SCIP
Solving Constraint Integer Programs
heur_nlpdiving.c File Reference
Detailed Description
NLP diving heuristic that chooses fixings w.r.t. the fractionalities.
Definition in file heur_nlpdiving.c.
#include "blockmemshell/memory.h"#include "scip/heur_nlpdiving.h"#include "scip/heur_subnlp.h"#include "scip/heur_undercover.h"#include "scip/pub_event.h"#include "scip/pub_heur.h"#include "scip/pub_message.h"#include "scip/pub_misc.h"#include "scip/pub_sol.h"#include "scip/pub_var.h"#include "scip/scip_branch.h"#include "scip/scip_copy.h"#include "scip/scip_event.h"#include "scip/scip_general.h"#include "scip/scip_heur.h"#include "scip/scip_lp.h"#include "scip/scip_mem.h"#include "scip/scip_message.h"#include "scip/scip_nlp.h"#include "scip/scip_nlpi.h"#include "scip/scip_nodesel.h"#include "scip/scip_numerics.h"#include "scip/scip_param.h"#include "scip/scip_prob.h"#include "scip/scip_probing.h"#include "scip/scip_randnumgen.h"#include "scip/scip_sol.h"#include "scip/scip_solve.h"#include "scip/scip_solvingstats.h"#include "scip/scip_timing.h"#include "scip/scip_tree.h"#include "scip/scip_var.h"#include <string.h>Go to the source code of this file.
Functions | |
| static SCIP_RETCODE | getNLPFracVars (SCIP *scip, SCIP_HEURDATA *heurdata, SCIP_VAR ***nlpcands, SCIP_Real **nlpcandssol, SCIP_Real **nlpcandsfrac, int *nnlpcands) |
| static SCIP_RETCODE | chooseFracVar (SCIP *scip, SCIP_HEURDATA *heurdata, SCIP_VAR **nlpcands, SCIP_Real *nlpcandssol, SCIP_Real *nlpcandsfrac, int nnlpcands, SCIP_HASHMAP *varincover, SCIP_Bool covercomputed, int *bestcand, SCIP_Bool *bestcandmayround, SCIP_Bool *bestcandroundup) |
| static SCIP_RETCODE | chooseVeclenVar (SCIP *scip, SCIP_HEURDATA *heurdata, SCIP_VAR **nlpcands, SCIP_Real *nlpcandssol, SCIP_Real *nlpcandsfrac, int nnlpcands, SCIP_HASHMAP *varincover, SCIP_Bool covercomputed, int *bestcand, SCIP_Bool *bestcandmayround, SCIP_Bool *bestcandroundup) |
| static SCIP_RETCODE | chooseCoefVar (SCIP *scip, SCIP_HEURDATA *heurdata, SCIP_VAR **nlpcands, SCIP_Real *nlpcandssol, SCIP_Real *nlpcandsfrac, int nnlpcands, SCIP_HASHMAP *varincover, SCIP_Bool covercomputed, int *bestcand, SCIP_Bool *bestcandmayround, SCIP_Bool *bestcandroundup) |
| static void | calcPscostQuot (SCIP *scip, SCIP_HEURDATA *heurdata, SCIP_VAR *var, SCIP_Real primsol, SCIP_Real frac, int rounddir, SCIP_Real *pscostquot, SCIP_Bool *roundup, SCIP_Bool prefvar) |
| static SCIP_RETCODE | choosePscostVar (SCIP *scip, SCIP_HEURDATA *heurdata, SCIP_VAR **nlpcands, SCIP_Real *nlpcandssol, SCIP_Real *nlpcandsfrac, int nnlpcands, SCIP_HASHMAP *varincover, SCIP_Bool covercomputed, int *bestcand, SCIP_Bool *bestcandmayround, SCIP_Bool *bestcandroundup) |
| static SCIP_RETCODE | chooseGuidedVar (SCIP *scip, SCIP_HEURDATA *heurdata, SCIP_VAR **nlpcands, SCIP_Real *nlpcandssol, SCIP_Real *nlpcandsfrac, int nnlpcands, SCIP_SOL *bestsol, SCIP_HASHMAP *varincover, SCIP_Bool covercomputed, int *bestcand, SCIP_Bool *bestcandmayround, SCIP_Bool *bestcandroundup) |
| static SCIP_RETCODE | chooseDoubleVar (SCIP *scip, SCIP_HEURDATA *heurdata, SCIP_VAR **pseudocands, SCIP_Real *pseudocandsnlpsol, SCIP_Real *pseudocandslpsol, int npseudocands, SCIP_HASHMAP *varincover, SCIP_Bool covercomputed, int *bestcand, SCIP_Real *bestboundval, SCIP_Bool *bestcandmayround, SCIP_Bool *bestcandroundup) |
| static SCIP_RETCODE | createNewSol (SCIP *scip, SCIP *subscip, SCIP_HEUR *heur, SCIP_HASHMAP *varmap, SCIP_SOL *subsol, SCIP_Bool *success) |
| static SCIP_RETCODE | doSolveSubMIP (SCIP *scip, SCIP *subscip, SCIP_HEUR *heur, SCIP_VAR **covervars, int ncovervars, SCIP_Bool *success) |
| static SCIP_RETCODE | solveSubMIP (SCIP *scip, SCIP_HEUR *heur, SCIP_VAR **covervars, int ncovervars, SCIP_Bool *success) |
| static | SCIP_DECL_EVENTEXEC (eventExecNlpdiving) |
| static | SCIP_DECL_HEURCOPY (heurCopyNlpdiving) |
| static | SCIP_DECL_HEURFREE (heurFreeNlpdiving) |
| static | SCIP_DECL_HEURINIT (heurInitNlpdiving) |
| static | SCIP_DECL_HEUREXIT (heurExitNlpdiving) |
| static | SCIP_DECL_HEUREXEC (heurExecNlpdiving) |
| SCIP_RETCODE | SCIPincludeHeurNlpdiving (SCIP *scip) |
Macro Definition Documentation
◆ HEUR_NAME
| #define HEUR_NAME "nlpdiving" |
Definition at line 68 of file heur_nlpdiving.c.
◆ HEUR_DESC
| #define HEUR_DESC "NLP diving heuristic that chooses fixings w.r.t. the fractionalities" |
Definition at line 69 of file heur_nlpdiving.c.
◆ HEUR_DISPCHAR
| #define HEUR_DISPCHAR SCIP_HEURDISPCHAR_DIVING |
Definition at line 70 of file heur_nlpdiving.c.
◆ HEUR_PRIORITY
| #define HEUR_PRIORITY -1003010 |
Definition at line 71 of file heur_nlpdiving.c.
◆ HEUR_FREQ
| #define HEUR_FREQ 10 |
Definition at line 72 of file heur_nlpdiving.c.
◆ HEUR_FREQOFS
| #define HEUR_FREQOFS 3 |
Definition at line 73 of file heur_nlpdiving.c.
◆ HEUR_MAXDEPTH
| #define HEUR_MAXDEPTH -1 |
Definition at line 74 of file heur_nlpdiving.c.
◆ HEUR_TIMING
| #define HEUR_TIMING SCIP_HEURTIMING_AFTERLPPLUNGE |
Definition at line 75 of file heur_nlpdiving.c.
◆ HEUR_USESSUBSCIP
| #define HEUR_USESSUBSCIP FALSE |
does the heuristic use a secondary SCIP instance?
Definition at line 76 of file heur_nlpdiving.c.
◆ EVENTHDLR_NAME
| #define EVENTHDLR_NAME "Nlpdiving" |
Definition at line 79 of file heur_nlpdiving.c.
◆ EVENTHDLR_DESC
| #define EVENTHDLR_DESC "bound change event handler for " HEUR_NAME " heuristic" |
Definition at line 80 of file heur_nlpdiving.c.
◆ DEFAULT_MINRELDEPTH
| #define DEFAULT_MINRELDEPTH 0.0 |
minimal relative depth to start diving
Definition at line 87 of file heur_nlpdiving.c.
◆ DEFAULT_MAXRELDEPTH
| #define DEFAULT_MAXRELDEPTH 1.0 |
maximal relative depth to start diving
Definition at line 88 of file heur_nlpdiving.c.
◆ DEFAULT_MAXNLPITERABS
| #define DEFAULT_MAXNLPITERABS 200 |
minimial absolute number of allowed NLP iterations
Definition at line 89 of file heur_nlpdiving.c.
◆ DEFAULT_MAXNLPITERREL
| #define DEFAULT_MAXNLPITERREL 10 |
additional allowed number of NLP iterations relative to successfully found solutions
Definition at line 90 of file heur_nlpdiving.c.
◆ DEFAULT_MAXDIVEUBQUOT
| #define DEFAULT_MAXDIVEUBQUOT 0.8 |
maximal quotient (curlowerbound - lowerbound)/(cutoffbound - lowerbound) where diving is performed (0.0: no limit)
Definition at line 91 of file heur_nlpdiving.c.
◆ DEFAULT_MAXDIVEAVGQUOT
| #define DEFAULT_MAXDIVEAVGQUOT 0.0 |
maximal quotient (curlowerbound - lowerbound)/(avglowerbound - lowerbound) where diving is performed (0.0: no limit)
Definition at line 94 of file heur_nlpdiving.c.
◆ DEFAULT_MAXDIVEUBQUOTNOSOL
| #define DEFAULT_MAXDIVEUBQUOTNOSOL 0.1 |
maximal UBQUOT when no solution was found yet (0.0: no limit)
Definition at line 97 of file heur_nlpdiving.c.
◆ DEFAULT_MAXDIVEAVGQUOTNOSOL
| #define DEFAULT_MAXDIVEAVGQUOTNOSOL 0.0 |
maximal AVGQUOT when no solution was found yet (0.0: no limit)
Definition at line 98 of file heur_nlpdiving.c.
◆ DEFAULT_MINSUCCQUOT
| #define DEFAULT_MINSUCCQUOT 0.1 |
heuristic will not run if less then this percentage of calls succeeded (0.0: no limit)
Definition at line 99 of file heur_nlpdiving.c.
◆ DEFAULT_MAXFEASNLPS
| #define DEFAULT_MAXFEASNLPS 10 |
maximal number of NLPs with feasible solution to solve during one dive
Definition at line 100 of file heur_nlpdiving.c.
◆ DEFAULT_FIXQUOT
| #define DEFAULT_FIXQUOT 0.2 |
percentage of fractional variables that should be fixed before the next NLP solve
Definition at line 101 of file heur_nlpdiving.c.
◆ DEFAULT_BACKTRACK
| #define DEFAULT_BACKTRACK TRUE |
use one level of backtracking if infeasibility is encountered?
Definition at line 102 of file heur_nlpdiving.c.
◆ DEFAULT_LP
| #define DEFAULT_LP FALSE |
should the LP relaxation be solved before the NLP relaxation?
Definition at line 103 of file heur_nlpdiving.c.
◆ DEFAULT_PREFERLPFRACS
| #define DEFAULT_PREFERLPFRACS FALSE |
prefer variables that are also fractional in LP solution?
Definition at line 104 of file heur_nlpdiving.c.
◆ DEFAULT_PREFERCOVER
| #define DEFAULT_PREFERCOVER TRUE |
should variables in a minimal cover be preferred?
Definition at line 105 of file heur_nlpdiving.c.
◆ DEFAULT_SOLVESUBMIP
| #define DEFAULT_SOLVESUBMIP FALSE |
should a sub-MIP be solved if all cover variables are fixed?
Definition at line 106 of file heur_nlpdiving.c.
◆ DEFAULT_NLPSTART
| #define DEFAULT_NLPSTART 's' |
which point should be used as starting point for the NLP solver?
Definition at line 107 of file heur_nlpdiving.c.
◆ DEFAULT_VARSELRULE
| #define DEFAULT_VARSELRULE 'd' |
which variable selection should be used? ('f'ractionality, 'c'oefficient, 'p'seudocost, 'g'uided, 'd'ouble)
Definition at line 108 of file heur_nlpdiving.c.
◆ DEFAULT_NLPFASTFAIL
| #define DEFAULT_NLPFASTFAIL TRUE |
should the NLP solver stop early if it converges slow?
Definition at line 113 of file heur_nlpdiving.c.
◆ DEFAULT_RANDSEED
| #define DEFAULT_RANDSEED 97 |
initial random seed
Definition at line 114 of file heur_nlpdiving.c.
◆ MINNLPITER
| #define MINNLPITER 10 |
minimal number of NLP iterations allowed in each NLP solving call
Definition at line 116 of file heur_nlpdiving.c.
Function Documentation
◆ getNLPFracVars()
|
static |
gets fractional variables of last NLP solution along with solution values and fractionalities
- Returns
- SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See SCIP_RETCODE for a complete list of error codes.
- Precondition
- This method can be called if SCIP is in one of the following stages:
- Parameters
-
scip SCIP data structure heurdata heuristic data structure nlpcands pointer to store the array of NLP fractional variables, or NULL nlpcandssol pointer to store the array of NLP fractional variables solution values, or NULL nlpcandsfrac pointer to store the array of NLP fractional variables fractionalities, or NULL nnlpcands pointer to store the number of NLP fractional variables , or NULL
Definition at line 174 of file heur_nlpdiving.c.
References chooseFracVar(), NULL, SCIP_CALL, SCIP_LPSOLSTAT_OPTIMAL, SCIP_OKAY, SCIP_Real, SCIPfeastol(), SCIPgetLPSolstat(), SCIPgetNLPFracVars(), SCIPgetSolVal(), SCIPisFeasIntegral(), SCIPsetSolVal(), SCIPvarGetLbLocal(), and SCIPvarGetUbLocal().
◆ chooseFracVar()
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static |
finds best candidate variable w.r.t. fractionality:
- prefer variables that may not be rounded without destroying NLP feasibility:
- of these variables, round least fractional variable in corresponding direction
- if all remaining fractional variables may be rounded without destroying NLP feasibility:
- round variable with least increasing objective value
- binary variables are prefered
- variables in a minimal cover or variables that are also fractional in an optimal LP solution might also be prefered if a correpsonding parameter is set
- Parameters
-
scip original SCIP data structure heurdata heuristic data structure nlpcands array of NLP fractional variables nlpcandssol array of NLP fractional variables solution values nlpcandsfrac array of NLP fractional variables fractionalities nnlpcands number of NLP fractional variables varincover hash map for variables covercomputed has a minimal cover been computed? bestcand pointer to store the index of the best candidate variable bestcandmayround pointer to store whether best candidate is trivially roundable bestcandroundup pointer to store whether best candidate should be rounded up
Definition at line 249 of file heur_nlpdiving.c.
References chooseVeclenVar(), FALSE, NULL, SCIP_Bool, SCIP_INVALID, SCIP_OKAY, SCIP_PROBINGSCORE_PENALTYRATIO, SCIP_Real, SCIPhashmapExists(), SCIPinfinity(), SCIPisEQ(), SCIPisGT(), SCIPisLT(), SCIPrandomGetInt(), SCIPvarGetLbLocal(), SCIPvarGetObj(), SCIPvarGetUbLocal(), SCIPvarIsBinary(), SCIPvarMayRoundDown(), SCIPvarMayRoundUp(), and TRUE.
Referenced by getNLPFracVars().
◆ chooseVeclenVar()
|
static |
finds best candidate variable w.r.t. vector length:
- round variable with a small ratio between the increase in the objective and the locking numbers
- binary variables are prefered
- variables in a minimal cover or variables that are also fractional in an optimal LP solution might also be prefered if a corresponding parameter is set
- Parameters
-
scip original SCIP data structure heurdata heuristic data structure nlpcands array of NLP fractional variables nlpcandssol array of NLP fractional variables solution values nlpcandsfrac array of NLP fractional variables fractionalities nnlpcands number of NLP fractional variables varincover hash map for variables covercomputed has a minimal cover been computed? bestcand pointer to store the index of the best candidate variable bestcandmayround pointer to store whether best candidate is trivially roundable bestcandroundup pointer to store whether best candidate should be rounded up
Definition at line 425 of file heur_nlpdiving.c.
References chooseCoefVar(), NULL, SCIP_Bool, SCIP_LOCKTYPE_MODEL, SCIP_OKAY, SCIP_Real, SCIP_REAL_MAX, SCIP_VARTYPE_BINARY, SCIPhashmapExists(), SCIPisGT(), SCIPisLT(), SCIPsumepsilon(), SCIPvarGetLbLocal(), SCIPvarGetNLocksDownType(), SCIPvarGetNLocksUpType(), SCIPvarGetObj(), SCIPvarGetType(), SCIPvarGetUbLocal(), SCIPvarMayRoundDown(), SCIPvarMayRoundUp(), and TRUE.
Referenced by chooseFracVar().
◆ chooseCoefVar()
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static |
finds best candidate variable w.r.t. locking numbers:
- prefer variables that may not be rounded without destroying LP feasibility:
- of these variables, round variable with least number of locks in corresponding direction
- if all remaining fractional variables may be rounded without destroying LP feasibility:
- round variable with least number of locks in opposite of its feasible rounding direction
- binary variables are prefered
- variables in a minimal cover or variables that are also fractional in an optimal LP solution might also be prefered if a correpsonding parameter is set
- Parameters
-
scip original SCIP data structure heurdata heuristic data structure nlpcands array of NLP fractional variables nlpcandssol array of NLP fractional variables solution values nlpcandsfrac array of NLP fractional variables fractionalities nnlpcands number of NLP fractional variables varincover hash map for variables covercomputed has a minimal cover been computed? bestcand pointer to store the index of the best candidate variable bestcandmayround pointer to store whether best candidate is trivially roundable bestcandroundup pointer to store whether best candidate should be rounded up
Definition at line 519 of file heur_nlpdiving.c.
References calcPscostQuot(), FALSE, NULL, SCIP_Bool, SCIP_INVALID, SCIP_LOCKTYPE_MODEL, SCIP_OKAY, SCIP_PROBINGSCORE_PENALTYRATIO, SCIP_Real, SCIPhashmapExists(), SCIPisEQ(), SCIPisGT(), SCIPisLT(), SCIPrandomGetInt(), SCIPvarGetLbLocal(), SCIPvarGetNLocksDownType(), SCIPvarGetNLocksUpType(), SCIPvarGetUbLocal(), SCIPvarIsBinary(), SCIPvarMayRoundDown(), SCIPvarMayRoundUp(), and TRUE.
Referenced by chooseVeclenVar().
◆ calcPscostQuot()
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static |
calculates the pseudocost score for a given variable w.r.t. a given solution value and a given rounding direction
- Parameters
-
scip SCIP data structure heurdata heuristic data structure var problem variable primsol primal solution of variable frac fractionality of variable rounddir -1: round down, +1: round up, 0: select due to pseudo cost values pscostquot pointer to store pseudo cost quotient roundup pointer to store whether the variable should be rounded up prefvar should this variable be preferred because it is in a minimal cover?
Definition at line 704 of file heur_nlpdiving.c.
References choosePscostVar(), FALSE, MAX, NULL, SCIP_Real, SCIPfeasFloor(), SCIPgetVarPseudocostVal(), SCIPisEQ(), SCIPisGT(), SCIPisLT(), SCIPrandomGetInt(), SCIPvarGetRootSol(), SCIPvarIsBinary(), and TRUE.
Referenced by chooseCoefVar(), and choosePscostVar().
◆ choosePscostVar()
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static |
finds best candidate variable w.r.t. pseudo costs:
- prefer variables that may not be rounded without destroying LP feasibility:
- of these variables, round variable with largest rel. difference of pseudo cost values in corresponding direction
- if all remaining fractional variables may be rounded without destroying LP feasibility:
- round variable in the objective value direction
- binary variables are prefered
- variables in a minimal cover or variables that are also fractional in an optimal LP solution might also be prefered if a correpsonding parameter is set
- Parameters
-
scip original SCIP data structure heurdata heuristic data structure nlpcands array of NLP fractional variables nlpcandssol array of NLP fractional variables solution values nlpcandsfrac array of NLP fractional variables fractionalities nnlpcands number of NLP fractional variables varincover hash map for variables covercomputed has a minimal cover been computed? bestcand pointer to store the index of the best candidate variable bestcandmayround pointer to store whether best candidate is trivially roundable bestcandroundup pointer to store whether best candidate should be rounded up
Definition at line 784 of file heur_nlpdiving.c.
References calcPscostQuot(), chooseGuidedVar(), FALSE, NULL, SCIP_Bool, SCIP_INVALID, SCIP_OKAY, SCIP_Real, SCIPhashmapExists(), SCIPisGT(), SCIPisInfinity(), SCIPisLT(), SCIPvarGetLbLocal(), SCIPvarGetUbLocal(), SCIPvarMayRoundDown(), SCIPvarMayRoundUp(), and TRUE.
Referenced by calcPscostQuot().
◆ chooseGuidedVar()
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static |
finds best candidate variable w.r.t. the incumbent solution:
- prefer variables that may not be rounded without destroying LP feasibility:
- of these variables, round a variable to its value in direction of incumbent solution, and choose the variable that is closest to its rounded value
- if all remaining fractional variables may be rounded without destroying LP feasibility:
- round variable in direction that destroys LP feasibility (other direction is checked by SCIProundSol())
- round variable with least increasing objective value
- binary variables are prefered
- variables in a minimal cover or variables that are also fractional in an optimal LP solution might also be prefered if a correpsonding parameter is set
- Parameters
-
scip original SCIP data structure heurdata heuristic data structure nlpcands array of NLP fractional variables nlpcandssol array of NLP fractional variables solution values nlpcandsfrac array of NLP fractional variables fractionalities nnlpcands number of NLP fractional variables bestsol incumbent solution varincover hash map for variables covercomputed has a minimal cover been computed? bestcand pointer to store the index of the best candidate variable bestcandmayround pointer to store whether best candidate is trivially roundable bestcandroundup pointer to store whether best candidate should be rounded up
Definition at line 906 of file heur_nlpdiving.c.
References chooseDoubleVar(), FALSE, NULL, SCIP_Bool, SCIP_INVALID, SCIP_OKAY, SCIP_PROBINGSCORE_PENALTYRATIO, SCIP_Real, SCIPgetSolVal(), SCIPhashmapExists(), SCIPinfinity(), SCIPisEQ(), SCIPisGT(), SCIPisLT(), SCIPrandomGetInt(), SCIPvarGetLbLocal(), SCIPvarGetObj(), SCIPvarGetUbLocal(), SCIPvarIsBinary(), SCIPvarMayRoundDown(), SCIPvarMayRoundUp(), and TRUE.
Referenced by choosePscostVar().
◆ chooseDoubleVar()
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static |
finds best candidate variable w.r.t. both, the LP and the NLP solution:
- choose a variable for which the sum of the distances from the relaxations' solutions to a common integer value is minimal
- binary variables are prefered
- variables in a minimal cover might be prefered if a corresponding parameter is set
- Parameters
-
scip original SCIP data structure heurdata heuristic data structure pseudocands array of non-fixed variables pseudocandsnlpsol array of NLP solution values pseudocandslpsol array of LP solution values npseudocands number of NLP fractional variables varincover hash map for variables covercomputed has a minimal cover been computed? bestcand pointer to store the index of the best candidate variable bestboundval pointer to store the bound, the best candidate should be rounded to bestcandmayround pointer to store whether best candidate is trivially roundable bestcandroundup pointer to store whether best candidate should be rounded up
Definition at line 1078 of file heur_nlpdiving.c.
References createNewSol(), FALSE, MAX, NULL, SCIP_Bool, SCIP_INVALID, SCIP_OKAY, SCIP_PROBINGSCORE_PENALTYRATIO, SCIP_Real, SCIPfeasCeil(), SCIPfeasFloor(), SCIPhashmapExists(), SCIPisEQ(), SCIPisFeasEQ(), SCIPisFeasIntegral(), SCIPisGT(), SCIPisLE(), SCIPisLT(), SCIPrandomGetInt(), SCIPvarGetLbLocal(), SCIPvarGetUbLocal(), SCIPvarIsBinary(), SCIPvarMayRoundDown(), SCIPvarMayRoundUp(), and TRUE.
Referenced by chooseGuidedVar().
◆ createNewSol()
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static |
creates a new solution for the original problem by copying the solution of the subproblem
- Parameters
-
scip original SCIP data structure subscip SCIP structure of the subproblem heur heuristic structure varmap hash map for variables subsol solution of the subproblem success used to store whether new solution was found or not
Definition at line 1229 of file heur_nlpdiving.c.
References doSolveSubMIP(), FALSE, MAX, NULL, SCIP_CALL, SCIP_OKAY, SCIP_Real, SCIPallocBufferArray, SCIPcreateSol(), SCIPfreeBufferArray, SCIPgetSolVal(), SCIPgetVarsData(), SCIPhashmapGetImage(), SCIPsetSolVals(), SCIPtrySolFree(), SCIPvarGetLbLocal(), SCIPvarGetUbLocal(), and TRUE.
Referenced by chooseDoubleVar(), and doSolveSubMIP().
◆ doSolveSubMIP()
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static |
todo setup and solve the subMIP
- Parameters
-
scip SCIP data structure subscip NLP diving subscip heur heuristic data structure covervars variables in the cover, should be fixed locally ncovervars number of variables in the cover success pointer to store whether a solution was found
Definition at line 1278 of file heur_nlpdiving.c.
References createNewSol(), FALSE, NULL, SCIP_CALL, SCIP_CALL_ABORT, SCIP_Longint, SCIP_OKAY, SCIP_PARAMSETTING_FAST, SCIP_PARAMSETTING_OFF, SCIP_Real, SCIPblkmem(), SCIPcopyConsCompression(), SCIPcopyLimits(), SCIPfindBranchrule(), SCIPfindNodesel(), SCIPgetLowerbound(), SCIPgetNSols(), SCIPgetNVars(), SCIPgetSols(), SCIPgetUpperbound(), SCIPhashmapCreate(), SCIPhashmapFree(), SCIPhashmapGetImage(), SCIPisFeasEQ(), SCIPisInfinity(), SCIPisParamFixed(), SCIPsetBoolParam(), SCIPsetCharParam(), SCIPsetIntParam(), SCIPsetLongintParam(), SCIPsetObjlimit(), SCIPsetPresolving(), SCIPsetSeparating(), SCIPsetSubscipsOff(), SCIPsolve(), SCIPsumepsilon(), SCIPvarGetLbGlobal(), SCIPvarGetLbLocal(), SCIPvarGetUbGlobal(), SCIPvarGetUbLocal(), solveSubMIP(), and TRUE.
Referenced by createNewSol(), and solveSubMIP().
◆ solveSubMIP()
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static |
solves subproblem and passes best feasible solution to original SCIP instance
- Parameters
-
scip SCIP data structure of the original problem heur heuristic data structure covervars variables in the cover, should be fixed locally ncovervars number of variables in the cover success pointer to store whether a solution was found
Definition at line 1415 of file heur_nlpdiving.c.
References doSolveSubMIP(), SCIP_CALL, SCIP_DECL_EVENTEXEC(), SCIP_OKAY, SCIPcheckCopyLimits(), SCIPcreate(), and SCIPfree().
Referenced by doSolveSubMIP().
◆ SCIP_DECL_EVENTEXEC()
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static |
Definition at line 1452 of file heur_nlpdiving.c.
Referenced by solveSubMIP().
◆ SCIP_DECL_HEURCOPY()
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static |
copy method for primal heuristic plugins (called when SCIP copies plugins)
Definition at line 1517 of file heur_nlpdiving.c.
◆ SCIP_DECL_HEURFREE()
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static |
destructor of primal heuristic to free user data (called when SCIP is exiting)
Definition at line 1531 of file heur_nlpdiving.c.
◆ SCIP_DECL_HEURINIT()
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static |
initialization method of primal heuristic (called after problem was transformed)
Definition at line 1551 of file heur_nlpdiving.c.
◆ SCIP_DECL_HEUREXIT()
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static |
deinitialization method of primal heuristic (called before transformed problem is freed)
Definition at line 1585 of file heur_nlpdiving.c.
◆ SCIP_DECL_HEUREXEC()
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static |
execution method of primal heuristic
Definition at line 1618 of file heur_nlpdiving.c.