, andcons);
468  andvars = SCIPgetVarsAnd(scip, andcons);
469  andres = SCIPgetResultantAnd(scip, andcons);
470 
471  probindex = -1;
472 
473  /**! [SnippetCodeStyleIfFor] */
474 
475  for( v = 0; v < nandvars; v++ )
476  {
477  /* don't rely on the and conshdlr removing fixed variables
478  * @todo fix the and conshdlr in that respect
479  */
480  if( SCIPvarGetStatus(andvars[v]) != SCIP_VARSTATUS_FIXED )
481  {
482  SCIP_CALL( binvarGetActiveProbindex(scip, andvars[v], &probindex) );
483  if( probindex >= 0 )
484  nlcount[probindex]++;
485  }
486  }
487 
488  /**! [SnippetCodeStyleIfFor] */
489 
490  SCIP_CALL( binvarGetActiveProbindex(scip, andres, &probindex) );
491  if( probindex >= 0 )
492  nlcount[probindex]++;
493  }
494  }
495 
496  /* compute maximum count value */
497  *nlcountmax = 1;
498  for( i = 0; i < nvars; i++ )
499  {
500  if( *nlcountmax < nlcount[i] )
501  *nlcountmax = nlcount[i];
502  }
503 
504  return SCIP_OKAY;
505 }
506 
507 static
508 SCIP_RETCODE branchruledataEnsureNlcount(
509  SCIP* scip, /**< SCIP data structure */
510  SCIP_BRANCHRULEDATA* branchruledata /**< branching rule data */
511  )
512 {
513  int nvars;
514 
515  assert(scip != NULL);
516  assert(branchruledata != NULL);
517 
518  nvars = SCIPgetNVars(scip);
519 
520  /**@todo test whether we want to apply this as if problem has only and constraints */
521  /**@todo update changes in and constraints */
522  if( branchruledata->nlscoreweight > 0.0 ) /* && SCIPisNLPConstructed(scip) */
523  {
524  if( branchruledata->nlcount == NULL )
525  {
526  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &branchruledata->nlcount, nvars) );
527  branchruledata->nlcountsize = nvars;
528 
529  SCIP_CALL( countNonlinearities(scip, branchruledata->nlcount, branchruledata->nlcountsize, &branchruledata->nlcountmax) );
530  }
531  else if( branchruledata->nlcountsize < nvars )
532  {
533  SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &branchruledata->nlcount, branchruledata->nlcountsize, nvars) );
534  /**@todo should we update nlcounts for new variables? */
535  BMSclearMemoryArray(&(branchruledata->nlcount[branchruledata->nlcountsize]), nvars - branchruledata->nlcountsize); /*lint !e866*/
536  branchruledata->nlcountsize = nvars;
537  }
538  assert(branchruledata->nlcount != NULL);
539  assert(branchruledata->nlcountsize == nvars);
540  assert(branchruledata->nlcountmax >= 1);
541  }
542  else
543  {
544  SCIPfreeBlockMemoryArrayNull(scip, &branchruledata->nlcount, branchruledata->nlcountsize);
545  branchruledata->nlcountsize = 0;
546  branchruledata->nlcountmax = 1;
547  }
548 
549  return SCIP_OKAY;
550 }
551 
552 
553 /** calculates nlscore value between 0 and 1 */
554 static
555 SCIP_Real calcNlscore(
556  SCIP* scip, /**< SCIP data structure */
557  int* nlcount, /**< array to store count values */
558  int nlcountmax, /**< maximum value in nlcount array */
559  int probindex /**< index of branching candidate */
560  )
561 {
562  if( nlcountmax >= 1 && nlcount != NULL )
563  {
564  SCIP_Real nlscore;
565 
566  assert(scip != NULL);
567  assert(probindex >= 0);
568  assert(probindex < SCIPgetNVars(scip));
569 
570  nlscore = nlcount[probindex] / (SCIP_Real)nlcountmax;
571 
572  assert(nlscore >= 0.0);
573  assert(nlscore <= 1.0);
574  return nlscore;
575  }
576  else
577  return 0.0;
578 }
579 
580 /** calculates an overall score value for the given individual score values */
581 static
582 SCIP_Real calcScore(
583  SCIP* scip, /**< SCIP data structure */
584  SCIP_BRANCHRULEDATA* branchruledata, /**< branching rule data */
585  SCIP_Real conflictscore, /**< conflict score of current variable */
586  SCIP_Real avgconflictscore, /**< average conflict score */
587  SCIP_Real conflengthscore, /**< conflict length score of current variable */
588  SCIP_Real avgconflengthscore, /**< average conflict length score */
589  SCIP_Real inferencescore, /**< inference score of current variable */
590  SCIP_Real avginferencescore, /**< average inference score */
591  SCIP_Real cutoffscore, /**< cutoff score of current variable */
592  SCIP_Real avgcutoffscore, /**< average cutoff score */
593  SCIP_Real pscostscore, /**< pscost score of current variable */
594  SCIP_Real avgpscostscore, /**< average pscost score */
595  SCIP_Real nlscore, /**< nonlinear score of current variable between 0 and 1 */
596  SCIP_Real frac, /**< fractional value of variable in current solution */
597  SCIP_Real degeneracyfactor /**< factor to apply because of degeneracy */
598  )
599 {
600  SCIP_Real score;
601  SCIP_Real dynamicfactor;
602 
603  assert(branchruledata != NULL);
604  assert(0.0 < frac && frac < 1.0);
605 
606  if( branchruledata->dynamicweights )
607  {
608  dynamicfactor = (SCIPgetNInfeasibleLeaves(scip) + 1.0) / (SCIPgetNObjlimLeaves(scip) + 1.0);
609  }
610  else
611  dynamicfactor = 1.0;
612 
613  dynamicfactor *= degeneracyfactor;
614 
615  score = dynamicfactor * (branchruledata->conflictweight * (1.0 - 1.0/(1.0+conflictscore/avgconflictscore))
616  + branchruledata->conflengthweight * (1.0 - 1.0/(1.0+conflengthscore/avgconflengthscore))
617  + branchruledata->inferenceweight * (1.0 - 1.0/(1.0+inferencescore/avginferencescore))
618  + branchruledata->cutoffweight * (1.0 - 1.0/(1.0+cutoffscore/avgcutoffscore)))
619  + branchruledata->pscostweight / dynamicfactor * (1.0 - 1.0/(1.0+pscostscore/avgpscostscore))
620  + branchruledata->nlscoreweight * nlscore;
621 
622  /* avoid close to integral variables */
623  if( MIN(frac, 1.0 - frac) < 10.0 * SCIPfeastol(scip) )
624  score *= 1e-6;
625 
626  return score;
627 }
628 
629 /** adds given index and direction to bound change arrays */
630 static
631 SCIP_RETCODE addBdchg(
632  SCIP* scip, /**< SCIP data structure */
633  int** bdchginds, /**< pointer to bound change index array */
634  SCIP_BOUNDTYPE** bdchgtypes, /**< pointer to bound change types array */
635  SCIP_Real** bdchgbounds, /**< pointer to bound change new bounds array */
636  int* nbdchgs, /**< pointer to number of bound changes */
637  int ind, /**< index to store in bound change index array */
638  SCIP_BOUNDTYPE type, /**< type of the bound change to store in bound change type array */
639  SCIP_Real bound /**< new bound to store in bound change new bounds array */
640  )
641 {
642  assert(bdchginds != NULL);
643  assert(bdchgtypes != NULL);
644  assert(bdchgbounds != NULL);
645  assert(nbdchgs != NULL);
646 
647  SCIP_CALL( SCIPreallocBufferArray(scip, bdchginds, (*nbdchgs) + 1) );
648  SCIP_CALL( SCIPreallocBufferArray(scip, bdchgtypes, (*nbdchgs) + 1) );
649  SCIP_CALL( SCIPreallocBufferArray(scip, bdchgbounds, (*nbdchgs) + 1) );
650  assert(*bdchginds != NULL);
651  assert(*bdchgtypes != NULL);
652  assert(*bdchgbounds != NULL);
653 
654  (*bdchginds)[*nbdchgs] = ind;
655  (*bdchgtypes)[*nbdchgs] = type;
656  (*bdchgbounds)[*nbdchgs] = bound;
657  (*nbdchgs)++;
658 
659  return SCIP_OKAY;
660 }
661 
662 /** frees bound change arrays */
663 static
664 void freeBdchgs(
665  SCIP* scip, /**< SCIP data structure */
666  int** bdchginds, /**< pointer to bound change index array */
667  SCIP_BOUNDTYPE** bdchgtypes, /**< pointer to bound change types array */
668  SCIP_Real** bdchgbounds, /**< pointer to bound change new bounds array */
669  int* nbdchgs /**< pointer to number of bound changes */
670  )
671 {
672  assert(bdchginds != NULL);
673  assert(bdchgtypes != NULL);
674  assert(bdchgbounds != NULL);
675  assert(nbdchgs != NULL);
676 
677  SCIPfreeBufferArrayNull(scip, bdchgbounds);
678  SCIPfreeBufferArrayNull(scip, bdchgtypes);
679  SCIPfreeBufferArrayNull(scip, bdchginds);
680  *nbdchgs = 0;
681 }
682 
683 /** applies bound changes stored in bound change arrays */
684 static
685 SCIP_RETCODE applyBdchgs(
686  SCIP* scip, /**< SCIP data structure */
687  SCIP_VAR** vars, /**< problem variables */
688  int* bdchginds, /**< bound change index array */
689  SCIP_BOUNDTYPE* bdchgtypes, /**< bound change types array */
690  SCIP_Real* bdchgbounds, /**< bound change new bound array */
691  int nbdchgs, /**< number of bound changes */
692  SCIP_RESULT* result /**< result pointer */
693  )
694 {
695 #ifndef NDEBUG
696  SCIP_BRANCHRULE* branchrule;
697  SCIP_BRANCHRULEDATA* branchruledata;
698 #endif
699  SCIP_Bool infeasible;
700  SCIP_Bool tightened;
701  int i;
702 
703  assert(vars != NULL);
704 
705 #ifndef NDEBUG
706  /* find branching rule */
707  branchrule = SCIPfindBranchrule(scip, BRANCHRULE_NAME);
708  assert(branchrule != NULL);
709 
710  /* get branching rule data */
711  branchruledata = SCIPbranchruleGetData(branchrule);
712  assert(branchruledata != NULL);
713 #endif
714 
715  SCIPdebugMsg(scip, "applying %d bound changes\n", nbdchgs);
716 
717  for( i = 0; i < nbdchgs; ++i )
718  {
719  int v;
720 
721  v = bdchginds[i];
722 
723  SCIPdebugMsg(scip, " -> <%s> [%g,%g]\n",
724  SCIPvarGetName(vars[v]), SCIPvarGetLbLocal(vars[v]), SCIPvarGetUbLocal(vars[v]));
725 
726  if( bdchgtypes[i] == SCIP_BOUNDTYPE_LOWER )
727  {
728  /* change lower bound of variable to given bound */
729  SCIP_CALL( SCIPtightenVarLb(scip, vars[v], bdchgbounds[i], TRUE, &infeasible, &tightened) );
730  if( infeasible )
731  {
732  *result = SCIP_CUTOFF;
733  return SCIP_OKAY;
734  }
735 
736  /* if we did propagation, the bound change might already have been added */
737  assert(tightened || (branchruledata->maxproprounds != 0));
738  }
739  else
740  {
741  assert(bdchgtypes[i] == SCIP_BOUNDTYPE_UPPER);
742 
743  /* change upper bound of variable to given bound */
744  SCIP_CALL( SCIPtightenVarUb(scip, vars[v], bdchgbounds[i], TRUE, &infeasible, &tightened) );
745  if( infeasible )
746  {
747  *result = SCIP_CUTOFF;
748  return SCIP_OKAY;
749  }
750 
751  /* if we did propagation, the bound change might already have been added */
752  assert(tightened || (branchruledata->maxproprounds != 0));
753  }
754  SCIPdebugMsg(scip, " -> [%g,%g]\n", SCIPvarGetLbLocal(vars[v]), SCIPvarGetUbLocal(vars[v]));
755  }
756 
757  return SCIP_OKAY;
758 }
759 
760 /** execute reliability pseudo cost branching */
761 static
762 SCIP_RETCODE execRelpscost(
763  SCIP* scip, /**< SCIP data structure */
764  SCIP_BRANCHRULE* branchrule, /**< branching rule */
765  SCIP_VAR** branchcands, /**< branching candidates */
766  SCIP_Real* branchcandssol, /**< solution value for the branching candidates */
767  SCIP_Real* branchcandsfrac, /**< fractional part of the branching candidates */
768  int* branchorbitidx, /**< indices of orbit (or NULL) */
769  int nbranchcands, /**< number of branching candidates */
770  SCIP_Bool executebranch, /**< execute a branching step or run probing only */
771  SCIP_RESULT* result /**< pointer to the result of the execution */
772  )
773 { /*lint --e{715}*/
774  SCIP_BRANCHRULEDATA* branchruledata;
775  SCIP_Real lpobjval;
776  SCIP_Real bestsbdown;
777  SCIP_Real bestsbup;
778  SCIP_Real provedbound;
779  SCIP_Bool bestsbdownvalid;
780  SCIP_Bool bestsbupvalid;
781  SCIP_Bool bestsbdowncutoff;
782  SCIP_Bool bestsbupcutoff;
783  SCIP_Bool bestisstrongbranch;
784  SCIP_Bool allcolsinlp;
785  SCIP_Bool exactsolve;
786  int ninitcands;
787  int bestcand;
788 
789  /* remember which variables strong branching is performed on, and the
790  * recorded lp bound changes that are observed */
791  SCIP_Bool* sbvars = NULL;
792  SCIP_Real* sbdown = NULL;
793  SCIP_Real* sbup = NULL;
794  SCIP_Bool* sbdownvalid = NULL;
795  SCIP_Bool* sbupvalid = NULL;
796 
797  *result = SCIP_DIDNOTRUN;
798 
799  assert(SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OPTIMAL);
800 
801  /* get branching rule data */
802  branchruledata = SCIPbranchruleGetData(branchrule);
803  assert(branchruledata != NULL);
804 
805  /* get current LP objective bound of the local sub problem and global cutoff bound */
806  lpobjval = SCIPgetLPObjval(scip);
807 
808  /* check, if we want to solve the problem exactly, meaning that strong branching information is not useful
809  * for cutting off sub problems and improving lower bounds of children
810  */
811  exactsolve = SCIPisExactSolve(scip);
812 
813  /* check, if all existing columns are in LP, and thus the strong branching results give lower bounds */
814  allcolsinlp = SCIPallColsInLP(scip);
815 
816  bestcand = -1;
817  bestisstrongbranch = FALSE;
818  bestsbdown = SCIP_INVALID;
819  bestsbup = SCIP_INVALID;
820  bestsbdownvalid = FALSE;
821  bestsbupvalid = FALSE;
822  bestsbdowncutoff = FALSE;
823  bestsbupcutoff = FALSE;
824  provedbound = lpobjval;
825 
826  /* Allocate memory to store the lp bounds of the up and down children
827  * for those of the variables that we performed sb on
828  */
829  SCIP_CALL( SCIPallocBufferArray(scip, &sbdown, nbranchcands) );
830  SCIP_CALL( SCIPallocBufferArray(scip, &sbup, nbranchcands) );
831  SCIP_CALL( SCIPallocBufferArray(scip, &sbdownvalid, nbranchcands) );
832  SCIP_CALL( SCIPallocBufferArray(scip, &sbupvalid, nbranchcands) );
833  SCIP_CALL( SCIPallocBufferArray(scip, &sbvars, nbranchcands) );
834 
835  if( nbranchcands == 1 )
836  {
837  /* only one candidate: nothing has to be done */
838  bestcand = 0;
839  SCIPdebug(ninitcands = 0);
840  sbvars[0] = FALSE;
841  }
842  else
843  {
844  SCIP_VAR** vars;
845  int* initcands;
846  SCIP_Real* initcandscores;
847  SCIP_Real* newlbs = NULL;
848  SCIP_Real* newubs = NULL;
849  SCIP_Real* mingains = NULL;
850  SCIP_Real* maxgains = NULL;
851  /* scores computed from pseudocost branching */
852  SCIP_Real* scores = NULL;
853  SCIP_Real* scoresfrompc = NULL;
854  SCIP_Real* scoresfromothers = NULL;
855  int* bdchginds;
856  SCIP_BOUNDTYPE* bdchgtypes;
857  SCIP_Real* bdchgbounds;
858  int maxninitcands;
859  int nuninitcands;
860  int nbdchgs;
861  int nbdconflicts;
862  SCIP_Real avgconflictscore;
863  SCIP_Real avgconflengthscore;
864  SCIP_Real avginferencescore;
865  SCIP_Real avgcutoffscore;
866  SCIP_Real avgpscostscore;
867  SCIP_Real bestpsscore;
868  SCIP_Real bestpsfracscore;
869  SCIP_Real bestpsdomainscore;
870  SCIP_Real bestsbscore;
871  SCIP_Real bestuninitsbscore;
872  SCIP_Real bestsbfracscore;
873  SCIP_Real bestsbdomainscore;
874  SCIP_Real prio;
875  SCIP_Real reliable;
876  SCIP_Real maxlookahead;
877  SCIP_Real lookahead;
878  SCIP_Real relerrorthreshold;
879  SCIP_Bool initstrongbranching;
880  SCIP_Bool propagate;
881  SCIP_Bool probingbounds;
882  SCIP_Longint nodenum;
883  SCIP_Longint nlpiterationsquot;
884  SCIP_Longint nsblpiterations;
885  SCIP_Longint maxnsblpiterations;
886  int bestsolidx;
887  int maxbdchgs;
888  int bestpscand;
889  int bestsbcand;
890  int bestuninitsbcand;
891  int inititer;
892  int nvars;
893  int i;
894  int c;
895  SCIP_CONFIDENCELEVEL clevel;
896  SCIP_Real degeneracyfactor = 1.0;
897 
898  /* get LP degeneracy information and compute a factor to change weighting of pseudo cost score vs. other scores */
899  if( branchruledata->degeneracyaware > 0 && (SCIPgetDepth(scip) > 0 || branchruledata->degeneracyaware > 1) )
900  {
901  SCIP_Real degeneracy;
902  SCIP_Real varconsratio;
903 
904  /* get LP degeneracy information */
905  SCIP_CALL( SCIPgetLPDualDegeneracy(scip, &degeneracy, &varconsratio) );
906 
907  assert(degeneracy >= 0.0);
908  assert(degeneracy <= 1.0);
909  assert(varconsratio >= 1.0);
910 
911  /* increase factor for a degeneracy >= 80% */
912  if( degeneracy >= 0.8 )
913  {
914  degeneracy = 10.0 * (degeneracy - 0.7);
915  degeneracyfactor = degeneracyfactor * pow(10.0,degeneracy);
916  }
917  /* increase factor for a variable-constraint ratio >= 2.0 */
918  if( varconsratio >= 2.0 )
919  {
920  degeneracyfactor *= 10.0 * varconsratio;
921  }
922  }
923 
924  vars = SCIPgetVars(scip);
925  nvars = SCIPgetNVars(scip);
926 
927  bestsolidx = SCIPgetBestSol(scip) == NULL ? -1 : SCIPsolGetIndex(SCIPgetBestSol(scip));
928 
929  /* get average conflict, inference, and pseudocost scores */
930  avgconflictscore = SCIPgetAvgConflictScore(scip);
931  avgconflictscore = MAX(avgconflictscore, 0.1);
932  avgconflengthscore = SCIPgetAvgConflictlengthScore(scip);
933  avgconflengthscore = MAX(avgconflengthscore, 0.1);
934  avginferencescore = SCIPgetAvgInferenceScore(scip);
935  avginferencescore = MAX(avginferencescore, 0.1);
936  avgcutoffscore = SCIPgetAvgCutoffScore(scip);
937  avgcutoffscore = MAX(avgcutoffscore, 0.1);
938  avgpscostscore = SCIPgetAvgPseudocostScore(scip);
939  avgpscostscore = MAX(avgpscostscore, 0.1);
940 
941  /* get nonlinear counts according to parameters */
942  SCIP_CALL( branchruledataEnsureNlcount(scip, branchruledata) );
943 
944  initstrongbranching = FALSE;
945 
946  /* check whether propagation should be performed */
947  propagate = (branchruledata->maxproprounds != 0);
948 
949  /* check whether valid bounds should be identified in probing-like fashion */
950  probingbounds = propagate && branchruledata->probingbounds;
951 
952  /* get maximal number of candidates to initialize with strong branching; if the current solutions is not basic,
953  * we cannot warmstart the simplex algorithm and therefore don't initialize any candidates
954  */
955  maxninitcands = MIN(nbranchcands, branchruledata->initcand);
956  if( !SCIPisLPSolBasic(scip) )
957  maxninitcands = 0;
958 
959  /* calculate maximal number of strong branching LP iterations; if we used too many, don't apply strong branching
960  * any more; also, if degeneracy is too high, don't run strong branching at this node
961  */
962  nlpiterationsquot = (SCIP_Longint)(branchruledata->sbiterquot * SCIPgetNNodeLPIterations(scip));
963  maxnsblpiterations = nlpiterationsquot + branchruledata->sbiterofs + SCIPgetNRootStrongbranchLPIterations(scip);
964  nsblpiterations = SCIPgetNStrongbranchLPIterations(scip);
965  if( nsblpiterations > maxnsblpiterations || degeneracyfactor >= 10.0 )
966  maxninitcands = 0;
967 
968  /* get buffer for storing the unreliable candidates */
969  SCIP_CALL( SCIPallocBufferArray(scip, &initcands, maxninitcands+1) ); /* allocate one additional slot for convenience */
970  SCIP_CALL( SCIPallocBufferArray(scip, &initcandscores, maxninitcands+1) );
971  ninitcands = 0;
972 
973  /* Allocate memory for the down and up gains, and the computed pseudocost scores */
974  SCIP_CALL( SCIPallocBufferArray(scip, &mingains, nbranchcands) );
975  SCIP_CALL( SCIPallocBufferArray(scip, &maxgains, nbranchcands) );
976  SCIP_CALL( SCIPallocBufferArray(scip, &scores, nbranchcands) );
977  SCIP_CALL( SCIPallocBufferArray(scip, &scoresfrompc, nbranchcands) );
978  SCIP_CALL( SCIPallocBufferArray(scip, &scoresfromothers, nbranchcands) );
979 
980  /* get current node number */
981  nodenum = SCIPgetNNodes(scip);
982 
983  /* initialize bound change arrays */
984  bdchginds = NULL;
985  bdchgtypes = NULL;
986  bdchgbounds = NULL;
987  nbdchgs = 0;
988  nbdconflicts = 0;
989  maxbdchgs = branchruledata->maxbdchgs;
990  if( maxbdchgs == -1 )
991  maxbdchgs = INT_MAX;
992 
993  /* calculate value used as reliability */
994  prio = (maxnsblpiterations - nsblpiterations)/(nsblpiterations + 1.0);
995  prio = MIN(prio, 1.0);
996  prio = MAX(prio, (nlpiterationsquot - nsblpiterations)/(nsblpiterations + 1.0));
997  reliable = (1.0-prio) * branchruledata->minreliable + prio * branchruledata->maxreliable;
998 
999  /* calculate the threshold for the relative error in the same way; low tolerance is more strict than higher tolerance */
1000  relerrorthreshold = (1.0 - prio) * branchruledata->higherrortol + prio * branchruledata->lowerrortol;
1001 
1002  clevel = (SCIP_CONFIDENCELEVEL)branchruledata->confidencelevel;
1003  /* determine the confidence level for hypothesis testing based on value of prio */
1004  if( branchruledata->usedynamicconfidence )
1005  {
1006  /* with decreasing priority, use a less strict confidence level */
1007  if( prio >= 0.9 )
1008  clevel = SCIP_CONFIDENCELEVEL_MAX;
1009  else if( prio >= 0.7 )
1010  clevel = SCIP_CONFIDENCELEVEL_HIGH;
1011  else if( prio >= 0.5 )
1012  clevel = SCIP_CONFIDENCELEVEL_MEDIUM;
1013  else if( prio >= 0.3 )
1014  clevel = SCIP_CONFIDENCELEVEL_LOW;
1015  else
1016  clevel = SCIP_CONFIDENCELEVEL_MIN;
1017  }
1018 
1019  /* search for the best pseudo cost candidate, while remembering unreliable candidates in a sorted buffer */
1020  nuninitcands = 0;
1021  bestpscand = -1;
1022  bestpsscore = -SCIPinfinity(scip);
1023  bestpsfracscore = -SCIPinfinity(scip);
1024  bestpsdomainscore = -SCIPinfinity(scip);
1025 
1026  /* search for the best candidate first */
1027  if( branchruledata->usehyptestforreliability )
1028  {
1029  for( c = 0; c < nbranchcands; ++c )
1030  {
1031  SCIP_Real conflictscore;
1032  SCIP_Real conflengthscore;
1033  SCIP_Real inferencescore;
1034  SCIP_Real cutoffscore;
1035  SCIP_Real pscostscore;
1036  SCIP_Real nlscore;
1037  SCIP_Real score;
1038 
1039  conflictscore = SCIPgetVarConflictScore(scip, branchcands[c]);
1040  conflengthscore = SCIPgetVarConflictlengthScore(scip, branchcands[c]);
1041  inferencescore = SCIPgetVarAvgInferenceScore(scip, branchcands[c]);
1042  cutoffscore = SCIPgetVarAvgCutoffScore(scip, branchcands[c]);
1043  nlscore = calcNlscore(scip, branchruledata->nlcount, branchruledata->nlcountmax, SCIPvarGetProbindex(branchcands[c]));
1044  pscostscore = SCIPgetVarPseudocostScore(scip, branchcands[c], branchcandssol[c]);
1045 
1046  /* replace the pseudo cost score with the already calculated one;
1047  * @todo: use old data for strong branching with propagation?
1048  */
1049  if( SCIPgetVarStrongbranchNode(scip, branchcands[c]) == nodenum )
1050  {
1051  SCIP_Real down;
1052  SCIP_Real up;
1053  SCIP_Real lastlpobjval;
1054  SCIP_Real downgain;
1055  SCIP_Real upgain;
1056 
1057  /* use the score of the strong branching call at the current node */
1058  SCIP_CALL( SCIPgetVarStrongbranchLast(scip, branchcands[c], &down, &up, NULL, NULL, NULL, &lastlpobjval) );
1059  downgain = MAX(down - lastlpobjval, 0.0);
1060  upgain = MAX(up - lastlpobjval, 0.0);
1061  pscostscore = SCIPgetBranchScore(scip, branchcands[c], downgain, upgain);
1062 
1063  SCIPdebugMsg(scip, " -> strong branching on variable <%s> already performed (down=%g (%+g), up=%g (%+g), pscostscore=%g)\n",
1064  SCIPvarGetName(branchcands[c]), down, downgain, up, upgain, pscostscore);
1065  }
1066 
1067  score = calcScore(scip, branchruledata, conflictscore, avgconflictscore, conflengthscore, avgconflengthscore,
1068  inferencescore, avginferencescore, cutoffscore, avgcutoffscore, pscostscore, avgpscostscore, nlscore, branchcandsfrac[c],
1069  degeneracyfactor);
1070 
1071  /* check for better score of candidate */
1072  if( SCIPisSumGE(scip, score, bestpsscore) )
1073  {
1074  SCIP_Real fracscore;
1075  SCIP_Real domainscore;
1076 
1077  fracscore = MIN(branchcandsfrac[c], 1.0 - branchcandsfrac[c]);
1078  domainscore = -(SCIPvarGetUbLocal(branchcands[c]) - SCIPvarGetLbLocal(branchcands[c]));
1079  if( SCIPisSumGT(scip, score, bestpsscore)
1080  || SCIPisSumGT(scip, fracscore, bestpsfracscore)
1081  || (SCIPisSumGE(scip, fracscore, bestpsfracscore) && domainscore > bestpsdomainscore) )
1082  {
1083  bestpscand = c;
1084  bestpsscore = score;
1085  bestpsfracscore = fracscore;
1086  bestpsdomainscore = domainscore;
1087  }
1088  }
1089  }
1090  }
1091 
1092  for( c = 0; c < nbranchcands; ++c )
1093  {
1094  SCIP_Real conflictscore;
1095  SCIP_Real conflengthscore;
1096  SCIP_Real inferencescore;
1097  SCIP_Real cutoffscore;
1098  SCIP_Real pscostscore;
1099  SCIP_Real nlscore;
1100  SCIP_Real score;
1101  SCIP_Bool usesb;
1102  SCIP_Real downgain;
1103  SCIP_Real upgain;
1104  SCIP_Real fracpart;
1105 
1106  assert(branchcands[c] != NULL);
1107  assert(!SCIPisFeasIntegral(scip, branchcandssol[c]));
1108  assert(!SCIPisFeasIntegral(scip, SCIPvarGetLPSol(branchcands[c])));
1109 
1110  /* Record the variables current pseudocosts. These may be overwritten if
1111  * strong branching is performed.
1112  */
1113  sbvars[c] = FALSE;
1114  fracpart = SCIPfeasFrac(scip, SCIPvarGetLPSol(branchcands[c]));
1115  downgain = SCIPgetVarPseudocostVal(scip, branchcands[c], 0.0 - fracpart);
1116  upgain = SCIPgetVarPseudocostVal(scip, branchcands[c], 1.0 - fracpart);
1117  mingains[c] = MIN(downgain, upgain);
1118  maxgains[c] = MAX(downgain, upgain);
1119 
1120  /* get conflict, inference, cutoff, nonlinear, and pseudo cost scores for candidate */
1121  conflictscore = SCIPgetVarConflictScore(scip, branchcands[c]);
1122  conflengthscore = SCIPgetVarConflictlengthScore(scip, branchcands[c]);
1123  inferencescore = SCIPgetVarAvgInferenceScore(scip, branchcands[c]);
1124  cutoffscore = SCIPgetVarAvgCutoffScore(scip, branchcands[c]);
1125  nlscore = calcNlscore(scip, branchruledata->nlcount, branchruledata->nlcountmax, SCIPvarGetProbindex(branchcands[c]));
1126  pscostscore = SCIPgetVarPseudocostScore(scip, branchcands[c], branchcandssol[c]);
1127  usesb = FALSE;
1128 
1129  /* don't use strong branching on variables that have already been initialized at the current node;
1130  * instead replace the pseudo cost score with the already calculated one;
1131  * @todo: use old data for strong branching with propagation?
1132  */
1133  if( SCIPgetVarStrongbranchNode(scip, branchcands[c]) == nodenum )
1134  {
1135  SCIP_Real down;
1136  SCIP_Real up;
1137  SCIP_Real lastlpobjval;
1138 
1139  /* use the score of the strong branching call at the current node */
1140  SCIP_CALL( SCIPgetVarStrongbranchLast(scip, branchcands[c], &down, &up, NULL, NULL, NULL, &lastlpobjval) );
1141  downgain = MAX(down - lastlpobjval, 0.0);
1142  upgain = MAX(up - lastlpobjval, 0.0);
1143  pscostscore = SCIPgetBranchScore(scip, branchcands[c], downgain, upgain);
1144 
1145  mingains[c] = MIN(downgain, upgain);
1146  maxgains[c] = MAX(downgain, upgain);
1147 
1148  SCIPdebugMsg(scip, " -> strong branching on variable <%s> already performed (down=%g (%+g), up=%g (%+g), pscostscore=%g)\n",
1149  SCIPvarGetName(branchcands[c]), down, downgain, up, upgain, pscostscore);
1150  }
1151  else if( maxninitcands > 0 )
1152  {
1153  SCIP_Real downsize;
1154  SCIP_Real upsize;
1155  SCIP_Real size;
1156 
1157  /* check, if the pseudo cost score of the variable is reliable */
1158  downsize = SCIPgetVarPseudocostCountCurrentRun(scip, branchcands[c], SCIP_BRANCHDIR_DOWNWARDS);
1159  upsize = SCIPgetVarPseudocostCountCurrentRun(scip, branchcands[c], SCIP_BRANCHDIR_UPWARDS);
1160  size = MIN(downsize, upsize);
1161 
1162  /* determine if variable is considered reliable based on the current reliability setting */
1163  /* check fixed number threshold (aka original) reliability first */
1164  assert(!branchruledata->usehyptestforreliability || bestpscand >= 0);
1165  usesb = FALSE;
1166  if( size < reliable )
1167  usesb = TRUE;
1168  else if( branchruledata->userelerrorforreliability && branchruledata->usehyptestforreliability )
1169  {
1170  if( !SCIPisVarPscostRelerrorReliable(scip, branchcands[c], relerrorthreshold, clevel) &&
1171  !SCIPsignificantVarPscostDifference(scip, branchcands[bestpscand], branchcandsfrac[bestpscand],
1172  branchcands[c], branchcandsfrac[c], SCIP_BRANCHDIR_DOWNWARDS, clevel, TRUE) &&
1173  !SCIPsignificantVarPscostDifference(scip, branchcands[bestpscand], 1 - branchcandsfrac[bestpscand],
1174  branchcands[c], 1 - branchcandsfrac[c], SCIP_BRANCHDIR_UPWARDS, clevel, TRUE) )
1175  usesb = TRUE;
1176  }
1177  /* check if relative error is tolerable */
1178  else if( branchruledata->userelerrorforreliability &&
1179  !SCIPisVarPscostRelerrorReliable(scip, branchcands[c], relerrorthreshold, clevel))
1180  usesb = TRUE;
1181  /* check if best pseudo-candidate is significantly better in both directions, use strong-branching otherwise */
1182  else if( branchruledata->usehyptestforreliability &&
1183  !SCIPsignificantVarPscostDifference(scip, branchcands[bestpscand], branchcandsfrac[bestpscand],
1184  branchcands[c], branchcandsfrac[c], SCIP_BRANCHDIR_DOWNWARDS, clevel, TRUE) &&
1185  !SCIPsignificantVarPscostDifference(scip, branchcands[bestpscand], 1 - branchcandsfrac[bestpscand],
1186  branchcands[c], 1 - branchcandsfrac[c], SCIP_BRANCHDIR_UPWARDS, clevel, TRUE))
1187  usesb = TRUE;
1188 
1189  /* count the number of variables that are completely uninitialized */
1190  if( size < 0.1 )
1191  nuninitcands++;
1192  }
1193 
1194  /* combine the five score values */
1195  scoresfrompc[c] = calcScore(scip, branchruledata, 0.0, avgconflictscore, 0.0, avgconflengthscore,
1196  0.0, avginferencescore, 0.0, avgcutoffscore, pscostscore, avgpscostscore, 0.0, branchcandsfrac[c], degeneracyfactor);
1197  scoresfromothers[c] = calcScore(scip, branchruledata, conflictscore, avgconflictscore, conflengthscore, avgconflengthscore,
1198  inferencescore, avginferencescore, cutoffscore, avgcutoffscore, 0.0, avgpscostscore, nlscore, branchcandsfrac[c], degeneracyfactor);
1199  score = scoresfrompc[c] + scoresfromothers[c];
1200  scores[c] = score;
1201  /*score = calcScore(scip, branchruledata, conflictscore, avgconflictscore, conflengthscore, avgconflengthscore,
1202  inferencescore, avginferencescore, cutoffscore, avgcutoffscore, pscostscore, avgpscostscore, nlscore, branchcandsfrac[c],
1203  degeneracyfactor);*/
1204  if( usesb )
1205  {
1206  int j;
1207 
1208  mingains[c] = 0;
1209  maxgains[c] = 0;
1210  scoresfrompc[c] = 0;
1211  scoresfromothers[c] = 0;
1212 
1213  /* assign a random score to this uninitialized candidate */
1214  if( branchruledata->randinitorder )
1215  score += SCIPrandomGetReal(branchruledata->randnumgen, 0.0, 1e-4);
1216 
1217  /* pseudo cost of variable is not reliable: insert candidate in initcands buffer */
1218  for( j = ninitcands; j > 0 && score > initcandscores[j-1]; --j )
1219  {
1220  initcands[j] = initcands[j-1];
1221  initcandscores[j] = initcandscores[j-1];
1222  }
1223  initcands[j] = c;
1224  initcandscores[j] = score;
1225  ninitcands++;
1226  ninitcands = MIN(ninitcands, maxninitcands);
1227  }
1228  /* in the case of hypothesis reliability, the best pseudo candidate has been determined already */
1229  else if( !branchruledata->usehyptestforreliability )
1230  {
1231  /* variable will keep its pseudo cost value: check for better score of candidate */
1232  if( SCIPisSumGE(scip, score, bestpsscore) )
1233  {
1234  SCIP_Real fracscore;
1235  SCIP_Real domainscore;
1236 
1237  fracscore = MIN(branchcandsfrac[c], 1.0 - branchcandsfrac[c]);
1238  domainscore = -(SCIPvarGetUbLocal(branchcands[c]) - SCIPvarGetLbLocal(branchcands[c]));
1239  if( SCIPisSumGT(scip, score, bestpsscore)
1240  || SCIPisSumGT(scip, fracscore, bestpsfracscore)
1241  || (SCIPisSumGE(scip, fracscore, bestpsfracscore) && domainscore > bestpsdomainscore) )
1242  {
1243  bestpscand = c;
1244  bestpsscore = score;
1245  bestpsfracscore = fracscore;
1246  bestpsdomainscore = domainscore;
1247  }
1248  }
1249  }
1250  }
1251 
1252  /* in the special case that only the best pseudo candidate was selected for strong branching, skip the strong branching */
1253  if( branchruledata->usehyptestforreliability && ninitcands == 1 )
1254  {
1255  ninitcands = 0;
1256  SCIPdebugMsg(scip, "Only one single candidate for initialization-->Skipping strong branching\n");
1257  }
1258 
1259  /* initialize unreliable candidates with strong branching until maxlookahead is reached,
1260  * search best strong branching candidate
1261  */
1262  maxlookahead = (SCIP_Real)branchruledata->maxlookahead * (1.0 + (SCIP_Real)nuninitcands/(SCIP_Real)nbranchcands);
1263  inititer = branchruledata->inititer;
1264  if( inititer == 0 )
1265  {
1266  SCIP_Longint nlpiterations;
1267  SCIP_Longint nlps;
1268 
1269  /* iteration limit is set to twice the average number of iterations spent to resolve a dual feasible SCIP_LP;
1270  * at the first few nodes, this average is not very exact, so we better increase the iteration limit on
1271  * these very important nodes
1272  */
1273  nlpiterations = SCIPgetNDualResolveLPIterations(scip);
1274  nlps = SCIPgetNDualResolveLPs(scip);
1275  if( nlps == 0 )
1276  {
1277  nlpiterations = SCIPgetNNodeInitLPIterations(scip);
1278  nlps = SCIPgetNNodeInitLPs(scip);
1279  if( nlps == 0 )
1280  {
1281  nlpiterations = 1000;
1282  nlps = 1;
1283  }
1284  }
1285  assert(nlps >= 1);
1286  inititer = (int)(2*nlpiterations / nlps);
1287  inititer = (int)((SCIP_Real)inititer * (1.0 + 20.0/nodenum));
1288  inititer = MAX(inititer, 10);
1289  inititer = MIN(inititer, 500);
1290  }
1291 
1292  SCIPdebugMsg(scip, "strong branching (reliable=%g, %d/%d cands, %d uninit, maxcands=%d, maxlookahead=%g, maxbdchgs=%d, inititer=%d, iterations:%" SCIP_LONGINT_FORMAT "/%" SCIP_LONGINT_FORMAT ", basic:%u)\n",
1293  reliable, ninitcands, nbranchcands, nuninitcands, maxninitcands, maxlookahead, maxbdchgs, inititer,
1294  SCIPgetNStrongbranchLPIterations(scip), maxnsblpiterations, SCIPisLPSolBasic(scip));
1295 
1296  bestsbcand = -1;
1297  bestsbscore = -SCIPinfinity(scip);
1298  bestsbfracscore = -SCIPinfinity(scip);
1299  bestsbdomainscore = -SCIPinfinity(scip);
1300  bestuninitsbscore = -SCIPinfinity(scip);
1301  bestuninitsbcand = -1;
1302  lookahead = 0.0;
1303  for( i = 0; i < ninitcands && lookahead < maxlookahead && nbdchgs + nbdconflicts < maxbdchgs
1304  && (i < (int) maxlookahead || SCIPgetNStrongbranchLPIterations(scip) < maxnsblpiterations); ++i )
1305  {
1306  SCIP_Real down;
1307  SCIP_Real up;
1308  SCIP_Real downgain;
1309  SCIP_Real upgain;
1310  SCIP_Bool downvalid;
1311  SCIP_Bool upvalid;
1312  SCIP_Longint ndomredsdown;
1313  SCIP_Longint ndomredsup;
1314  SCIP_Bool lperror;
1315  SCIP_Bool downinf;
1316  SCIP_Bool upinf;
1317  SCIP_Bool downconflict;
1318  SCIP_Bool upconflict;
1319 
1320  /* get candidate number to initialize */
1321  c = initcands[i];
1322  assert(!SCIPisFeasIntegral(scip, branchcandssol[c]));
1323 
1324  if( branchruledata->skipbadinitcands )
1325  {
1326  SCIP_Bool skipsb = FALSE;
1327  /* if the current best candidate is a candidate found by strong branching, determine if candidate pseudo-costs are
1328  * significantly smaller in at least one direction, in which case we safe the execution of strong-branching for now
1329  */
1330  if( bestsbscore > bestpsscore && bestsbscore > bestuninitsbscore && bestsbupvalid && bestsbdownvalid )
1331  {
1332  assert(bestsbcand != -1);
1333  assert(bestsbup != SCIP_INVALID && bestsbdown != SCIP_INVALID); /*lint !e777 lint doesn't like comparing floats */
1334 
1335  /* test if the variable is unlikely to produce a better gain than the currently best one. Skip strong-branching
1336  * in such a case
1337  */
1338  if( SCIPpscostThresholdProbabilityTest(scip, branchcands[c], branchcandsfrac[c], bestsbdown,
1339  SCIP_BRANCHDIR_DOWNWARDS, clevel)
1340  || SCIPpscostThresholdProbabilityTest(scip, branchcands[c], 1.0 - branchcandsfrac[c], bestsbup,
1341  SCIP_BRANCHDIR_UPWARDS, clevel) )
1342  skipsb = TRUE;
1343  }
1344  /* the currently best candidate is also a pseudo-candidate; apply significance test and skip candidate if it
1345  * is significantly worse in at least one direction
1346  */
1347  else if( bestpscand != -1 && bestpsscore > bestuninitsbscore )
1348  {
1349  if( SCIPsignificantVarPscostDifference(scip, branchcands[bestpscand], branchcandsfrac[bestpscand],
1350  branchcands[c], branchcandsfrac[c], SCIP_BRANCHDIR_DOWNWARDS, clevel, TRUE)
1351  || SCIPsignificantVarPscostDifference(scip, branchcands[bestpscand], 1.0 - branchcandsfrac[bestpscand],
1352  branchcands[c], 1.0 - branchcandsfrac[c], SCIP_BRANCHDIR_UPWARDS, clevel, TRUE) )
1353  skipsb = TRUE;
1354  }
1355  /* compare against the best init cand that has been skipped already */
1356  else if( bestuninitsbcand != -1 )
1357  {
1358  if( SCIPsignificantVarPscostDifference(scip, branchcands[bestuninitsbcand], branchcandsfrac[bestuninitsbcand],
1359  branchcands[c], branchcandsfrac[c], SCIP_BRANCHDIR_DOWNWARDS, clevel, TRUE)
1360  || SCIPsignificantVarPscostDifference(scip, branchcands[bestuninitsbcand], 1.0 - branchcandsfrac[bestuninitsbcand],
1361  branchcands[c], 1.0 - branchcandsfrac[c], SCIP_BRANCHDIR_UPWARDS, clevel, TRUE) )
1362  skipsb = TRUE;
1363  }
1364 
1365  /* skip candidate, update the best score of an unitialized candidate */
1366  if( skipsb )
1367  {
1368  if( bestuninitsbcand == -1 )
1369  {
1370  bestuninitsbcand = c;
1371  bestuninitsbscore = initcandscores[i];
1372  }
1373  continue;
1374  }
1375  }
1376  SCIPdebugMsg(scip, "init pseudo cost (%g/%g) of <%s> at %g (score:%g) with strong branching (%d iterations) -- %" SCIP_LONGINT_FORMAT "/%" SCIP_LONGINT_FORMAT " iterations\n",
1377  SCIPgetVarPseudocostCountCurrentRun(scip, branchcands[c], SCIP_BRANCHDIR_DOWNWARDS),
1378  SCIPgetVarPseudocostCountCurrentRun(scip, branchcands[c], SCIP_BRANCHDIR_UPWARDS),
1379  SCIPvarGetName(branchcands[c]), branchcandssol[c], initcandscores[i],
1380  inititer, SCIPgetNStrongbranchLPIterations(scip), maxnsblpiterations);
1381 
1382  /* use strong branching on candidate */
1383  if( !initstrongbranching )
1384  {
1385  initstrongbranching = TRUE;
1386 
1387  SCIP_CALL( SCIPstartStrongbranch(scip, propagate) );
1388 
1389  /* create arrays for probing-like bound tightening */
1390  if( probingbounds )
1391  {
1392  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &newlbs, nvars) );
1393  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &newubs, nvars) );
1394  }
1395  }
1396 
1397  if( propagate )
1398  {
1399  /* apply strong branching */
1400  SCIP_CALL( SCIPgetVarStrongbranchWithPropagation(scip, branchcands[c], branchcandssol[c], lpobjval, inititer,
1401  branchruledata->maxproprounds, &down, &up, &downvalid, &upvalid, &ndomredsdown, &ndomredsup, &downinf, &upinf,
1402  &downconflict, &upconflict, &lperror, newlbs, newubs) );
1403  }
1404  else
1405  {
1406  /* apply strong branching */
1407  SCIP_CALL( SCIPgetVarStrongbranchFrac(scip, branchcands[c], inititer, FALSE,
1408  &down, &up, &downvalid, &upvalid, &downinf, &upinf, &downconflict, &upconflict, &lperror) );
1409 
1410  ndomredsdown = ndomredsup = 0;
1411  }
1412 
1413  /* check for an error in strong branching */
1414  if( lperror )
1415  {
1416  if( !SCIPisStopped(scip) )
1417  {
1418  SCIPverbMessage(scip, SCIP_VERBLEVEL_HIGH, NULL,
1419  "(node %" SCIP_LONGINT_FORMAT ") error in strong branching call for variable <%s> with solution %g\n",
1420  SCIPgetNNodes(scip), SCIPvarGetName(branchcands[c]), branchcandssol[c]);
1421  }
1422  break;
1423  }
1424 
1425  /* Strong branching might have found a new primal solution which updated the cutoff bound. In this case, the
1426  * provedbound computed before can be higher than the cutoffbound and the current node can be cut off.
1427  * Additionally, also if the value for the current best candidate is valid and exceeds the new cutoff bound,
1428  * we want to change the domain of this variable rather than branching on it.
1429  */
1430  if( SCIPgetBestSol(scip) != NULL && SCIPsolGetIndex(SCIPgetBestSol(scip)) != bestsolidx )
1431  {
1432  bestsolidx = SCIPsolGetIndex(SCIPgetBestSol(scip));
1433 
1434  SCIPdebugMsg(scip, " -> strong branching on variable <%s> lead to a new incumbent\n",
1435  SCIPvarGetName(branchcands[c]));
1436 
1437  /* proved bound for current node is larger than new cutoff bound -> cut off current node */
1438  if( SCIPisGE(scip, provedbound, SCIPgetCutoffbound(scip)) )
1439  {
1440  SCIPdebugMsg(scip, " -> node can be cut off (provedbound=%g, cutoff=%g)\n", provedbound, SCIPgetCutoffbound(scip));
1441 
1442  *result = SCIP_CUTOFF;
1443  break; /* terminate initialization loop, because node is infeasible */
1444  }
1445  /* proved bound for down child of best candidate is larger than cutoff bound
1446  * -> increase lower bound of best candidate
1447  * we must only do this if the LP is complete, i.e., we are not doing column generation
1448  */
1449 
1450  else if( bestsbcand != -1 && allcolsinlp )
1451  {
1452  if( !bestsbdowncutoff && bestsbdownvalid && SCIPisGE(scip, bestsbdown, SCIPgetCutoffbound(scip)) )
1453  {
1454  bestsbdowncutoff = TRUE;
1455 
1456  SCIPdebugMsg(scip, " -> valid dual bound for down child of best candidate <%s> is higher than new cutoff bound (valid=%u, bestsbdown=%g, cutoff=%g)\n",
1457  SCIPvarGetName(branchcands[bestsbcand]), bestsbdownvalid, bestsbdown, SCIPgetCutoffbound(scip));
1458 
1459  SCIPdebugMsg(scip, " -> increase lower bound of best candidate <%s> to %g\n",
1460  SCIPvarGetName(branchcands[bestsbcand]), SCIPfeasCeil(scip, branchcandssol[bestsbcand]));
1461 
1462  SCIP_CALL( addBdchg(scip, &bdchginds, &bdchgtypes, &bdchgbounds, &nbdchgs, SCIPvarGetProbindex(branchcands[bestsbcand]),
1463  SCIP_BOUNDTYPE_LOWER, SCIPfeasCeil(scip, branchcandssol[bestsbcand])) );
1464  }
1465  /* proved bound for up child of best candidate is larger than cutoff bound -> decrease upper bound of best candidate */
1466  else if( !bestsbupcutoff && bestsbupvalid && SCIPisGE(scip, bestsbup, SCIPgetCutoffbound(scip)) )
1467  {
1468  bestsbupcutoff = TRUE;
1469 
1470  SCIPdebugMsg(scip, " -> valid dual bound for up child of best candidate <%s> is higher than new cutoff bound (valid=%u, bestsbup=%g, cutoff=%g)\n",
1471  SCIPvarGetName(branchcands[bestsbcand]), bestsbupvalid, bestsbup, SCIPgetCutoffbound(scip));
1472 
1473  SCIPdebugMsg(scip, " -> decrease upper bound of best candidate <%s> to %g\n",
1474  SCIPvarGetName(branchcands[bestsbcand]), SCIPfeasFloor(scip, branchcandssol[bestsbcand]));
1475 
1476  SCIP_CALL( addBdchg(scip, &bdchginds, &bdchgtypes, &bdchgbounds, &nbdchgs, SCIPvarGetProbindex(branchcands[bestsbcand]),
1477  SCIP_BOUNDTYPE_UPPER, SCIPfeasFloor(scip, branchcandssol[bestsbcand])) );
1478  }
1479  }
1480  }
1481 
1482  /* evaluate strong branching */
1483  down = MAX(down, lpobjval);
1484  up = MAX(up, lpobjval);
1485  downgain = down - lpobjval;
1486  upgain = up - lpobjval;
1487  assert(!allcolsinlp || exactsolve || !downvalid || downinf == SCIPisGE(scip, down, SCIPgetCutoffbound(scip)));
1488  assert(!allcolsinlp || exactsolve || !upvalid || upinf == SCIPisGE(scip, up, SCIPgetCutoffbound(scip)));
1489  assert(downinf || !downconflict);
1490  assert(upinf || !upconflict);
1491 
1492  /* @todo: store pseudo cost only for valid bounds?
1493  * depending on the user parameter choice of storesemiinitcosts, pseudo costs are also updated in single directions,
1494  * if the node in the other direction was infeasible or cut off
1495  */
1496  if( !downinf
1497 #ifdef WITH_LPSOLSTAT
1498  && SCIPgetLastStrongbranchLPSolStat(scip, SCIP_BRANCHDIR_DOWNWARDS) != SCIP_LPSOLSTAT_ITERLIMIT
1499 #endif
1500  && (!upinf || branchruledata->storesemiinitcosts) )
1501  {
1502  SCIP_Real weight;
1503 
1504  /* smaller weights are given if the strong branching hit the time limit in the corresponding direction */
1505  if( branchruledata->usesmallweightsitlim )
1506  weight = SCIPgetLastStrongbranchLPSolStat(scip, SCIP_BRANCHDIR_DOWNWARDS) != SCIP_LPSOLSTAT_ITERLIMIT ? 1.0 : 0.5;
1507  else
1508  weight = 1.0;
1509 
1510  /* update pseudo cost values */
1511  SCIP_CALL( SCIPupdateVarPseudocostSymmetric(scip, branchruledata, branchcands[c], branchorbitidx, c, 0.0 - branchcandsfrac[c], downgain, weight) );
1512  }
1513  if( !upinf
1514 #ifdef WITH_LPSOLSTAT
1515  && SCIPgetLastStrongbranchLPSolStat(scip, SCIP_BRANCHDIR_UPWARDS) != SCIP_LPSOLSTAT_ITERLIMIT
1516 #endif
1517  && (!downinf || branchruledata->storesemiinitcosts) )
1518  {
1519  SCIP_Real weight;
1520 
1521  /* smaller weights are given if the strong branching hit the time limit in the corresponding direction */
1522  if( branchruledata->usesmallweightsitlim )
1523  weight = SCIPgetLastStrongbranchLPSolStat(scip, SCIP_BRANCHDIR_UPWARDS) != SCIP_LPSOLSTAT_ITERLIMIT ? 1.0 : 0.5;
1524  else
1525  weight = 1.0;
1526 
1527  /* update pseudo cost values */
1528  SCIP_CALL( SCIPupdateVarPseudocostSymmetric(scip, branchruledata, branchcands[c], branchorbitidx, c, 1.0 - branchcandsfrac[c], upgain, weight) );
1529  }
1530 
1531  /* the minimal lower bound of both children is a proved lower bound of the current subtree */
1532  if( allcolsinlp && !exactsolve && downvalid && upvalid )
1533  {
1534  SCIP_Real minbound;
1535 
1536  minbound = MIN(down, up);
1537  provedbound = MAX(provedbound, minbound);
1538  assert((downinf && upinf) || SCIPisLT(scip, provedbound, SCIPgetCutoffbound(scip)));
1539 
1540  /* save probing-like bounds detected during strong branching */
1541  if( probingbounds )
1542  {
1543  int v;
1544 
1545  assert(newlbs != NULL);
1546  assert(newubs != NULL);
1547 
1548  for( v = 0; v < nvars; ++v )
1549  {
1550  if( SCIPisGT(scip, newlbs[v], SCIPvarGetLbLocal(vars[v])) )
1551  {
1552  SCIPdebugMsg(scip, "better lower bound for variable <%s>: %.9g -> %.9g (by strongbranching on <%s>)\n",
1553  SCIPvarGetName(vars[v]), SCIPvarGetLbLocal(vars[v]), newlbs[v], SCIPvarGetName(branchcands[c]));
1554 
1555  SCIP_CALL( addBdchg(scip, &bdchginds, &bdchgtypes, &bdchgbounds, &nbdchgs, v,
1556  SCIP_BOUNDTYPE_LOWER, newlbs[v]) );
1557  }
1558  if( SCIPisLT(scip, newubs[v], SCIPvarGetUbLocal(vars[v])) )
1559  {
1560  SCIPdebugMsg(scip, "better upper bound for variable <%s>: %.9g -> %.9g (by strongbranching on <%s>)\n",
1561  SCIPvarGetName(vars[v]), SCIPvarGetUbLocal(vars[v]), newubs[v], SCIPvarGetName(branchcands[c]));
1562 
1563  SCIP_CALL( addBdchg(scip, &bdchginds, &bdchgtypes, &bdchgbounds, &nbdchgs, v,
1564  SCIP_BOUNDTYPE_UPPER, newubs[v]) );
1565  }
1566  }
1567  }
1568  }
1569 
1570  /* check if there are infeasible roundings */
1571  if( downinf || upinf )
1572  {
1573  assert(allcolsinlp || propagate);
1574  assert(!exactsolve);
1575 
1576  if( downinf && upinf )
1577  {
1578  /* both roundings are infeasible -> node is infeasible */
1579  SCIPdebugMsg(scip, " -> variable <%s> is infeasible in both directions (conflict: %u/%u)\n",
1580  SCIPvarGetName(branchcands[c]), downconflict, upconflict);
1581  *result = SCIP_CUTOFF;
1582  break; /* terminate initialization loop, because node is infeasible */
1583  }
1584  else
1585  {
1586  /* rounding is infeasible in one direction -> round variable in other direction */
1587  SCIPdebugMsg(scip, " -> variable <%s> is infeasible in %s branch (conflict: %u/%u)\n",
1588  SCIPvarGetName(branchcands[c]), downinf ? "downward" : "upward", downconflict, upconflict);
1589  SCIP_CALL( addBdchg(scip, &bdchginds, &bdchgtypes, &bdchgbounds, &nbdchgs, SCIPvarGetProbindex(branchcands[c]),
1590  (downinf ? SCIP_BOUNDTYPE_LOWER : SCIP_BOUNDTYPE_UPPER),
1591  (downinf ? SCIPfeasCeil(scip, branchcandssol[c]) : SCIPfeasFloor(scip, branchcandssol[c]))) );
1592  if( nbdchgs + nbdconflicts >= maxbdchgs )
1593  break; /* terminate initialization loop, because enough roundings are performed */
1594  }
1595  }
1596  else
1597  {
1598  SCIP_Real conflictscore;
1599  SCIP_Real conflengthscore;
1600  SCIP_Real inferencescore;
1601  SCIP_Real cutoffscore;
1602  SCIP_Real pscostscore;
1603  SCIP_Real nlscore;
1604  SCIP_Real score;
1605 
1606  mingains[c] = MIN(downgain, upgain);
1607  maxgains[c] = MAX(downgain, upgain);
1608 
1609  sbdown[c] = down;
1610  sbup[c] = up;
1611  sbdownvalid[c] = downvalid;
1612  sbupvalid[c] = upvalid;
1613  sbvars[c] = TRUE;
1614 
1615  /* check for a better score */
1616  conflictscore = SCIPgetVarConflictScore(scip, branchcands[c]);
1617  conflengthscore = SCIPgetVarConflictlengthScore(scip, branchcands[c]);
1618  nlscore = calcNlscore(scip, branchruledata->nlcount, branchruledata->nlcountmax, SCIPvarGetProbindex(branchcands[c]));
1619 
1620  /* optionally, use only local information obtained via strong branching for this candidate, i.e., local
1621  * domain reductions and no cutoff score
1622  */
1623  inferencescore = branchruledata->usesblocalinfo ? SCIPgetBranchScore(scip, branchcands[c], (SCIP_Real)ndomredsdown, (SCIP_Real)ndomredsup)
1624  : SCIPgetVarAvgInferenceScore(scip, branchcands[c]);
1625  cutoffscore = branchruledata->usesblocalinfo ? 0.0 : SCIPgetVarAvgCutoffScore(scip, branchcands[c]);
1626  pscostscore = SCIPgetBranchScore(scip, branchcands[c], downgain, upgain);
1627 
1628  scoresfrompc[c] = calcScore(scip, branchruledata, 0.0, avgconflictscore, 0.0, avgconflengthscore,
1629  0.0, avginferencescore, 0.0, avgcutoffscore, pscostscore, avgpscostscore, 0.0, branchcandsfrac[c], degeneracyfactor);
1630  scoresfromothers[c] = calcScore(scip, branchruledata, conflictscore, avgconflictscore, conflengthscore, avgconflengthscore,
1631  inferencescore, avginferencescore, cutoffscore, avgcutoffscore, 0.0, avgpscostscore, nlscore, branchcandsfrac[c], degeneracyfactor);
1632  score = scoresfrompc[c] + scoresfromothers[c];
1633  scores[c] = score;
1634  /*score = calcScore(scip, branchruledata, conflictscore, avgconflictscore, conflengthscore, avgconflengthscore,
1635  inferencescore, avginferencescore, cutoffscore, avgcutoffscore, pscostscore, avgpscostscore, nlscore, branchcandsfrac[c],
1636  degeneracyfactor);*/
1637 
1638  if( SCIPisSumGE(scip, score, bestsbscore) )
1639  {
1640  SCIP_Real fracscore;
1641  SCIP_Real domainscore;
1642 
1643  fracscore = MIN(branchcandsfrac[c], 1.0 - branchcandsfrac[c]);
1644  domainscore = -(SCIPvarGetUbLocal(branchcands[c]) - SCIPvarGetLbLocal(branchcands[c]));
1645  if( SCIPisSumGT(scip, score, bestsbscore)
1646  || SCIPisSumGT(scip, fracscore, bestsbfracscore)
1647  || (SCIPisSumGE(scip, fracscore, bestsbfracscore) && domainscore > bestsbdomainscore) )
1648  {
1649  bestsbcand = c;
1650  bestsbscore = score;
1651  bestsbdown = down;
1652  bestsbup = up;
1653  bestsbdownvalid = downvalid;
1654  bestsbupvalid = upvalid;
1655  bestsbdowncutoff = FALSE;
1656  bestsbupcutoff = FALSE;
1657  bestsbfracscore = fracscore;
1658  bestsbdomainscore = domainscore;
1659  lookahead = 0.0;
1660  }
1661  else
1662  lookahead += 0.5;
1663  }
1664  else
1665  lookahead += 1.0;
1666 
1667  SCIPdebugMsg(scip, " -> variable <%s> (solval=%g, down=%g (%+g,valid=%u), up=%g (%+g,valid=%u), score=%g/ %g/%g %g/%g -> %g)\n",
1668  SCIPvarGetName(branchcands[c]), branchcandssol[c], down, downgain, downvalid, up, upgain, upvalid,
1669  pscostscore, conflictscore, conflengthscore, inferencescore, cutoffscore, score);
1670  }
1671  }
1672 #ifdef SCIP_DEBUG
1673  if( bestsbcand >= 0 )
1674  {
1675  SCIPdebugMsg(scip, " -> best: <%s> (%g / %g / %g), lookahead=%g/%g\n",
1676  SCIPvarGetName(branchcands[bestsbcand]), bestsbscore, bestsbfracscore, bestsbdomainscore,
1677  lookahead, maxlookahead);
1678  }
1679 #endif
1680 
1681  if( initstrongbranching )
1682  {
1683  if( probingbounds )
1684  {
1685  assert(newlbs != NULL);
1686  assert(newubs != NULL);
1687 
1688  SCIPfreeBlockMemoryArray(scip, &newubs, nvars);
1689  SCIPfreeBlockMemoryArray(scip, &newlbs, nvars);
1690  }
1691 
1692  SCIP_CALL( SCIPendStrongbranch(scip) );
1693 
1694  if( SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OBJLIMIT || SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_INFEASIBLE )
1695  {
1696  assert(SCIPhasCurrentNodeLP(scip));
1697  *result = SCIP_CUTOFF;
1698  }
1699  }
1700 
1701  if( *result != SCIP_CUTOFF )
1702  {
1703  /* get the score of the best uninitialized strong branching candidate */
1704  if( i < ninitcands && bestuninitsbcand == -1 )
1705  bestuninitsbscore = initcandscores[i];
1706 
1707  /* if the best pseudo cost candidate is better than the best uninitialized strong branching candidate,
1708  * compare it to the best initialized strong branching candidate
1709  */
1710  if( bestpsscore > bestuninitsbscore && SCIPisSumGT(scip, bestpsscore, bestsbscore) )
1711  {
1712  bestcand = bestpscand;
1713  bestisstrongbranch = FALSE;
1714  }
1715  else if( bestsbcand >= 0 )
1716  {
1717  bestcand = bestsbcand;
1718  bestisstrongbranch = TRUE;
1719  }
1720  else
1721  {
1722  /* no candidate was initialized, and the best score is the one of the first candidate in the initialization
1723  * queue
1724  */
1725  assert(ninitcands >= 1);
1726  bestcand = initcands[0];
1727  bestisstrongbranch = FALSE;
1728  }
1729 
1730  /* update lower bound of current node */
1731  if( allcolsinlp && !exactsolve )
1732  {
1733  assert(SCIPisLT(scip, provedbound, SCIPgetCutoffbound(scip)));
1734  SCIP_CALL( SCIPupdateNodeLowerbound(scip, SCIPgetCurrentNode(scip), provedbound) );
1735  }
1736  }
1737 
1738  /* apply domain reductions */
1739  if( nbdchgs > 0 )
1740  {
1741  if( *result != SCIP_CUTOFF )
1742  {
1743  SCIP_CALL( applyBdchgs(scip, vars, bdchginds, bdchgtypes, bdchgbounds, nbdchgs, result) );
1744  if( *result != SCIP_CUTOFF )
1745  *result = SCIP_REDUCEDDOM;
1746  }
1747  freeBdchgs(scip, &bdchginds, &bdchgtypes, &bdchgbounds, &nbdchgs);
1748  }
1749 
1750  /* Apply the Treemodel branching rule to potentially select a better branching candidate than the current one. */
1751  if( *result != SCIP_CUTOFF && *result != SCIP_REDUCEDDOM && *result != SCIP_CONSADDED && SCIPtreemodelIsEnabled(scip, branchruledata->treemodel) )
1752  {
1753  SCIP_Real smallpscost;
1754  SCIP_Bool usetreemodel;
1755 
1756  usetreemodel = TRUE;
1757 
1758  /* If the pseudocosts are zero, use SCIPs best variable since the Treemodel is not applicable */
1759  if( SCIPisZero(scip, maxgains[bestcand]))
1760  {
1761  usetreemodel = FALSE;
1762  }
1763 
1764  /* If SCIPs best candidate was selected due to hybrid branching scores
1765  * rather than because of pseudocosts, then we keep it.
1766  */
1767  SCIP_CALL( SCIPgetRealParam(scip, "branching/treemodel/smallpscost", &smallpscost) );
1768  if( usetreemodel == TRUE && avgpscostscore <= smallpscost )
1769  {
1770  int cand;
1771  for( cand = 0; cand < nbranchcands; ++cand )
1772  {
1773  if( scoresfrompc[cand] > scoresfrompc[bestcand] )
1774  {
1775  usetreemodel = FALSE;
1776  break;
1777  }
1778  }
1779  }
1780 
1781  if( usetreemodel == TRUE )
1782  {
1783  SCIP_CALL( SCIPtreemodelSelectCandidate(
1784  scip, /* SCIP data structure */
1785  branchruledata->treemodel, /* branching rule */
1786  branchcands, /* branching candidate storage */
1787  mingains, /* minimum gain of rounding downwards or upwards */
1788  maxgains, /* maximum gain of rounding downwards or upwards */
1789  scoresfromothers, /* scores from other branching methods */
1790  nbranchcands, /* the number of branching candidates */
1791  &bestcand /* the best branching candidate found by SCIP */
1792  ) );
1793  }
1794  }
1795 
1796  /* free buffer for the lp gains and pseudocost scores */
1797  SCIPfreeBufferArray(scip, &scoresfromothers);
1798  SCIPfreeBufferArray(scip, &scoresfrompc);
1799  SCIPfreeBufferArray(scip, &scores);
1800  SCIPfreeBufferArray(scip, &maxgains);
1801  SCIPfreeBufferArray(scip, &mingains);
1802 
1803  /* free buffer for the unreliable candidates */
1804  SCIPfreeBufferArray(scip, &initcandscores);
1805  SCIPfreeBufferArray(scip, &initcands);
1806  }
1807 
1808  /* if no domain could be reduced, create the branching */
1809  if( *result != SCIP_CUTOFF && *result != SCIP_REDUCEDDOM && *result != SCIP_CONSADDED && executebranch )
1810  {
1811  SCIP_NODE* downchild;
1812  SCIP_NODE* upchild;
1813  SCIP_VAR* var;
1814  SCIP_Real val;
1815 
1816  assert(*result == SCIP_DIDNOTRUN);
1817  assert(0 <= bestcand && bestcand < nbranchcands);
1818  assert(!SCIPisFeasIntegral(scip, branchcandssol[bestcand]));
1819  assert(!allcolsinlp || SCIPisLT(scip, provedbound, SCIPgetCutoffbound(scip)));
1820  assert(!bestsbdowncutoff && !bestsbupcutoff);
1821 
1822  var = branchcands[bestcand];
1823  val = branchcandssol[bestcand];
1824 
1825  /* perform the branching */
1826  SCIPdebugMsg(scip, " -> %d (%d) cands, sel cand %d: var <%s> (sol=%g, down=%g (%+g), up=%g (%+g), sb=%u, psc=%g/%g [%g])\n",
1827  nbranchcands, ninitcands, bestcand, SCIPvarGetName(var), branchcandssol[bestcand],
1828  bestsbdown, bestsbdown - lpobjval, bestsbup, bestsbup - lpobjval, bestisstrongbranch,
1829  SCIPgetVarPseudocostCurrentRun(scip, var, SCIP_BRANCHDIR_DOWNWARDS),
1830  SCIPgetVarPseudocostCurrentRun(scip, var, SCIP_BRANCHDIR_UPWARDS),
1831  SCIPgetVarPseudocostScoreCurrentRun(scip, var, branchcandssol[bestcand]));
1832  SCIP_UNUSED(bestisstrongbranch);
1833  SCIP_CALL( SCIPbranchVarVal(scip, var, val, &downchild, NULL, &upchild) );
1834  assert(downchild != NULL);
1835  assert(upchild != NULL);
1836 
1837  /* update the lower bounds in the children */
1838  if( sbvars[bestcand] && allcolsinlp && !exactsolve )
1839  {
1840  if( sbdownvalid[bestcand] )
1841  {
1842  assert(SCIPisLT(scip, sbdown[bestcand], SCIPgetCutoffbound(scip)));
1843  SCIP_CALL( SCIPupdateNodeLowerbound(scip, downchild, sbdown[bestcand]) );
1844  assert(SCIPisGE(scip, SCIPgetNodeLowerbound(scip, downchild), provedbound));
1845  }
1846  if( sbupvalid[bestcand] )
1847  {
1848  assert(SCIPisLT(scip, sbup[bestcand], SCIPgetCutoffbound(scip)));
1849  SCIP_CALL( SCIPupdateNodeLowerbound(scip, upchild, sbup[bestcand]) );
1850  assert(SCIPisGE(scip, SCIPgetNodeLowerbound(scip, upchild), provedbound));
1851  }
1852  }
1853 
1854  SCIPdebugMsg(scip, " -> down child's lowerbound: %g\n", SCIPnodeGetLowerbound(downchild));
1855  SCIPdebugMsg(scip, " -> up child's lowerbound : %g\n", SCIPnodeGetLowerbound(upchild));
1856 
1857  assert(SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_INFEASIBLE && SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OBJLIMIT);
1858 
1859  *result = SCIP_BRANCHED;
1860  }
1861 
1862  /* free buffer for the strong branching lp gains */
1863  SCIPfreeBufferArray(scip, &sbvars);
1864  SCIPfreeBufferArray(scip, &sbupvalid);
1865  SCIPfreeBufferArray(scip, &sbdownvalid);
1866  SCIPfreeBufferArray(scip, &sbup);
1867  SCIPfreeBufferArray(scip, &sbdown);
1868 
1869  return SCIP_OKAY;
1870 }
1871 
1872 
1873 /*
1874  * Callback methods
1875  */
1876 
1877 /** copy method for branchrule plugins (called when SCIP copies plugins) */
1878 static
1879 SCIP_DECL_BRANCHCOPY(branchCopyRelpscost)
1880 { /*lint --e{715}*/
1881  assert(scip != NULL);
1882  assert(branchrule != NULL);
1883  assert(strcmp(SCIPbranchruleGetName(branchrule), BRANCHRULE_NAME) == 0);
1884 
1885  /* call inclusion method of branchrule */
1886  SCIP_CALL( SCIPincludeBranchruleRelpscost(scip) );
1887 
1888  return SCIP_OKAY;
1889 }
1890 
1891 /** destructor of branching rule to free user data (called when SCIP is exiting) */
1892 static
1893 SCIP_DECL_BRANCHFREE(branchFreeRelpscost)
1894 { /*lint --e{715}*/
1895  SCIP_BRANCHRULEDATA* branchruledata;
1896  branchruledata = SCIPbranchruleGetData(branchrule);
1897 
1898  /* free Treemodel parameter data structure */
1899  SCIP_CALL( SCIPtreemodelFree(scip, &branchruledata->treemodel) );
1900 
1901  /* free branching rule data */
1902  SCIPfreeBlockMemory(scip, &branchruledata);
1903  SCIPbranchruleSetData(branchrule, NULL);
1904 
1905  return SCIP_OKAY;
1906 }
1907 
1908 
1909 /** solving process initialization method of branching rule (called when branch and bound process is about to begin) */
1910 static
1911 SCIP_DECL_BRANCHINITSOL(branchInitsolRelpscost)
1912 { /*lint --e{715}*/
1913  SCIP_BRANCHRULEDATA* branchruledata;
1914 
1915  /* initialize branching rule data */
1916  branchruledata = SCIPbranchruleGetData(branchrule);
1917  branchruledata->nlcount = NULL;
1918  branchruledata->nlcountsize = 0;
1919  branchruledata->nlcountmax = 1;
1920  assert(branchruledata->startrandseed >= 0);
1921 
1922  /* create a random number generator */
1923  SCIP_CALL( SCIPcreateRandom(scip, &branchruledata->randnumgen,
1924  (unsigned int)branchruledata->startrandseed, TRUE) );
1925 
1926  return SCIP_OKAY;
1927 }
1928 
1929 
1930 /** solving process deinitialization method of branching rule (called before branch and bound process data is freed) */
1931 static
1932 SCIP_DECL_BRANCHEXITSOL(branchExitsolRelpscost)
1933 { /*lint --e{715}*/
1934  SCIP_BRANCHRULEDATA* branchruledata;
1935 
1936  /* free memory in branching rule data */
1937  branchruledata = SCIPbranchruleGetData(branchrule);
1938  SCIPfreeBlockMemoryArrayNull(scip, &branchruledata->nlcount, branchruledata->nlcountsize);
1939 
1940  /* free random number generator */
1941  SCIPfreeRandom(scip, &branchruledata->randnumgen);
1942 
1943  SCIPfreeBlockMemoryArrayNull(scip, &branchruledata->orbitrep, branchruledata->npermvars);
1944  SCIPfreeBlockMemoryArrayNull(scip, &branchruledata->varorbitmap, branchruledata->npermvars);
1945  SCIPfreeBlockMemoryArrayNull(scip, &branchruledata->orbitbegins, branchruledata->npermvars);
1946  SCIPfreeBlockMemoryArrayNull(scip, &branchruledata->orbits, branchruledata->npermvars);
1947  branchruledata->nosymmetry = FALSE;
1948  branchruledata->norbits = 0;
1949  branchruledata->permvars = NULL;
1950  branchruledata->permvarmap = NULL;
1951  branchruledata->npermvars = 0;
1952 
1953  return SCIP_OKAY;
1954 }
1955 
1956 
1957 /** branching execution method for fractional LP solutions */
1958 static
1959 SCIP_DECL_BRANCHEXECLP(branchExeclpRelpscost)
1960 { /*lint --e{715}*/
1961  SCIP_BRANCHRULEDATA* branchruledata;
1962  SCIP_VAR** lpcands;
1963  SCIP_Real* lpcandssol;
1964  SCIP_Real* lpcandsfrac;
1965  SCIP_VAR** filteredlpcands;
1966  SCIP_Real* filteredlpcandssol;
1967  SCIP_Real* filteredlpcandsfrac;
1968  SCIP_Bool runfiltering;
1969  int* filteredlpcandsorbitidx = NULL;
1970  int nfilteredlpcands;
1971  int nlpcands;
1972 
1973  assert(branchrule != NULL);
1974  assert(strcmp(SCIPbranchruleGetName(branchrule), BRANCHRULE_NAME) == 0);
1975  assert(scip != NULL);
1976  assert(result != NULL);
1977 
1978  SCIPdebugMsg(scip, "Execlp method of relpscost branching in node %" SCIP_LONGINT_FORMAT "\n", SCIPnodeGetNumber(SCIPgetCurrentNode(scip)));
1979 
1980  if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
1981  {
1982  *result = SCIP_DIDNOTRUN;
1983  SCIPdebugMsg(scip, "Could not apply relpscost branching, as the current LP was not solved to optimality.\n");
1984 
1985  return SCIP_OKAY;
1986  }
1987 
1988  /* get branching candidates */
1989  SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, NULL, &nlpcands, NULL) );
1990  assert(nlpcands > 0);
1991 
1992  branchruledata = SCIPbranchruleGetData(branchrule);
1993  assert(branchruledata != NULL);
1994 
1995  /* determine whether we should run filtering */
1996  runfiltering = ! branchruledata->nosymmetry && branchruledata->filtercandssym && SCIPgetSubscipDepth(scip) == 0 && ! SCIPinDive(scip) && ! SCIPinProbing(scip);
1997 
1998  /* init orbits if necessary */
1999  if( runfiltering )
2000  {
2001  SCIP_CALL( initOrbits(scip, branchruledata) );
2002  }
2003 
2004  /* determine fractional variables (possibly filter by using symmetries) */
2005  if( runfiltering && branchruledata->norbits != 0 )
2006  {
2007  SCIP_CALL( SCIPallocBufferArray(scip, &filteredlpcands, nlpcands) );
2008  SCIP_CALL( SCIPallocBufferArray(scip, &filteredlpcandssol, nlpcands) );
2009  SCIP_CALL( SCIPallocBufferArray(scip, &filteredlpcandsfrac, nlpcands) );
2010  SCIP_CALL( SCIPallocBufferArray(scip, &filteredlpcandsorbitidx, nlpcands) );
2011 
2012  /* determine filtered fractional variables */
2013  SCIP_CALL( filterSymmetricVariables(scip, branchruledata, lpcands, lpcandssol, lpcandsfrac, nlpcands,
2014  filteredlpcands, filteredlpcandssol, filteredlpcandsfrac, filteredlpcandsorbitidx, &nfilteredlpcands) );
2015  }
2016  else
2017  {
2018  /* No orbits available. Copy all (unfiltered) branching candidates, because they will be updated w.r.t. the strong branching LP solution */
2019  SCIP_CALL( SCIPduplicateBufferArray(scip, &filteredlpcands, lpcands, nlpcands) );
2020  SCIP_CALL( SCIPduplicateBufferArray(scip, &filteredlpcandssol, lpcandssol, nlpcands) );
2021  SCIP_CALL( SCIPduplicateBufferArray(scip, &filteredlpcandsfrac, lpcandsfrac, nlpcands) );
2022  nfilteredlpcands = nlpcands;
2023  }
2024 
2025  /* execute branching rule */
2026  SCIP_CALL( execRelpscost(scip, branchrule, filteredlpcands, filteredlpcandssol, filteredlpcandsfrac, filteredlpcandsorbitidx, nfilteredlpcands, TRUE, result) );
2027 
2028  SCIPfreeBufferArrayNull(scip, &filteredlpcandsorbitidx);
2029  SCIPfreeBufferArray(scip, &filteredlpcandsfrac);
2030  SCIPfreeBufferArray(scip, &filteredlpcandssol);
2031  SCIPfreeBufferArray(scip, &filteredlpcands);
2032 
2033  return SCIP_OKAY;
2034 }
2035 
2036 
2037 /*
2038  * branching specific interface methods
2039  */
2040 
2041 /** creates the reliable pseudo cost branching rule and includes it in SCIP */
2042 SCIP_RETCODE SCIPincludeBranchruleRelpscost(
2043  SCIP* scip /**< SCIP data structure */
2044  )
2045 {
2046  SCIP_BRANCHRULEDATA* branchruledata;
2047  SCIP_BRANCHRULE* branchrule;
2048 
2049  /* create relpscost branching rule data */
2050  SCIP_CALL( SCIPallocBlockMemory(scip, &branchruledata) );
2051 
2052  branchruledata->nosymmetry = FALSE;
2053  branchruledata->orbits = NULL;
2054  branchruledata->orbitbegins = NULL;
2055  branchruledata->orbitrep = NULL;
2056  branchruledata->varorbitmap = NULL;
2057  branchruledata->norbits = 0;
2058  branchruledata->permvars = NULL;
2059  branchruledata->npermvars = 0;
2060  branchruledata->permvarmap = NULL;
2061 
2062  /* include branching rule */
2063  SCIP_CALL( SCIPincludeBranchruleBasic(scip, &branchrule, BRANCHRULE_NAME, BRANCHRULE_DESC, BRANCHRULE_PRIORITY,
2064  BRANCHRULE_MAXDEPTH, BRANCHRULE_MAXBOUNDDIST, branchruledata) );
2065 
2066  assert(branchrule != NULL);
2067 
2068  /* set non-fundamental callbacks via specific setter functions*/
2069  SCIP_CALL( SCIPsetBranchruleCopy(scip, branchrule, branchCopyRelpscost) );
2070  SCIP_CALL( SCIPsetBranchruleFree(scip, branchrule, branchFreeRelpscost) );
2071  SCIP_CALL( SCIPsetBranchruleInitsol(scip, branchrule, branchInitsolRelpscost) );
2072  SCIP_CALL( SCIPsetBranchruleExitsol(scip, branchrule, branchExitsolRelpscost) );
2073  SCIP_CALL( SCIPsetBranchruleExecLp(scip, branchrule, branchExeclpRelpscost) );
2074 
2075  /* relpscost branching rule parameters */
2076  SCIP_CALL( SCIPaddRealParam(scip,
2077  "branching/relpscost/conflictweight",
2078  "weight in score calculations for conflict score",
2079  &branchruledata->conflictweight, TRUE, DEFAULT_CONFLICTWEIGHT, SCIP_REAL_MIN, SCIP_REAL_MAX, NULL, NULL) );
2080  SCIP_CALL( SCIPaddRealParam(scip,
2081  "branching/relpscost/conflictlengthweight",
2082  "weight in score calculations for conflict length score",
2083  &branchruledata->conflengthweight, TRUE, DEFAULT_CONFLENGTHWEIGHT, SCIP_REAL_MIN, SCIP_REAL_MAX, NULL, NULL) );
2084  SCIP_CALL( SCIPaddRealParam(scip,
2085  "branching/relpscost/inferenceweight",
2086  "weight in score calculations for inference score",
2087  &branchruledata->inferenceweight, TRUE, DEFAULT_INFERENCEWEIGHT, SCIP_REAL_MIN, SCIP_REAL_MAX, NULL, NULL) );
2088  SCIP_CALL( SCIPaddRealParam(scip,
2089  "branching/relpscost/cutoffweight",
2090  "weight in score calculations for cutoff score",
2091  &branchruledata->cutoffweight, TRUE, DEFAULT_CUTOFFWEIGHT, SCIP_REAL_MIN, SCIP_REAL_MAX, NULL, NULL) );
2092  SCIP_CALL( SCIPaddRealParam(scip,
2093  "branching/relpscost/pscostweight",
2094  "weight in score calculations for pseudo cost score",
2095  &branchruledata->pscostweight, TRUE, DEFAULT_PSCOSTWEIGHT, SCIP_REAL_MIN, SCIP_REAL_MAX, NULL, NULL) );
2096  SCIP_CALL( SCIPaddRealParam(scip,
2097  "branching/relpscost/nlscoreweight",
2098  "weight in score calculations for nlcount score",
2099  &branchruledata->nlscoreweight, TRUE, DEFAULT_NLSCOREWEIGHT, SCIP_REAL_MIN, SCIP_REAL_MAX, NULL, NULL) );
2100  SCIP_CALL( SCIPaddRealParam(scip,
2101  "branching/relpscost/minreliable",
2102  "minimal value for minimum pseudo cost size to regard pseudo cost value as reliable",
2103  &branchruledata->minreliable, TRUE, DEFAULT_MINRELIABLE, 0.0, SCIP_REAL_MAX, NULL, NULL) );
2104  SCIP_CALL( SCIPaddRealParam(scip,
2105  "branching/relpscost/maxreliable",
2106  "maximal value for minimum pseudo cost size to regard pseudo cost value as reliable",
2107  &branchruledata->maxreliable, TRUE, DEFAULT_MAXRELIABLE, 0.0, SCIP_REAL_MAX, NULL, NULL) );
2108  SCIP_CALL( SCIPaddRealParam(scip,
2109  "branching/relpscost/sbiterquot",
2110  "maximal fraction of strong branching LP iterations compared to node relaxation LP iterations",
2111  &branchruledata->sbiterquot, FALSE, DEFAULT_SBITERQUOT, 0.0, SCIP_REAL_MAX, NULL, NULL) );
2112  SCIP_CALL( SCIPaddIntParam(scip,
2113  "branching/relpscost/sbiterofs",
2114  "additional number of allowed strong branching LP iterations",
2115  &branchruledata->sbiterofs, FALSE, DEFAULT_SBITEROFS, 0, INT_MAX, NULL, NULL) );
2116  SCIP_CALL( SCIPaddIntParam(scip,
2117  "branching/relpscost/maxlookahead",
2118  "maximal number of further variables evaluated without better score",
2119  &branchruledata->maxlookahead, TRUE, DEFAULT_MAXLOOKAHEAD, 1, INT_MAX, NULL, NULL) );
2120  SCIP_CALL( SCIPaddIntParam(scip,
2121  "branching/relpscost/initcand",
2122  "maximal number of candidates initialized with strong branching per node",
2123  &branchruledata->initcand, FALSE, DEFAULT_INITCAND, 0, INT_MAX, NULL, NULL) );
2124  SCIP_CALL( SCIPaddIntParam(scip,
2125  "branching/relpscost/inititer",
2126  "iteration limit for strong branching initializations of pseudo cost entries (0: auto)",
2127  &branchruledata->inititer, FALSE, DEFAULT_INITITER, 0, INT_MAX, NULL, NULL) );
2128  SCIP_CALL( SCIPaddIntParam(scip,
2129  "branching/relpscost/maxbdchgs",
2130  "maximal number of bound tightenings before the node is reevaluated (-1: unlimited)",
2131  &branchruledata->maxbdchgs, TRUE, DEFAULT_MAXBDCHGS, -1, INT_MAX, NULL, NULL) );
2132  SCIP_CALL( SCIPaddIntParam(scip,
2133  "branching/relpscost/maxproprounds",
2134  "maximum number of propagation rounds to be performed during strong branching before solving the LP (-1: no limit, -2: parameter settings)",
2135  &branchruledata->maxproprounds, TRUE, DEFAULT_MAXPROPROUNDS, -2, INT_MAX, NULL, NULL) );
2136  SCIP_CALL( SCIPaddBoolParam(scip,
2137  "branching/relpscost/probingbounds",
2138  "should valid bounds be identified in a probing-like fashion during strong branching (only with propagation)?",
2139  &branchruledata->probingbounds, TRUE, DEFAULT_PROBINGBOUNDS, NULL, NULL) );
2140 
2141  SCIP_CALL( SCIPaddBoolParam(scip, "branching/relpscost/userelerrorreliability",
2142  "should reliability be based on relative errors?", &branchruledata->userelerrorforreliability, TRUE, DEFAULT_USERELERRORFORRELIABILITY,
2143  NULL, NULL) );
2144 
2145  SCIP_CALL( SCIPaddRealParam(scip, "branching/relpscost/lowerrortol", "low relative error tolerance for reliability",
2146  &branchruledata->lowerrortol, TRUE, DEFAULT_LOWERRORTOL, 0.0, SCIP_REAL_MAX, NULL, NULL) );
2147 
2148  SCIP_CALL( SCIPaddRealParam(scip, "branching/relpscost/higherrortol", "high relative error tolerance for reliability",
2149  &branchruledata->higherrortol, TRUE, DEFAULT_HIGHERRORTOL, 0.0, SCIP_REAL_MAX, NULL, NULL) );
2150 
2151 /**! [SnippetCodeStyleParenIndent] */
2152 
2153  SCIP_CALL( SCIPaddBoolParam(scip, "branching/relpscost/storesemiinitcosts",
2154  "should strong branching result be considered for pseudo costs if the other direction was infeasible?",
2155  &branchruledata->storesemiinitcosts, TRUE, DEFAULT_STORESEMIINITCOSTS,
2156  NULL, NULL) );
2157 
2158 /**! [SnippetCodeStyleParenIndent] */
2159 
2160  SCIP_CALL( SCIPaddBoolParam(scip, "branching/relpscost/usesblocalinfo",
2161  "should the scoring function use only local cutoff and inference information obtained for strong branching candidates?",
2162  &branchruledata->usesblocalinfo, TRUE, DEFAULT_USESBLOCALINFO,
2163  NULL, NULL) );
2164 
2165  SCIP_CALL( SCIPaddBoolParam(scip, "branching/relpscost/usehyptestforreliability",
2166  "should the strong branching decision be based on a hypothesis test?",
2167  &branchruledata->usehyptestforreliability, TRUE, DEFAULT_USEHYPTESTFORRELIABILITY,
2168  NULL, NULL) );
2169 
2170  SCIP_CALL( SCIPaddBoolParam(scip, "branching/relpscost/usedynamicconfidence",
2171  "should the confidence level be adjusted dynamically?",
2172  &branchruledata->usedynamicconfidence, TRUE, DEFAULT_USEDYNAMICCONFIDENCE,
2173  NULL, NULL) );
2174  SCIP_CALL( SCIPaddBoolParam(scip, "branching/relpscost/skipbadinitcands",
2175  "should branching rule skip candidates that have a low probability to "
2176  "be better than the best strong-branching or pseudo-candidate?",
2177  &branchruledata->skipbadinitcands, TRUE, DEFAULT_SKIPBADINITCANDS,
2178  NULL, NULL) );
2179  SCIP_CALL( SCIPaddIntParam(scip,
2180  "branching/relpscost/confidencelevel",
2181  "the confidence level for statistical methods, between 0 (Min) and 4 (Max).",
2182  &branchruledata->confidencelevel, TRUE, DEFAULT_CONFIDENCELEVEL, 0, 4, NULL, NULL) );
2183 
2184  SCIP_CALL( SCIPaddBoolParam(scip, "branching/relpscost/randinitorder",
2185  "should candidates be initialized in randomized order?",
2186  &branchruledata->randinitorder, TRUE, DEFAULT_RANDINITORDER,
2187  NULL, NULL) );
2188 
2189  SCIP_CALL( SCIPaddBoolParam(scip, "branching/relpscost/usesmallweightsitlim",
2190  "should smaller weights be used for pseudo cost updates after hitting the LP iteration limit?",
2191  &branchruledata->usesmallweightsitlim, TRUE, DEFAULT_USESMALLWEIGHTSITLIM,
2192  NULL, NULL) );
2193 
2194  SCIP_CALL( SCIPaddBoolParam(scip, "branching/relpscost/dynamicweights",
2195  "should the weights of the branching rule be adjusted dynamically during solving based on objective and infeasible leaf counters?",
2196  &branchruledata->dynamicweights, TRUE, DEFAULT_DYNAMICWEIGHTS,
2197  NULL, NULL) );
2198  SCIP_CALL( SCIPaddIntParam(scip, "branching/relpscost/degeneracyaware",
2199  "should degeneracy be taken into account to update weights and skip strong branching? (0: off, 1: after root, 2: always)",
2200  &branchruledata->degeneracyaware, TRUE, DEFAULT_DEGENERACYAWARE, 0, 2,
2201  NULL, NULL) );
2202  SCIP_CALL( SCIPaddIntParam(scip, "branching/relpscost/startrandseed", "start seed for random number generation",
2203  &branchruledata->startrandseed, TRUE, DEFAULT_STARTRANDSEED, 0, INT_MAX, NULL, NULL) );
2204 
2205  SCIP_CALL( SCIPaddBoolParam(scip, "branching/relpscost/filtercandssym",
2206  "Use symmetry to filter branching candidates?",
2207  &branchruledata->filtercandssym, TRUE, DEFAULT_FILTERCANDSSYM, NULL, NULL) );
2208 
2209  SCIP_CALL( SCIPaddBoolParam(scip, "branching/relpscost/transsympscost",
2210  "Transfer pscost information to symmetric variables?",
2211  &branchruledata->transsympscost, TRUE, DEFAULT_TRANSSYMPSCOST, NULL, NULL) );
2212 
2213  /* initialise the Treemodel parameters */
2214  SCIP_CALL( SCIPtreemodelInit(scip, &branchruledata->treemodel) );
2215 
2216  return SCIP_OKAY;
2217 }
2218 
2219 /** execution reliability pseudo cost branching with the given branching candidates */
2220 SCIP_RETCODE SCIPexecRelpscostBranching(
2221  SCIP* scip, /**< SCIP data structure */
2222  SCIP_VAR** branchcands, /**< branching candidates */
2223  SCIP_Real* branchcandssol, /**< solution value for the branching candidates */
2224  SCIP_Real* branchcandsfrac, /**< fractional part of the branching candidates */
2225  int nbranchcands, /**< number of branching candidates */
2226  SCIP_Bool executebranching, /**< perform a branching step after probing */
2227  SCIP_RESULT* result /**< pointer to the result of the execution */
2228  )
2229 {
2230  SCIP_BRANCHRULE* branchrule;
2231 
2232  assert(scip != NULL);
2233  assert(result != NULL);
2234 
2235  /* find branching rule */
2236  branchrule = SCIPfindBranchrule(scip, BRANCHRULE_NAME);
2237  assert(branchrule != NULL);
2238 
2239  /* execute branching rule */
2240  SCIP_CALL( execRelpscost(scip, branchrule, branchcands, branchcandssol, branchcandsfrac, NULL, nbranchcands, executebranching, result) );
2241 
2242  return SCIP_OKAY;
2243 }
SCIP_RESULT
enum SCIP_Result SCIP_RESULT
Definition: type_result.h:61
SCIPgetLPBranchCands
SCIP_RETCODE SCIPgetLPBranchCands(SCIP *scip, SCIP_VAR ***lpcands, SCIP_Real **lpcandssol, SCIP_Real **lpcandsfrac, int *nlpcands, int *npriolpcands, int *nfracimplvars)
Definition: scip_branch.c:395
countNonlinearities
static SCIP_RETCODE countNonlinearities(SCIP *scip, int *nlcount, int nlcountsize, int *nlcountmax)
Definition: branch_relpscost.c:422
SCIPfreeRandom
void SCIPfreeRandom(SCIP *scip, SCIP_RANDNUMGEN **randnumgen)
Definition: scip_randnumgen.c:79
SCIPfreeBlockMemoryArray
#define SCIPfreeBlockMemoryArray(scip, ptr, num)
Definition: scip_mem.h:110
DEFAULT_FILTERCANDSSYM
#define DEFAULT_FILTERCANDSSYM
Definition: branch_relpscost.c:112
SCIP_BOUNDTYPE
enum SCIP_BoundType SCIP_BOUNDTYPE
Definition: type_lp.h:59
calcNlscore
static SCIP_Real calcNlscore(SCIP *scip, int *nlcount, int nlcountmax, int probindex)
Definition: branch_relpscost.c:559
branch_relpscost.h
reliable pseudo costs branching rule
SCIPreallocBlockMemoryArray
#define SCIPreallocBlockMemoryArray(scip, ptr, oldnum, newnum)
Definition: scip_mem.h:99
SCIP_DIDNOTRUN
Definition: type_result.h:42
SCIPbranchruleGetData
SCIP_BRANCHRULEDATA * SCIPbranchruleGetData(SCIP_BRANCHRULE *branchrule)
Definition: branch.c:1849
SCIPfeastol
SCIP_Real SCIPfeastol(SCIP *scip)
Definition: scip_numerics.c:165
SCIPallocBlockMemoryArray
#define SCIPallocBlockMemoryArray(scip, ptr, num)
Definition: scip_mem.h:93
DEFAULT_PSCOSTWEIGHT
#define DEFAULT_PSCOSTWEIGHT
Definition: branch_relpscost.c:76
SCIPisNLPConstructed
SCIP_Bool SCIPisNLPConstructed(SCIP *scip)
Definition: scip_nlp.c:110
SCIPupdateVarPseudocostSymmetric
static SCIP_RETCODE SCIPupdateVarPseudocostSymmetric(SCIP *scip, SCIP_BRANCHRULEDATA *branchruledata, SCIP_VAR *branchvar, int *branchorbitidx, int branchvaridx, SCIP_Real solvaldelta, SCIP_Real objdelta, SCIP_Real weight)
Definition: branch_relpscost.c:322
SCIPtightenVarLb
SCIP_RETCODE SCIPtightenVarLb(SCIP *scip, SCIP_VAR *var, SCIP_Real newbound, SCIP_Bool force, SCIP_Bool *infeasible, SCIP_Bool *tightened)
Definition: scip_var.c:5203
freeBdchgs
static void freeBdchgs(SCIP *scip, int **bdchginds, SCIP_BOUNDTYPE **bdchgtypes, SCIP_Real **bdchgbounds, int *nbdchgs)
Definition: branch_relpscost.c:668
BRANCHRULE_MAXDEPTH
#define BRANCHRULE_MAXDEPTH
Definition: branch_relpscost.c:69
scip_param.h
public methods for SCIP parameter handling
SCIPgetCurrentNode
SCIP_NODE * SCIPgetCurrentNode(SCIP *scip)
Definition: scip_tree.c:91
pub_tree.h
public methods for branch and bound tree
SCIPgetBinvarRepresentative
SCIP_RETCODE SCIPgetBinvarRepresentative(SCIP *scip, SCIP_VAR *var, SCIP_VAR **repvar, SCIP_Bool *negated)
Definition: scip_var.c:1597
DEFAULT_MAXBDCHGS
#define DEFAULT_MAXBDCHGS
Definition: branch_relpscost.c:85
SCIPisSumGE
SCIP_Bool SCIPisSumGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:731
scip_mem.h
public methods for memory management
SCIPfindConshdlr
SCIP_CONSHDLR * SCIPfindConshdlr(SCIP *scip, const char *name)
Definition: scip_cons.c:886
SCIPgetCutoffbound
SCIP_Real SCIPgetCutoffbound(SCIP *scip)
Definition: scip_solvingstats.c:1585
SCIPnodeGetLowerbound
SCIP_Real SCIPnodeGetLowerbound(SCIP_NODE *node)
Definition: tree.c:7464
SCIPgetRealParam
SCIP_RETCODE SCIPgetRealParam(SCIP *scip, const char *name, SCIP_Real *value)
Definition: scip_param.c:307
SCIPgetVarPseudocostVal
SCIP_Real SCIPgetVarPseudocostVal(SCIP *scip, SCIP_VAR *var, SCIP_Real solvaldelta)
Definition: scip_var.c:8814
SCIPgetSymmetry
SCIP_RETCODE SCIPgetSymmetry(SCIP *scip, int *npermvars, SCIP_VAR ***permvars, SCIP_HASHMAP **permvarmap, int *nperms, int ***perms, int ***permstrans, SCIP_Real *log10groupsize, SCIP_Bool *binvaraffected, int **components, int **componentbegins, int **vartocomponent, int *ncomponents)
Definition: prop_symmetry.c:7627
DEFAULT_LOWERRORTOL
#define DEFAULT_LOWERRORTOL
Definition: branch_relpscost.c:93
bound
static long bound
Definition: GomoryHuTree.cpp:47
SCIPgetLPDualDegeneracy
SCIP_RETCODE SCIPgetLPDualDegeneracy(SCIP *scip, SCIP_Real *degeneracy, SCIP_Real *varconsratio)
Definition: scip_lp.c:2792
SCIPvarGetLbLocal
SCIP_Real SCIPvarGetLbLocal(SCIP_VAR *var)
Definition: var.c:17957
SCIPgetVarStrongbranchLast
SCIP_RETCODE SCIPgetVarStrongbranchLast(SCIP *scip, SCIP_VAR *var, SCIP_Real *down, SCIP_Real *up, SCIP_Bool *downvalid, SCIP_Bool *upvalid, SCIP_Real *solval, SCIP_Real *lpobjval)
Definition: scip_var.c:4010
SCIPisGE
SCIP_Bool SCIPisGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:497
SCIP_BRANCHRULEDATA
struct SCIP_BranchruleData SCIP_BRANCHRULEDATA
Definition: type_branch.h:57
DEFAULT_DEGENERACYAWARE
#define DEFAULT_DEGENERACYAWARE
Definition: branch_relpscost.c:109
SCIPpscostThresholdProbabilityTest
SCIP_Bool SCIPpscostThresholdProbabilityTest(SCIP *scip, SCIP_VAR *var, SCIP_Real frac, SCIP_Real threshold, SCIP_BRANCHDIR dir, SCIP_CONFIDENCELEVEL clevel)
Definition: scip_var.c:9059
binvarGetActiveProbindex
static SCIP_RETCODE binvarGetActiveProbindex(SCIP *scip, SCIP_VAR *var, int *probindex)
Definition: branch_relpscost.c:384
SCIPgetAvgConflictScore
SCIP_Real SCIPgetAvgConflictScore(SCIP *scip)
Definition: scip_solvingstats.c:1986
SCIP_Var
Definition: struct_var.h:207
SCIPsetBranchruleInitsol
SCIP_RETCODE SCIPsetBranchruleInitsol(SCIP *scip, SCIP_BRANCHRULE *branchrule, SCIP_DECL_BRANCHINITSOL((*branchinitsol)))
Definition: scip_branch.c:217
SCIPvarIsBinary
SCIP_Bool SCIPvarIsBinary(SCIP_VAR *var)
Definition: var.c:17422
BRANCHRULE_MAXBOUNDDIST
#define BRANCHRULE_MAXBOUNDDIST
Definition: branch_relpscost.c:70
DEFAULT_STARTRANDSEED
#define DEFAULT_STARTRANDSEED
Definition: branch_relpscost.c:103
SCIPgetVarPseudocostCountCurrentRun
SCIP_Real SCIPgetVarPseudocostCountCurrentRun(SCIP *scip, SCIP_VAR *var, SCIP_BRANCHDIR dir)
Definition: scip_var.c:8950
SCIPgetVarPseudocostScoreCurrentRun
SCIP_Real SCIPgetVarPseudocostScoreCurrentRun(SCIP *scip, SCIP_VAR *var, SCIP_Real solval)
Definition: scip_var.c:9141
SCIPsetBranchruleFree
SCIP_RETCODE SCIPsetBranchruleFree(SCIP *scip, SCIP_BRANCHRULE *branchrule, SCIP_DECL_BRANCHFREE((*branchfree)))
Definition: scip_branch.c:169
SCIPgetVarsData
SCIP_RETCODE SCIPgetVarsData(SCIP *scip, SCIP_VAR ***vars, int *nvars, int *nbinvars, int *nintvars, int *nimplvars, int *ncontvars)
Definition: scip_prob.c:1866
DEFAULT_SBITERQUOT
#define DEFAULT_SBITERQUOT
Definition: branch_relpscost.c:80
SCIP_VERBLEVEL_HIGH
Definition: type_message.h:54
SCIPconshdlrGetConss
SCIP_CONS ** SCIPconshdlrGetConss(SCIP_CONSHDLR *conshdlr)
Definition: cons.c:4554
FALSE
#define FALSE
Definition: def.h:96
SCIPgetSubscipDepth
int SCIPgetSubscipDepth(SCIP *scip)
Definition: scip_copy.c:2605
SCIPinfinity
SCIP_Real SCIPinfinity(SCIP *scip)
Definition: scip_numerics.c:510
TRUE
#define TRUE
Definition: def.h:95
SCIPdebug
#define SCIPdebug(x)
Definition: pub_message.h:93
SCIPsetBranchruleCopy
SCIP_RETCODE SCIPsetBranchruleCopy(SCIP *scip, SCIP_BRANCHRULE *branchrule, SCIP_DECL_BRANCHCOPY((*branchcopy)))
Definition: scip_branch.c:153
SCIP_RETCODE
enum SCIP_Retcode SCIP_RETCODE
Definition: type_retcode.h:63
treemodel.h
Branching rules based on the Single-Variable-Branching (SVB) model.
SCIPgetVarStrongbranchNode
SCIP_Longint SCIPgetVarStrongbranchNode(SCIP *scip, SCIP_VAR *var)
Definition: scip_var.c:4160
DEFAULT_INFERENCEWEIGHT
#define DEFAULT_INFERENCEWEIGHT
Definition: branch_relpscost.c:74
SCIP_RandNumGen
Definition: struct_misc.h:268
SCIPfindBranchrule
SCIP_BRANCHRULE * SCIPfindBranchrule(SCIP *scip, const char *name)
Definition: scip_branch.c:297
SCIPvarGetProbindex
int SCIPvarGetProbindex(SCIP_VAR *var)
Definition: var.c:17591
SCIP_UNUSED
#define SCIP_UNUSED(x)
Definition: def.h:448
SCIPgetNRootStrongbranchLPIterations
SCIP_Longint SCIPgetNRootStrongbranchLPIterations(SCIP *scip)
Definition: scip_solvingstats.c:930
pub_var.h
public methods for problem variables
SCIPisVarPscostRelerrorReliable
SCIP_Bool SCIPisVarPscostRelerrorReliable(SCIP *scip, SCIP_VAR *var, SCIP_Real threshold, SCIP_CONFIDENCELEVEL clevel)
Definition: scip_var.c:9078
SCIPtightenVarUb
SCIP_RETCODE SCIPtightenVarUb(SCIP *scip, SCIP_VAR *var, SCIP_Real newbound, SCIP_Bool force, SCIP_Bool *infeasible, SCIP_Bool *tightened)
Definition: scip_var.c:5320
SCIPfreeBlockMemory
#define SCIPfreeBlockMemory(scip, ptr)
Definition: scip_mem.h:108
pub_branch.h
public methods for branching rules
SCIPgetNLPVarsNonlinearity
SCIP_RETCODE SCIPgetNLPVarsNonlinearity(SCIP *scip, int *nlcount)
Definition: scip_nlp.c:223
SCIPincludeBranchruleBasic
SCIP_RETCODE SCIPincludeBranchruleBasic(SCIP *scip, SCIP_BRANCHRULE **branchruleptr, const char *name, const char *desc, int priority, int maxdepth, SCIP_Real maxbounddist, SCIP_BRANCHRULEDATA *branchruledata)
Definition: scip_branch.c:116
cons_and.h
Constraint handler for AND constraints, .
SCIPduplicateBufferArray
#define SCIPduplicateBufferArray(scip, ptr, source, num)
Definition: scip_mem.h:132
SCIPfeasFrac
SCIP_Real SCIPfeasFrac(SCIP *scip, SCIP_Real val)
Definition: scip_numerics.c:941
SCIP_DECL_BRANCHINITSOL
static SCIP_DECL_BRANCHINITSOL(branchInitsolRelpscost)
Definition: branch_relpscost.c:1915
SCIP_DECL_BRANCHFREE
static SCIP_DECL_BRANCHFREE(branchFreeRelpscost)
Definition: branch_relpscost.c:1897
SCIPfreeBufferArray
#define SCIPfreeBufferArray(scip, ptr)
Definition: scip_mem.h:136
DEFAULT_HIGHERRORTOL
#define DEFAULT_HIGHERRORTOL
Definition: branch_relpscost.c:94
SCIPallocBlockMemory
#define SCIPallocBlockMemory(scip, ptr)
Definition: scip_mem.h:89
SCIP_LPSOLSTAT_OBJLIMIT
Definition: type_lp.h:46
scip_var.h
public methods for SCIP variables
SCIPvarGetNegationVar
SCIP_VAR * SCIPvarGetNegationVar(SCIP_VAR *var)
Definition: var.c:17727
SCIPdebugMsg
#define SCIPdebugMsg
Definition: scip_message.h:78
SCIPaddIntParam
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:83
initOrbits
static SCIP_RETCODE initOrbits(SCIP *scip, SCIP_BRANCHRULEDATA *branchruledata)
Definition: branch_relpscost.c:180
SCIP_Node
Definition: struct_tree.h:141
SCIP_Treemodel
Definition: treemodel.c:101
SCIPfeasCeil
SCIP_Real SCIPfeasCeil(SCIP *scip, SCIP_Real val)
Definition: scip_numerics.c:917
SCIP_DECL_BRANCHEXITSOL
static SCIP_DECL_BRANCHEXITSOL(branchExitsolRelpscost)
Definition: branch_relpscost.c:1936
DEFAULT_USESMALLWEIGHTSITLIM
#define DEFAULT_USESMALLWEIGHTSITLIM
Definition: branch_relpscost.c:105
scip_numerics.h
public methods for numerical tolerances
SCIPtreemodelSelectCandidate
SCIP_RETCODE SCIPtreemodelSelectCandidate(SCIP *scip, SCIP_TREEMODEL *treemodel, SCIP_VAR **branchcands, SCIP_Real *mingains, SCIP_Real *maxgains, SCIP_Real *tiebreakerscore, int nbranchcands, int *bestcand)
Definition: treemodel.c:920
SCIPgetVarPseudocostScore
SCIP_Real SCIPgetVarPseudocostScore(SCIP *scip, SCIP_VAR *var, SCIP_Real solval)
Definition: scip_var.c:9103
SCIPfeasFloor
SCIP_Real SCIPfeasFloor(SCIP *scip, SCIP_Real val)
Definition: scip_numerics.c:905
SCIPsetBranchruleExecLp
SCIP_RETCODE SCIPsetBranchruleExecLp(SCIP *scip, SCIP_BRANCHRULE *branchrule, SCIP_DECL_BRANCHEXECLP((*branchexeclp)))
Definition: scip_branch.c:249
scip_solvingstats.h
public methods for querying solving statistics
DEFAULT_INITITER
#define DEFAULT_INITITER
Definition: branch_relpscost.c:84
SCIPgetNDualResolveLPIterations
SCIP_Longint SCIPgetNDualResolveLPIterations(SCIP *scip)
Definition: scip_solvingstats.c:732
SCIPupdateVarPseudocost
SCIP_RETCODE SCIPupdateVarPseudocost(SCIP *scip, SCIP_VAR *var, SCIP_Real solvaldelta, SCIP_Real objdelta, SCIP_Real weight)
Definition: scip_var.c:8780
SCIPgetBranchScore
SCIP_Real SCIPgetBranchScore(SCIP *scip, SCIP_VAR *var, SCIP_Real downgain, SCIP_Real upgain)
Definition: scip_branch.c:849
scip_tree.h
public methods for the branch-and-bound tree
SCIPnodeGetNumber
SCIP_Longint SCIPnodeGetNumber(SCIP_NODE *node)
Definition: tree.c:7444
BRANCHRULE_NAME
#define BRANCHRULE_NAME
Definition: branch_relpscost.c:66
SCIPisLPSolBasic
SCIP_Bool SCIPisLPSolBasic(SCIP *scip)
Definition: scip_lp.c:667
SCIP_HashMap
Definition: struct_misc.h:137
pub_cons.h
public methods for managing constraints
BRANCHRULE_PRIORITY
#define BRANCHRULE_PRIORITY
Definition: branch_relpscost.c:68
SCIPgetNNLPVars
int SCIPgetNNLPVars(SCIP *scip)
Definition: scip_nlp.c:201
SCIP_CONFIDENCELEVEL
enum SCIP_Confidencelevel SCIP_CONFIDENCELEVEL
Definition: type_misc.h:53
SCIPgetVarsAnd
SCIP_VAR ** SCIPgetVarsAnd(SCIP *scip, SCIP_CONS *cons)
Definition: cons_and.c:5151
applyBdchgs
static SCIP_RETCODE applyBdchgs(SCIP *scip, SCIP_VAR **vars, int *bdchginds, SCIP_BOUNDTYPE *bdchgtypes, SCIP_Real *bdchgbounds, int nbdchgs, SCIP_RESULT *result)
Definition: branch_relpscost.c:689
SCIP_Cons
Definition: struct_cons.h:46
SCIPgetResultantAnd
SCIP_VAR * SCIPgetResultantAnd(SCIP *scip, SCIP_CONS *cons)
Definition: cons_and.c:5176
SCIPisLT
SCIP_Bool SCIPisLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:458
SCIP_Conshdlr
Definition: struct_cons.h:126
SCIP_BOUNDTYPE_LOWER
Definition: type_lp.h:56
SCIPfreeBufferArrayNull
#define SCIPfreeBufferArrayNull(scip, ptr)
Definition: scip_mem.h:137
SCIPvarGetName
const char * SCIPvarGetName(SCIP_VAR *var)
Definition: var.c:17242
DEFAULT_USEHYPTESTFORRELIABILITY
#define DEFAULT_USEHYPTESTFORRELIABILITY
Definition: branch_relpscost.c:95
NULL
#define NULL
Definition: lpi_spx1.cpp:164
SCIPgetVarConflictlengthScore
SCIP_Real SCIPgetVarConflictlengthScore(SCIP *scip, SCIP_VAR *var)
Definition: scip_var.c:9303
SCIPvarGetLPSol
SCIP_Real SCIPvarGetLPSol(SCIP_VAR *var)
Definition: var.c:18275
SCIP_OKAY
Definition: type_retcode.h:42
pub_sol.h
public methods for primal CIP solutions
SCIP_CALL
#define SCIP_CALL(x)
Definition: def.h:394
SCIPsignificantVarPscostDifference
SCIP_Bool SCIPsignificantVarPscostDifference(SCIP *scip, SCIP_VAR *varx, SCIP_Real fracx, SCIP_VAR *vary, SCIP_Real fracy, SCIP_BRANCHDIR dir, SCIP_CONFIDENCELEVEL clevel, SCIP_Bool onesided)
Definition: scip_var.c:9029
SCIPbranchVarVal
SCIP_RETCODE SCIPbranchVarVal(SCIP *scip, SCIP_VAR *var, SCIP_Real val, SCIP_NODE **downchild, SCIP_NODE **eqchild, SCIP_NODE **upchild)
Definition: scip_branch.c:1126
filterSymmetricVariables
static SCIP_RETCODE filterSymmetricVariables(SCIP *scip, SCIP_BRANCHRULEDATA *branchruledata, SCIP_VAR **origbranchcands, SCIP_Real *origbranchcandssol, SCIP_Real *origbranchcandsfrac, int norigbranchcands, SCIP_VAR **branchcands, SCIP_Real *branchcandssol, SCIP_Real *branchcandsfrac, int *branchorbitidx, int *nbranchcands)
Definition: branch_relpscost.c:239
prop_symmetry.h
propagator for symmetry handling
SCIP_REDUCEDDOM
Definition: type_result.h:51
SCIPverbMessage
void SCIPverbMessage(SCIP *scip, SCIP_VERBLEVEL msgverblevel, FILE *file, const char *formatstr,...)
Definition: scip_message.c:225
DEFAULT_SBITEROFS
#define DEFAULT_SBITEROFS
Definition: branch_relpscost.c:81
DEFAULT_CUTOFFWEIGHT
#define DEFAULT_CUTOFFWEIGHT
Definition: branch_relpscost.c:75
SCIP_Branchrule
Definition: struct_branch.h:78
SCIPtreemodelIsEnabled
SCIP_Bool SCIPtreemodelIsEnabled(SCIP *scip, SCIP_TREEMODEL *treemodel)
Definition: treemodel.c:908
SCIP_LPSOLSTAT_OPTIMAL
Definition: type_lp.h:43
SCIPhasCurrentNodeLP
SCIP_Bool SCIPhasCurrentNodeLP(SCIP *scip)
Definition: scip_lp.c:83
scip_cons.h
public methods for constraint handler plugins and constraints
SCIPgetNNodeLPIterations
SCIP_Longint SCIPgetNNodeLPIterations(SCIP *scip)
Definition: scip_solvingstats.c:786
SCIPgetVarPseudocostCurrentRun
SCIP_Real SCIPgetVarPseudocostCurrentRun(SCIP *scip, SCIP_VAR *var, SCIP_BRANCHDIR dir)
Definition: scip_var.c:8896
DEFAULT_CONFLICTWEIGHT
#define DEFAULT_CONFLICTWEIGHT
Definition: branch_relpscost.c:72
SCIPcreateRandom
SCIP_RETCODE SCIPcreateRandom(SCIP *scip, SCIP_RANDNUMGEN **randnumgen, unsigned int initialseed, SCIP_Bool useglobalseed)
Definition: scip_randnumgen.c:56
addBdchg
static SCIP_RETCODE addBdchg(SCIP *scip, int **bdchginds, SCIP_BOUNDTYPE **bdchgtypes, SCIP_Real **bdchgbounds, int *nbdchgs, int ind, SCIP_BOUNDTYPE type, SCIP_Real bound)
Definition: branch_relpscost.c:635
SCIPallocBufferArray
#define SCIPallocBufferArray(scip, ptr, num)
Definition: scip_mem.h:124
SCIPstartStrongbranch
SCIP_RETCODE SCIPstartStrongbranch(SCIP *scip, SCIP_Bool enablepropagation)
Definition: scip_var.c:2686
pub_misc.h
public data structures and miscellaneous methods
SCIPisSumGT
SCIP_Bool SCIPisSumGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:718
SCIP_Bool
#define SCIP_Bool
Definition: def.h:93
SCIPgetLPSolstat
SCIP_LPSOLSTAT SCIPgetLPSolstat(SCIP *scip)
Definition: scip_lp.c:168
SCIP_DECL_BRANCHEXECLP
static SCIP_DECL_BRANCHEXECLP(branchExeclpRelpscost)
Definition: branch_relpscost.c:1963
SCIP_DECL_BRANCHCOPY
static SCIP_DECL_BRANCHCOPY(branchCopyRelpscost)
Definition: branch_relpscost.c:1883
DEFAULT_CONFLENGTHWEIGHT
#define DEFAULT_CONFLENGTHWEIGHT
Definition: branch_relpscost.c:73
DEFAULT_SKIPBADINITCANDS
#define DEFAULT_SKIPBADINITCANDS
Definition: branch_relpscost.c:100
SCIPgetDepth
int SCIPgetDepth(SCIP *scip)
Definition: scip_tree.c:670
SCIPupdateNodeLowerbound
SCIP_RETCODE SCIPupdateNodeLowerbound(SCIP *scip, SCIP_NODE *node, SCIP_Real newbound)
Definition: scip_prob.c:3757
SCIPtreemodelFree
SCIP_RETCODE SCIPtreemodelFree(SCIP *scip, SCIP_TREEMODEL **treemodel)
Definition: treemodel.c:892
SCIPbranchruleSetData
void SCIPbranchruleSetData(SCIP_BRANCHRULE *branchrule, SCIP_BRANCHRULEDATA *branchruledata)
Definition: branch.c:1859
SCIP_CONFIDENCELEVEL_HIGH
Definition: type_misc.h:50
SCIPgetVarStrongbranchWithPropagation
SCIP_RETCODE SCIPgetVarStrongbranchWithPropagation(SCIP *scip, SCIP_VAR *var, SCIP_Real solval, SCIP_Real lpobjval, int itlim, int maxproprounds, SCIP_Real *down, SCIP_Real *up, SCIP_Bool *downvalid, SCIP_Bool *upvalid, SCIP_Longint *ndomredsdown, SCIP_Longint *ndomredsup, SCIP_Bool *downinf, SCIP_Bool *upinf, SCIP_Bool *downconflict, SCIP_Bool *upconflict, SCIP_Bool *lperror, SCIP_Real *newlbs, SCIP_Real *newubs)
Definition: scip_var.c:3352
DEFAULT_MINRELIABLE
#define DEFAULT_MINRELIABLE
Definition: branch_relpscost.c:78
MAX
#define MAX(x, y)
Definition: tclique_def.h:92
DEFAULT_MAXPROPROUNDS
#define DEFAULT_MAXPROPROUNDS
Definition: branch_relpscost.c:86
SCIPsetBranchruleExitsol
SCIP_RETCODE SCIPsetBranchruleExitsol(SCIP *scip, SCIP_BRANCHRULE *branchrule, SCIP_DECL_BRANCHEXITSOL((*branchexitsol)))
Definition: scip_branch.c:233
DEFAULT_INITCAND
#define DEFAULT_INITCAND
Definition: branch_relpscost.c:83
SCIPgetNDualResolveLPs
SCIP_Longint SCIPgetNDualResolveLPs(SCIP *scip)
Definition: scip_solvingstats.c:712
DEFAULT_NLSCOREWEIGHT
#define DEFAULT_NLSCOREWEIGHT
Definition: branch_relpscost.c:77
DEFAULT_DYNAMICWEIGHTS
#define DEFAULT_DYNAMICWEIGHTS
Definition: branch_relpscost.c:106
DEFAULT_MAXLOOKAHEAD
#define DEFAULT_MAXLOOKAHEAD
Definition: branch_relpscost.c:82
SCIP_CONFIDENCELEVEL_LOW
Definition: type_misc.h:48
SCIPgetNObjlimLeaves
SCIP_Longint SCIPgetNObjlimLeaves(SCIP *scip)
Definition: scip_solvingstats.c:320
SCIPgetVarStrongbranchFrac
SCIP_RETCODE SCIPgetVarStrongbranchFrac(SCIP *scip, SCIP_VAR *var, int itlim, SCIP_Bool idempotent, SCIP_Real *down, SCIP_Real *up, SCIP_Bool *downvalid, SCIP_Bool *upvalid, SCIP_Bool *downinf, SCIP_Bool *upinf, SCIP_Bool *downconflict, SCIP_Bool *upconflict, SCIP_Bool *lperror)
Definition: scip_var.c:2919
SCIPconshdlrGetNActiveConss
int SCIPconshdlrGetNActiveConss(SCIP_CONSHDLR *conshdlr)
Definition: cons.c:4631
SCIPrandomGetReal
SCIP_Real SCIPrandomGetReal(SCIP_RANDNUMGEN *randnumgen, SCIP_Real minrandval, SCIP_Real maxrandval)
Definition: misc.c:10041
SCIP_CONFIDENCELEVEL_MIN
Definition: type_misc.h:47
SCIPinProbing
SCIP_Bool SCIPinProbing(SCIP *scip)
Definition: scip_probing.c:97
scip_lp.h
public methods for the LP relaxation, rows and columns
SCIPgetNVars
int SCIPgetNVars(SCIP *scip)
Definition: scip_prob.c:1992
SCIP_REAL_MAX
#define SCIP_REAL_MAX
Definition: def.h:187
DEFAULT_USERELERRORFORRELIABILITY
#define DEFAULT_USERELERRORFORRELIABILITY
Definition: branch_relpscost.c:92
scip_nlp.h
public methods for nonlinear relaxation
execRelpscost
static SCIP_RETCODE execRelpscost(SCIP *scip, SCIP_BRANCHRULE *branchrule, SCIP_VAR **branchcands, SCIP_Real *branchcandssol, SCIP_Real *branchcandsfrac, int *branchorbitidx, int nbranchcands, SCIP_Bool executebranch, SCIP_RESULT *result)
Definition: branch_relpscost.c:766
SCIP_REAL_MIN
#define SCIP_REAL_MIN
Definition: def.h:188
SCIP_CONFIDENCELEVEL_MAX
Definition: type_misc.h:51
SCIPinDive
SCIP_Bool SCIPinDive(SCIP *scip)
Definition: scip_lp.c:2775
SCIP_BRANCHDIR_DOWNWARDS
Definition: type_history.h:43
SCIPgetAvgCutoffScore
SCIP_Real SCIPgetAvgCutoffScore(SCIP *scip)
Definition: scip_solvingstats.c:2208
scip_branch.h
public methods for branching rule plugins and branching
SCIPgetLastStrongbranchLPSolStat
SCIP_LPSOLSTAT SCIPgetLastStrongbranchLPSolStat(SCIP *scip, SCIP_BRANCHDIR branchdir)
Definition: scip_var.c:3988
SCIPgetNNodeInitLPIterations
SCIP_Longint SCIPgetNNodeInitLPIterations(SCIP *scip)
Definition: scip_solvingstats.c:822
scip_general.h
general public methods
SCIPgetNNodeInitLPs
SCIP_Longint SCIPgetNNodeInitLPs(SCIP *scip)
Definition: scip_solvingstats.c:804
SCIPgetAvgConflictlengthScore
SCIP_Real SCIPgetAvgConflictlengthScore(SCIP *scip)
Definition: scip_solvingstats.c:2036
SCIPgetLPObjval
SCIP_Real SCIPgetLPObjval(SCIP *scip)
Definition: scip_lp.c:247
SCIPgetBestSol
SCIP_SOL * SCIPgetBestSol(SCIP *scip)
Definition: scip_sol.c:2313
SCIPisGT
SCIP_Bool SCIPisGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:484
DEFAULT_PROBINGBOUNDS
#define DEFAULT_PROBINGBOUNDS
Definition: branch_relpscost.c:89
SCIP_BRANCHDIR_UPWARDS
Definition: type_history.h:44
scip_sol.h
public methods for solutions
SCIPgetNStrongbranchLPIterations
SCIP_Longint SCIPgetNStrongbranchLPIterations(SCIP *scip)
Definition: scip_solvingstats.c:894
scip_randnumgen.h
public methods for random numbers
symmetry.h
methods for handling symmetries
SCIP_BOUNDTYPE_UPPER
Definition: type_lp.h:57
SCIPincludeBranchruleRelpscost
SCIP_RETCODE SCIPincludeBranchruleRelpscost(SCIP *scip)
Definition: branch_relpscost.c:2046
SCIPendStrongbranch
SCIP_RETCODE SCIPendStrongbranch(SCIP *scip)
Definition: scip_var.c:2744
DEFAULT_USESBLOCALINFO
#define DEFAULT_USESBLOCALINFO
Definition: branch_relpscost.c:98
pub_message.h
public methods for message output
SCIP_CONSADDED
Definition: type_result.h:52
SCIPexecRelpscostBranching
SCIP_RETCODE SCIPexecRelpscostBranching(SCIP *scip, SCIP_VAR **branchcands, SCIP_Real *branchcandssol, SCIP_Real *branchcandsfrac, int nbranchcands, SCIP_Bool executebranching, SCIP_RESULT *result)
Definition: branch_relpscost.c:2224
DEFAULT_STORESEMIINITCOSTS
#define DEFAULT_STORESEMIINITCOSTS
Definition: branch_relpscost.c:97
SCIPcomputeOrbitsComponentsSym
SCIP_RETCODE SCIPcomputeOrbitsComponentsSym(SCIP *scip, int npermvars, int **permstrans, int nperms, int *components, int *componentbegins, int *vartocomponent, int ncomponents, int *orbits, int *orbitbegins, int *norbits, int *varorbitmap)
Definition: symmetry.c:411
SCIPgetVars
SCIP_VAR ** SCIPgetVars(SCIP *scip)
Definition: scip_prob.c:1947
SCIPvarGetStatus
SCIP_VARSTATUS SCIPvarGetStatus(SCIP_VAR *var)
Definition: var.c:17361
SCIP_Real
#define SCIP_Real
Definition: def.h:186
SCIPbranchruleGetName
const char * SCIPbranchruleGetName(SCIP_BRANCHRULE *branchrule)
Definition: branch.c:1971
SCIPisStopped
SCIP_Bool SCIPisStopped(SCIP *scip)
Definition: scip_general.c:703
SCIPgetNVarsAnd
int SCIPgetNVarsAnd(SCIP *scip, SCIP_CONS *cons)
Definition: cons_and.c:5127
calcScore
static SCIP_Real calcScore(SCIP *scip, SCIP_BRANCHRULEDATA *branchruledata, SCIP_Real conflictscore, SCIP_Real avgconflictscore, SCIP_Real conflengthscore, SCIP_Real avgconflengthscore, SCIP_Real inferencescore, SCIP_Real avginferencescore, SCIP_Real cutoffscore, SCIP_Real avgcutoffscore, SCIP_Real pscostscore, SCIP_Real avgpscostscore, SCIP_Real nlscore, SCIP_Real frac, SCIP_Real degeneracyfactor)
Definition: branch_relpscost.c:586
scip_message.h
public methods for message handling
SCIP_INVALID
#define SCIP_INVALID
Definition: def.h:206
SCIP_Longint
#define SCIP_Longint
Definition: def.h:171
SCIPallColsInLP
SCIP_Bool SCIPallColsInLP(SCIP *scip)
Definition: scip_lp.c:649
DEFAULT_USEDYNAMICCONFIDENCE
#define DEFAULT_USEDYNAMICCONFIDENCE
Definition: branch_relpscost.c:96
branchruledataEnsureNlcount
static SCIP_RETCODE branchruledataEnsureNlcount(SCIP *scip, SCIP_BRANCHRULEDATA *branchruledata)
Definition: branch_relpscost.c:512
SCIP_LPSOLSTAT_INFEASIBLE
Definition: type_lp.h:44
DEFAULT_TRANSSYMPSCOST
#define DEFAULT_TRANSSYMPSCOST
Definition: branch_relpscost.c:113
SCIPgetNodeLowerbound
SCIP_Real SCIPgetNodeLowerbound(SCIP *scip, SCIP_NODE *node)
Definition: scip_prob.c:3622
SCIPisZero
SCIP_Bool SCIPisZero(SCIP *scip, SCIP_Real val)
Definition: scip_numerics.c:558
SCIP_BRANCHED
Definition: type_result.h:54
BRANCHRULE_DESC
#define BRANCHRULE_DESC
Definition: branch_relpscost.c:67
SCIPgetAvgPseudocostScore
SCIP_Real SCIPgetAvgPseudocostScore(SCIP *scip)
Definition: scip_solvingstats.c:1889
SCIPvarGetUbLocal
SCIP_Real SCIPvarGetUbLocal(SCIP_VAR *var)
Definition: var.c:17967
SCIPfreeBlockMemoryArrayNull
#define SCIPfreeBlockMemoryArrayNull(scip, ptr, num)
Definition: scip_mem.h:111
SCIP_LPSOLSTAT_ITERLIMIT
Definition: type_lp.h:47
SCIPisFeasIntegral
SCIP_Bool SCIPisFeasIntegral(SCIP *scip, SCIP_Real val)
Definition: scip_numerics.c:881
BMSclearMemoryArray
#define BMSclearMemoryArray(ptr, num)
Definition: memory.h:132
SCIPhashmapGetImageInt
int SCIPhashmapGetImageInt(SCIP_HASHMAP *hashmap, void *origin)
Definition: misc.c:3231
SCIPtreemodelInit
SCIP_RETCODE SCIPtreemodelInit(SCIP *scip, SCIP_TREEMODEL **treemodel)
Definition: treemodel.c:834
DEFAULT_MAXRELIABLE
#define DEFAULT_MAXRELIABLE
Definition: branch_relpscost.c:79
SCIPgetNNodes
SCIP_Longint SCIPgetNNodes(SCIP *scip)
Definition: scip_solvingstats.c:212
scip_prob.h
public methods for global and local (sub)problems
SCIPgetNInfeasibleLeaves
SCIP_Longint SCIPgetNInfeasibleLeaves(SCIP *scip)
Definition: scip_solvingstats.c:293
DEFAULT_CONFIDENCELEVEL
#define DEFAULT_CONFIDENCELEVEL
Definition: branch_relpscost.c:99
SCIP_VARSTATUS_FIXED
Definition: type_var.h:52
SCIP_CONFIDENCELEVEL_MEDIUM
Definition: type_misc.h:49
DEFAULT_RANDINITORDER
#define DEFAULT_RANDINITORDER
Definition: branch_relpscost.c:104
SCIPgetVarAvgInferenceScore
SCIP_Real SCIPgetVarAvgInferenceScore(SCIP *scip, SCIP_VAR *var)
Definition: scip_var.c:9473
SCIPisExactSolve
SCIP_Bool SCIPisExactSolve(SCIP *scip)
Definition: scip_general.c:590
SCIPsolGetIndex
int SCIPsolGetIndex(SCIP_SOL *sol)
Definition: sol.c:2669
SCIPaddRealParam
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:139
SCIP_CUTOFF
Definition: type_result.h:48
SCIPgetAvgInferenceScore
SCIP_Real SCIPgetAvgInferenceScore(SCIP *scip)
Definition: scip_solvingstats.c:2122
SCIPaddBoolParam
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:57
SCIPgetVarConflictScore
SCIP_Real SCIPgetVarConflictScore(SCIP *scip, SCIP_VAR *var)
Definition: scip_var.c:9241
SCIPvarIsActive
SCIP_Bool SCIPvarIsActive(SCIP_VAR *var)
Definition: var.c:17571
SCIPvarIsNegated
SCIP_Bool SCIPvarIsNegated(SCIP_VAR *var)
Definition: var.c:17397
SCIPreallocBufferArray
#define SCIPreallocBufferArray(scip, ptr, num)
Definition: scip_mem.h:128
memory.h
memory allocation routines
SCIPgetVarAvgCutoffScore
SCIP_Real SCIPgetVarAvgCutoffScore(SCIP *scip, SCIP_VAR *var)
Definition: scip_var.c:9727