Scippy

SCIP

Solving Constraint Integer Programs

Detailed Description

NLP diving heuristic that chooses fixings w.r.t. the fractionalities.

Author
Timo Berthold
Stefan Vigerske

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.

Macros

#define HEUR_NAME   "nlpdiving"
 
#define HEUR_DESC   "NLP diving heuristic that chooses fixings w.r.t. the fractionalities"
 
#define HEUR_DISPCHAR   SCIP_HEURDISPCHAR_DIVING
 
#define HEUR_PRIORITY   -1003010
 
#define HEUR_FREQ   10
 
#define HEUR_FREQOFS   3
 
#define HEUR_MAXDEPTH   -1
 
#define HEUR_TIMING   SCIP_HEURTIMING_AFTERLPPLUNGE
 
#define HEUR_USESSUBSCIP   FALSE
 
#define EVENTHDLR_NAME   "Nlpdiving"
 
#define EVENTHDLR_DESC   "bound change event handler for " HEUR_NAME " heuristic"
 
#define DEFAULT_MINRELDEPTH   0.0
 
#define DEFAULT_MAXRELDEPTH   1.0
 
#define DEFAULT_MAXNLPITERABS   200
 
#define DEFAULT_MAXNLPITERREL   10
 
#define DEFAULT_MAXDIVEUBQUOT   0.8
 
#define DEFAULT_MAXDIVEAVGQUOT   0.0
 
#define DEFAULT_MAXDIVEUBQUOTNOSOL   0.1
 
#define DEFAULT_MAXDIVEAVGQUOTNOSOL   0.0
 
#define DEFAULT_MINSUCCQUOT   0.1
 
#define DEFAULT_MAXFEASNLPS   10
 
#define DEFAULT_FIXQUOT   0.2
 
#define DEFAULT_BACKTRACK   TRUE
 
#define DEFAULT_LP   FALSE
 
#define DEFAULT_PREFERLPFRACS   FALSE
 
#define DEFAULT_PREFERCOVER   TRUE
 
#define DEFAULT_SOLVESUBMIP   FALSE
 
#define DEFAULT_NLPSTART   's'
 
#define DEFAULT_VARSELRULE   'd'
 
#define DEFAULT_NLPFASTFAIL   TRUE
 
#define DEFAULT_RANDSEED   97
 
#define MINNLPITER   10
 

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 SCIP_RETCODE getNLPFracVars ( SCIP scip,
SCIP_HEURDATA heurdata,
SCIP_VAR ***  nlpcands,
SCIP_Real **  nlpcandssol,
SCIP_Real **  nlpcandsfrac,
int *  nnlpcands 
)
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
scipSCIP data structure
heurdataheuristic data structure
nlpcandspointer to store the array of NLP fractional variables, or NULL
nlpcandssolpointer to store the array of NLP fractional variables solution values, or NULL
nlpcandsfracpointer to store the array of NLP fractional variables fractionalities, or NULL
nnlpcandspointer 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()

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

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
sciporiginal SCIP data structure
heurdataheuristic data structure
nlpcandsarray of NLP fractional variables
nlpcandssolarray of NLP fractional variables solution values
nlpcandsfracarray of NLP fractional variables fractionalities
nnlpcandsnumber of NLP fractional variables
varincoverhash map for variables
covercomputedhas a minimal cover been computed?
bestcandpointer to store the index of the best candidate variable
bestcandmayroundpointer to store whether best candidate is trivially roundable
bestcandrounduppointer 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 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

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
sciporiginal SCIP data structure
heurdataheuristic data structure
nlpcandsarray of NLP fractional variables
nlpcandssolarray of NLP fractional variables solution values
nlpcandsfracarray of NLP fractional variables fractionalities
nnlpcandsnumber of NLP fractional variables
varincoverhash map for variables
covercomputedhas a minimal cover been computed?
bestcandpointer to store the index of the best candidate variable
bestcandmayroundpointer to store whether best candidate is trivially roundable
bestcandrounduppointer 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()

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

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
sciporiginal SCIP data structure
heurdataheuristic data structure
nlpcandsarray of NLP fractional variables
nlpcandssolarray of NLP fractional variables solution values
nlpcandsfracarray of NLP fractional variables fractionalities
nnlpcandsnumber of NLP fractional variables
varincoverhash map for variables
covercomputedhas a minimal cover been computed?
bestcandpointer to store the index of the best candidate variable
bestcandmayroundpointer to store whether best candidate is trivially roundable
bestcandrounduppointer 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()

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

calculates the pseudocost score for a given variable w.r.t. a given solution value and a given rounding direction

Parameters
scipSCIP data structure
heurdataheuristic data structure
varproblem variable
primsolprimal solution of variable
fracfractionality of variable
rounddir-1: round down, +1: round up, 0: select due to pseudo cost values
pscostquotpointer to store pseudo cost quotient
rounduppointer to store whether the variable should be rounded up
prefvarshould this variable be preferred because it is in a minimal cover?

Definition at line 704 of file heur_nlpdiving.c.

References choosePscostVar(), FALSE, MAX, MIN, NULL, SCIP_Real, SCIPfeasFloor(), SCIPgetVarPseudocostVal(), SCIPisEQ(), SCIPisGT(), SCIPisLT(), SCIPrandomGetInt(), SCIPvarGetRootSol(), SCIPvarIsBinary(), and TRUE.

Referenced by chooseCoefVar(), and choosePscostVar().

◆ choosePscostVar()

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

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
sciporiginal SCIP data structure
heurdataheuristic data structure
nlpcandsarray of NLP fractional variables
nlpcandssolarray of NLP fractional variables solution values
nlpcandsfracarray of NLP fractional variables fractionalities
nnlpcandsnumber of NLP fractional variables
varincoverhash map for variables
covercomputedhas a minimal cover been computed?
bestcandpointer to store the index of the best candidate variable
bestcandmayroundpointer to store whether best candidate is trivially roundable
bestcandrounduppointer to store whether best candidate should be rounded up

Definition at line 784 of file heur_nlpdiving.c.

References ABS, 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()

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

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
sciporiginal SCIP data structure
heurdataheuristic data structure
nlpcandsarray of NLP fractional variables
nlpcandssolarray of NLP fractional variables solution values
nlpcandsfracarray of NLP fractional variables fractionalities
nnlpcandsnumber of NLP fractional variables
bestsolincumbent solution
varincoverhash map for variables
covercomputedhas a minimal cover been computed?
bestcandpointer to store the index of the best candidate variable
bestcandmayroundpointer to store whether best candidate is trivially roundable
bestcandrounduppointer 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()

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

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
sciporiginal SCIP data structure
heurdataheuristic data structure
pseudocandsarray of non-fixed variables
pseudocandsnlpsolarray of NLP solution values
pseudocandslpsolarray of LP solution values
npseudocandsnumber of NLP fractional variables
varincoverhash map for variables
covercomputedhas a minimal cover been computed?
bestcandpointer to store the index of the best candidate variable
bestboundvalpointer to store the bound, the best candidate should be rounded to
bestcandmayroundpointer to store whether best candidate is trivially roundable
bestcandrounduppointer to store whether best candidate should be rounded up

Definition at line 1078 of file heur_nlpdiving.c.

References ABS, createNewSol(), FALSE, MAX, MIN, 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()

static SCIP_RETCODE createNewSol ( SCIP scip,
SCIP subscip,
SCIP_HEUR heur,
SCIP_HASHMAP varmap,
SCIP_SOL subsol,
SCIP_Bool success 
)
static

creates a new solution for the original problem by copying the solution of the subproblem

Parameters
sciporiginal SCIP data structure
subscipSCIP structure of the subproblem
heurheuristic structure
varmaphash map for variables
subsolsolution of the subproblem
successused to store whether new solution was found or not

Definition at line 1229 of file heur_nlpdiving.c.

References doSolveSubMIP(), FALSE, MAX, MIN, 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()

static SCIP_RETCODE doSolveSubMIP ( SCIP scip,
SCIP subscip,
SCIP_HEUR heur,
SCIP_VAR **  covervars,
int  ncovervars,
SCIP_Bool success 
)
static

◆ solveSubMIP()

static SCIP_RETCODE solveSubMIP ( SCIP scip,
SCIP_HEUR heur,
SCIP_VAR **  covervars,
int  ncovervars,
SCIP_Bool success 
)
static

solves subproblem and passes best feasible solution to original SCIP instance

Parameters
scipSCIP data structure of the original problem
heurheuristic data structure
covervarsvariables in the cover, should be fixed locally
ncovervarsnumber of variables in the cover
successpointer 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()

static SCIP_DECL_EVENTEXEC ( eventExecNlpdiving  )
static

Definition at line 1452 of file heur_nlpdiving.c.

Referenced by solveSubMIP().

◆ SCIP_DECL_HEURCOPY()

static SCIP_DECL_HEURCOPY ( heurCopyNlpdiving  )
static

copy method for primal heuristic plugins (called when SCIP copies plugins)

Definition at line 1517 of file heur_nlpdiving.c.

◆ SCIP_DECL_HEURFREE()

static SCIP_DECL_HEURFREE ( heurFreeNlpdiving  )
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()

static SCIP_DECL_HEURINIT ( heurInitNlpdiving  )
static

initialization method of primal heuristic (called after problem was transformed)

Definition at line 1551 of file heur_nlpdiving.c.

◆ SCIP_DECL_HEUREXIT()

static SCIP_DECL_HEUREXIT ( heurExitNlpdiving  )
static

deinitialization method of primal heuristic (called before transformed problem is freed)

Definition at line 1585 of file heur_nlpdiving.c.

◆ SCIP_DECL_HEUREXEC()

static SCIP_DECL_HEUREXEC ( heurExecNlpdiving  )
static

execution method of primal heuristic

Definition at line 1618 of file heur_nlpdiving.c.