Detailed Description

methods and files provided by the default primal heuristics of SCIP

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

Modules
	Inclusion methods
	methods to include specific primal heuristics into SCIP

Functions
SCIP_RETCODE	SCIPapplyHeurDualval (SCIP scip, SCIP_HEUR heur, SCIP_RESULT result, SCIP_SOL refpoint)

SCIP_RETCODE	SCIPheurPassIndicator (SCIP scip, SCIP_HEUR heur, int nindconss, SCIP_CONS *indconss, SCIP_Bool solcand, SCIP_Real obj)

SCIP_RETCODE	SCIPapplyProximity (SCIP scip, SCIP_HEUR heur, SCIP_RESULT result, SCIP_Real minimprove, SCIP_Longint nnodes, SCIP_Longint nlpiters, SCIP_Longint nusednodes, SCIP_Longint *nusedlpiters, SCIP_Bool freesubscip)

SCIP_RETCODE	SCIPdeleteSubproblemProximity (SCIP *scip)

SCIP_RETCODE	SCIPapplyRens (SCIP scip, SCIP_HEUR heur, SCIP_RESULT *result, SCIP_Real minfixingrate, SCIP_Real minimprove, SCIP_Longint maxnodes, SCIP_Longint nstallnodes, char startsol, SCIP_Bool binarybounds, SCIP_Bool uselprows)

int	SCIPreoptsolsGetNCheckedsols (SCIP *scip)

int	SCIPreoptsolsGetNImprovingsols (SCIP *scip)

SCIP_RETCODE	SCIPapplyHeurSubNlp (SCIP scip, SCIP_HEUR heur, SCIP_RESULT result, SCIP_SOL refpoint, SCIP_SOL *resultsol)

SCIP_RETCODE	SCIPupdateStartpointHeurSubNlp (SCIP scip, SCIP_HEUR heur, SCIP_SOL *solcand, SCIP_Real violation)

SCIP_SOL *	SCIPgetStartCandidateHeurSubNlp (SCIP scip, SCIP_HEUR heur)

SCIP_RETCODE	SCIPheurSyncPassSol (SCIP scip, SCIP_HEUR heur, SCIP_SOL *sol)

SCIP_RETCODE	SCIPheurPassSolTrySol (SCIP scip, SCIP_HEUR heur, SCIP_SOL *sol)

SCIP_RETCODE	SCIPheurPassSolAddSol (SCIP scip, SCIP_HEUR heur, SCIP_SOL *sol)

SCIP_RETCODE	SCIPcomputeCoverUndercover (SCIP scip, int coversize, SCIP_VAR *cover, SCIP_Real timelimit, SCIP_Real memorylimit, SCIP_Real objlimit, SCIP_Bool globalbounds, SCIP_Bool onlyconvexify, SCIP_Bool coverbd, char coveringobj, SCIP_Bool success)

SCIP_RETCODE	SCIPapplyZeroobj (SCIP scip, SCIP_HEUR heur, SCIP_RESULT *result, SCIP_Real minimprove, SCIP_Longint nnodes)

Files
file	heur_actconsdiving.h
	LP diving heuristic that chooses fixings w.r.t. the active constraints the variable appear in.

file	heur_adaptivediving.h
	diving heuristic that selects adaptively between the existing, public dive sets

file	heur_alns.h
	Adaptive large neighborhood search heuristic that orchestrates popular LNS heuristics.

file	heur_bound.h
	heuristic which fixes all integer variables to a bound (lower/upper) and solves the remaining LP

file	heur_clique.h
	LNS heuristic using a clique partition to restrict the search neighborhood.

file	heur_coefdiving.h
	LP diving heuristic that chooses fixings w.r.t. the matrix coefficients.

file	heur_completesol.h
	primal heuristic trying to complete given partial solutions

file	heur_conflictdiving.h
	LP diving heuristic that chooses fixings w.r.t. conflict locks.

file	heur_crossover.h
	LNS heuristic that tries to combine several feasible solutions.

file	heur_dins.h
	DINS primal heuristic.

file	heur_distributiondiving.h
	Diving heuristic that chooses fixings w.r.t. changes in the solution density after Pryor and Chinneck.

file	heur_dps.h
	dynamic partition search

file	heur_dualval.h
	primal heuristic that uses dualvalues for successive switching variable values

file	heur_farkasdiving.h
	LP diving heuristic that tries to construct a Farkas-proof.

file	heur_feaspump.h
	Objective Feasibility Pump 2.0.

file	heur_fixandinfer.h
	fix-and-infer primal heuristic

file	heur_fracdiving.h
	LP diving heuristic that chooses fixings w.r.t. the fractionalities.

file	heur_gins.h
	LNS heuristic that tries to delimit the search region to a neighborhood in the constraint graph.

file	heur_guideddiving.h
	LP diving heuristic that chooses fixings in direction of incumbent solutions.

file	heur_indicator.h
	handle partial solutions for linear problems with indicators and otherwise continuous variables

file	heur_intdiving.h
	LP diving heuristic that fixes variables with integral LP value.

file	heur_intshifting.h
	LP rounding heuristic that tries to recover from intermediate infeasibilities, shifts integer variables, and solves a final LP to calculate feasible values for continuous variables.

file	heur_linesearchdiving.h
	LP diving heuristic that fixes variables with a large difference to their root solution.

file	heur_localbranching.h
	Local branching heuristic according to Fischetti and Lodi.

file	heur_locks.h
	locks primal heuristic

file	heur_lpface.h
	LNS heuristic that tries to compute integral solution on optimal LP face.

file	heur_mpec.h
	mpec primal heuristic

file	heur_multistart.h
	multistart heuristic for convex and nonconvex MINLPs

file	heur_mutation.h
	LNS heuristic that tries to randomly mutate the incumbent solution.

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

file	heur_objpscostdiving.h
	LP diving heuristic that changes variable's objective value instead of bounds, using pseudo cost values as guide.

file	heur_octane.h
	octane primal heuristic based on Balas, Ceria, Dawande, Margot, and Pataki

file	heur_ofins.h
	OFINS - Objective Function Induced Neighborhood Search - a primal heuristic for reoptimization.

file	heur_oneopt.h
	Improvement heuristic that alters single variable values.

file	heur_padm.h
	PADM primal heuristic based on ideas published in the paper "A Decomposition Heuristic for Mixed-Integer Supply Chain Problems" by Martin Schmidt, Lars Schewe, and Dieter Weninger.

file	heur_proximity.h
	improvement heuristic which uses an auxiliary objective instead of the original objective function which is itself added as a constraint to a sub-SCIP instance. The heuristic was presented by Matteo Fischetti and Michele Monaci

file	heur_pscostdiving.h
	LP diving heuristic that chooses fixings w.r.t. the pseudo cost values.

file	heur_randrounding.h
	randomized LP rounding heuristic which also generates conflicts via an auxiliary probing tree

file	heur_rens.h
	LNS heuristic that finds the optimal rounding to a given point.

file	heur_reoptsols.h
	reoptsols primal heuristic

file	heur_repair.h
	repair primal heuristic

file	heur_rins.h
	LNS heuristic that combines the incumbent with the LP optimum.

file	heur_rootsoldiving.h
	LP diving heuristic that changes variables' objective values using root LP solution as guide.

file	heur_rounding.h
	LP rounding heuristic that tries to recover from intermediate infeasibilities.

file	heur_shiftandpropagate.h
	preroot heuristic that alternatingly fixes variables and propagates domains

file	heur_shifting.h
	LP rounding heuristic that tries to recover from intermediate infeasibilities and shifts continuous variables.

file	heur_simplerounding.h
	Simple and fast LP rounding heuristic.

file	heur_subnlp.h
	NLP local search primal heuristic using sub-SCIPs.

file	heur_sync.h
	primal heuristic that adds given solutions

file	heur_trivial.h
	trivial primal heuristic

file	heur_trivialnegation.h
	trivialnegation primal heuristic

file	heur_trustregion.h
	Large neighborhood search heuristic for Benders' decomposition based on trust region methods.

file	heur_trysol.h
	primal heuristic that tries a given solution

file	heur_twoopt.h
	Primal heuristic to improve incumbent solution by flipping pairs of variables.

file	heur_undercover.h
	Undercover primal heuristic for MINLPs.

file	heur_vbounds.h
	LNS heuristic uses the variable lower and upper bounds to determine the search neighborhood.

file	heur_veclendiving.h
	LP diving heuristic that rounds variables with long column vectors.

file	heur_zeroobj.h
	heuristic that tries to solve the problem without objective. In Gurobi, this heuristic is known as "Hail Mary"

file	heur_zirounding.h
	ZI Round primal heuristic.

file	heur_cycgreedy.h
	Greedy primal heuristic. States are assigned to clusters iteratively. At each iteration all possible assignments are computed and the one with the best change in objective value is selected.

file	heur_cyckerlin.h
	Improvement heuristic that trades bin-variables between clusters.

file	heur_fuzzyround.h
	primal heuristic that constructs a feasible solution from the lp-relaxation. Round only on the state-variables (binvars) and then reconstruct the rest of the variables accordingly.

file	heur_redsize.h
	primal heuristic that solves the problem with a sparser matrix as a submip

file	heur_listscheduling.c
	scheduling specific primal heuristic which is based on bidirectional serial generation scheme.

file	heur_optcumulative.h
	heuristic for cumulative scheduling with optional activities

Function Documentation

◆ SCIPapplyHeurDualval()

SCIP_RETCODE SCIPapplyHeurDualval	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		SCIP_RESULT *	result,
		SCIP_SOL *	refpoint
	)

main procedure of the dualval heuristic

Parameters

scip	original SCIP data structure
heur	heuristic data structure
result	pointer to store result of: did not run, solution found, no solution found, or fixing is infeasible (cutoff)
refpoint	point to take fixation of discrete variables from; if NULL, then LP solution is used

Definition at line 2016 of file heur_dualval.c.

References addLinearConstraintsToNlp(), bound, computeRanks(), createSolFromNLP(), createSubSCIP(), FALSE, fixDiscreteVars(), freeMemory(), MAX, maximalslack(), NULL, REALABS, SCIP_CALL, SCIP_DIDNOTFIND, SCIP_DIDNOTRUN, SCIP_NLPSOLSTAT_FEASIBLE, SCIP_OKAY, SCIP_Real, SCIP_STATUS_INFEASIBLE, SCIP_STATUS_OPTIMAL, SCIP_VERBLEVEL_HIGH, SCIPallocBlockMemoryArray, SCIPallocBufferArray, SCIPapplyHeurDualval(), SCIPchgRhsLinear(), SCIPchgVarLbGlobal(), SCIPchgVarUbGlobal(), SCIPconsGetHdlr(), SCIPdebugMsg, SCIPfindConshdlr(), SCIPfreeBlockMemoryArray, SCIPfreeBufferArray, SCIPfreeSol(), SCIPfreeTransform(), SCIPgetBestSol(), SCIPgetGap(), SCIPgetNLPBranchCands(), SCIPgetNLPSolstat(), SCIPgetNLPVars(), SCIPgetNNlpis(), SCIPgetNNLPVars(), SCIPgetNOrigConss(), SCIPgetNPseudoBranchCands(), SCIPgetOrigConss(), SCIPgetOrigVars(), SCIPgetOrigVarsData(), SCIPgetSolOrigObj(), SCIPgetSolVal(), SCIPgetStatus(), SCIPgetTransformedCons(), SCIPgetUpperbound(), SCIPhashmapGetImage(), SCIPhashmapInsert(), SCIPhashmapRemove(), SCIPhashmapRemoveAll(), SCIPheurGetData(), SCIPisEQ(), SCIPisFeasEQ(), SCIPisFeasLE(), SCIPisGE(), SCIPisInfinity(), SCIPisNLPConstructed(), SCIPisTransformed(), SCIPnlrowGetDualsol(), SCIPpresolve(), SCIPsetIntParam(), SCIPsetLongintParam(), SCIPsetNLPInitialGuess(), SCIPsetSolVal(), SCIPsolve(), SCIPsolveNLP, SCIPvarGetLbGlobal(), SCIPvarGetName(), SCIPvarGetObj(), SCIPvarGetOrigvarSum(), SCIPvarGetTransVar(), SCIPvarGetUbGlobal(), SCIPvarIsBinary(), SCIPvarIsNegated(), SCIPverbMessage(), storeSolution(), and TRUE.

Referenced by SCIP_DECL_HEUREXEC(), and SCIPapplyHeurDualval().

◆ SCIPheurPassIndicator()

SCIP_RETCODE SCIPheurPassIndicator	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		int	nindconss,
		SCIP_CONS **	indconss,
		SCIP_Bool *	solcand,
		SCIP_Real	obj
	)

pass partial solution for indicator variables to heuristic

Parameters

scip	SCIP data structure
heur	indicator heuristic
nindconss	number of indicator constraints
indconss	indicator constraints
solcand	values for indicator variables in partial solution
obj	objective of solution

Definition at line 596 of file heur_indicator.c.

References BMScopyMemoryArray, HEUR_NAME, NULL, SCIP_CALL, SCIP_OKAY, SCIPduplicateBlockMemoryArray, SCIPfreeBlockMemoryArray, SCIPheurGetData(), and SCIPheurGetName().

Referenced by extendToCover().

◆ SCIPapplyProximity()

SCIP_RETCODE SCIPapplyProximity	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		SCIP_RESULT *	result,
		SCIP_Real	minimprove,
		SCIP_Longint	nnodes,
		SCIP_Longint	nlpiters,
		SCIP_Longint *	nusednodes,
		SCIP_Longint *	nusedlpiters,
		SCIP_Bool	freesubscip
	)

main procedure of the proximity heuristic, creates and solves a sub-SCIP

Note: the method can be applied in an iterative way, keeping the same subscip in between. If the freesubscip parameter is set to FALSE, the heuristic will keep the subscip data structures. Always set this parameter to TRUE, or call SCIPdeleteSubproblemProximity() afterwards

main procedure of the proximity heuristic, creates and solves a sub-SCIP

Note: The method can be applied in an iterative way, keeping the same subscip in between. If the freesubscip parameter is set to FALSE, the heuristic will keep the subscip data structures. Always set this parameter to TRUE, or call SCIPdeleteSubproblemProximity() afterwards.

Parameters

scip	original SCIP data structure
heur	heuristic data structure
result	result data structure
minimprove	factor by which proximity should at least improve the incumbent
nnodes	node limit for the subproblem
nlpiters	LP iteration limit for the subproblem
nusednodes	pointer to store number of used nodes in subscip
nusedlpiters	pointer to store number of used LP iterations in subscip
freesubscip	should the created sub-MIP be freed at the end of the method?

Definition at line 667 of file heur_proximity.c.

References createNewSol(), deleteSubproblem(), EVENTHDLR_DESC, EVENTHDLR_NAME, FALSE, HEUR_NAME, MAX, NULL, REALABS, SCIP_Bool, SCIP_CALL, SCIP_CALL_ABORT, SCIP_DIDNOTFIND, SCIP_DIDNOTRUN, SCIP_EVENTTYPE_NODESOLVED, SCIP_FOUNDSOL, SCIP_Longint, SCIP_OKAY, SCIP_PLUGINNOTFOUND, SCIP_Real, SCIPaddCoefLinear(), SCIPaddCons(), SCIPallocBlockMemoryArray, SCIPblkmem(), SCIPcatchEvent(), SCIPcheckCopyLimits(), SCIPchgRhsLinear(), SCIPchgVarLbGlobal(), SCIPchgVarObj(), SCIPchgVarUbGlobal(), SCIPcopyLargeNeighborhoodSearch(), SCIPcopyLimits(), SCIPcreate(), SCIPcreateConsBasicLinear(), SCIPdebug, SCIPdebugMsg, SCIPdropEvent(), SCIPerrorMessage, SCIPfeasCeil(), SCIPfeasFloor(), SCIPfeastol(), SCIPfindEventhdlr(), SCIPfreeTransform(), SCIPgetBestSol(), SCIPgetGap(), SCIPgetLowerbound(), SCIPgetNBinVars(), SCIPgetNFixedVars(), SCIPgetNLPIterations(), SCIPgetNNodes(), SCIPgetNRootLPIterations(), SCIPgetNSols(), SCIPgetNSolsFound(), SCIPgetPresolvingTime(), SCIPgetPrimalbound(), SCIPgetRhsLinear(), SCIPgetSolTransObj(), SCIPgetSolVal(), SCIPgetSolvingTime(), SCIPgetVarsData(), SCIPhashmapCreate(), SCIPhashmapGetImage(), SCIPheurGetData(), SCIPheurGetName(), SCIPincludeEventhdlrBasic(), SCIPinfinity(), SCIPisFeasEQ(), SCIPisFeasGE(), SCIPisFeasIntegral(), SCIPisFeasLE(), SCIPisFeasLT(), SCIPisFeasZero(), SCIPisInfinity(), SCIPisObjIntegral(), SCIPisZero(), SCIPpresolve(), SCIPprintStatistics(), SCIPsetIntParam(), SCIPsetLongintParam(), SCIPsolGetHeur(), SCIPsolGetIndex(), SCIPsolGetNodenum(), SCIPsolIsOriginal(), SCIPsolve(), SCIPstatisticMessage, SCIPtransformProb(), SCIPvarGetLbGlobal(), SCIPvarGetObj(), SCIPvarGetUbGlobal(), SCIPvarIsBinary(), setupSubproblem(), and TRUE.

Referenced by SCIP_DECL_HEUREXEC().

◆ SCIPdeleteSubproblemProximity()

SCIP_RETCODE SCIPdeleteSubproblemProximity ( SCIP * scip )

frees the sub-MIP created by proximity

Parameters

scip	SCIP data structure

Definition at line 640 of file heur_proximity.c.

References deleteSubproblem(), HEUR_NAME, NULL, SCIP_CALL, SCIP_OKAY, SCIPfindHeur(), and SCIPheurGetData().

Referenced by SCIP_DECL_HEUREXEC().

◆ SCIPapplyRens()

SCIP_RETCODE SCIPapplyRens	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		SCIP_RESULT *	result,
		SCIP_Real	minfixingrate,
		SCIP_Real	minimprove,
		SCIP_Longint	maxnodes,
		SCIP_Longint	nstallnodes,
		char	startsol,
		SCIP_Bool	binarybounds,
		SCIP_Bool	uselprows
	)

main procedure of the RNS heuristic, creates and solves a sub-SCIP

main procedure of the RENS heuristic, creates and solves a sub-SCIP

Parameters

scip	original SCIP data structure
heur	heuristic data structure
result	result data structure
minfixingrate	minimum percentage of integer variables that have to be fixed
minimprove	factor by which RENS should at least improve the incumbent
maxnodes	maximum number of nodes for the subproblem
nstallnodes	number of stalling nodes for the subproblem
startsol	solution used for fixing values ('l'p relaxation, 'n'lp relaxation)
binarybounds	should general integers get binary bounds [floor(.),ceil(.)]?
uselprows	should subproblem be created out of the rows in the LP rows?

Definition at line 603 of file heur_rens.c.

References computeFixingrate(), NULL, SCIP_Bool, SCIP_CALL, SCIP_DIDNOTFIND, SCIP_DIDNOTRUN, SCIP_OKAY, SCIP_Real, SCIPallocBufferArray, SCIPcheckCopyLimits(), SCIPcreate(), SCIPfree(), SCIPfreeBufferArray, SCIPgetNBinVars(), SCIPgetNIntVars(), SCIPstatisticPrintf, and setupAndSolveSubscip().

Referenced by SCIP_DECL_HEUREXEC().

◆ SCIPreoptsolsGetNCheckedsols()

int SCIPreoptsolsGetNCheckedsols ( SCIP * scip )

Definition at line 311 of file heur_reoptsols.c.

References HEUR_NAME, NULL, SCIPfindHeur(), and SCIPheurGetData().

◆ SCIPreoptsolsGetNImprovingsols()

int SCIPreoptsolsGetNImprovingsols ( SCIP * scip )

Definition at line 330 of file heur_reoptsols.c.

References HEUR_NAME, NULL, SCIPfindHeur(), and SCIPheurGetData().

◆ SCIPapplyHeurSubNlp()

SCIP_RETCODE SCIPapplyHeurSubNlp	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		SCIP_RESULT *	result,
		SCIP_SOL *	refpoint,
		SCIP_SOL *	resultsol
	)

main procedure of the subNLP heuristic

Parameters

scip	original SCIP data structure
heur	heuristic data structure
result	pointer to store result of: did not run, solution found, no solution found, or fixing is infeasible (cutoff)
refpoint	point to take fixation of discrete variables from, and startpoint for NLP solver; if NULL, then LP solution is used
resultsol	a solution where to store found solution values, if any, or NULL if to try adding to SCIP

Definition at line 1766 of file heur_subnlp.c.

References createSubSCIP(), FALSE, forbidFixation(), freeSubSCIP(), MAX, NULL, REALABS, SCIP_Bool, SCIP_CALL, SCIP_CUTOFF, SCIP_DIDNOTFIND, SCIP_DIDNOTRUN, SCIP_LPSOLSTAT_OPTIMAL, SCIP_OKAY, SCIP_Real, SCIP_STAGE_SOLVING, SCIPdebugMsg, SCIPfreeTransform(), SCIPgetLPSolstat(), SCIPgetNActivePricers(), SCIPgetNSols(), SCIPgetOrigVarsData(), SCIPgetSolVal(), SCIPgetStage(), SCIPgetUpperbound(), SCIPheurGetData(), SCIPinfinity(), SCIPisEQ(), SCIPisFeasIntegral(), SCIPisInfinity(), SCIPisTransformed(), SCIPround(), SCIPsetObjlimit(), SCIPtightenVarLb(), SCIPtightenVarUb(), SCIPtransformProb(), SCIPvarGetLbGlobal(), SCIPvarGetName(), SCIPvarGetProbindex(), SCIPvarGetUbGlobal(), solveSubNLP(), and TRUE.

Referenced by heurExec(), SCIP_DECL_HEUREXEC(), SCIPapplyUndercover(), and solveNLP().

◆ SCIPupdateStartpointHeurSubNlp()

SCIP_RETCODE SCIPupdateStartpointHeurSubNlp	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		SCIP_SOL *	solcand,
		SCIP_Real	violation
	)

updates the starting point for the NLP heuristic

Is called, for example, by a constraint handler that handles nonlinear constraints when a check on feasibility of a solution fails.

updates the starting point for the NLP heuristic

Is called by a constraint handler that handles nonlinear constraints when a check on feasibility of a solution fails.

Parameters

scip	SCIP data structure
heur	NLP heuristic
solcand	solution candidate
violation	constraint violation of solution candidate

Definition at line 1941 of file heur_subnlp.c.

References HEUR_NAME, NULL, runHeuristic(), SCIP_Bool, SCIP_CALL, SCIP_OKAY, SCIP_STAGE_SOLVING, SCIPcreateSolCopy(), SCIPdebugMsg, SCIPfreeSol(), SCIPgetSolHeur(), SCIPgetSolTransObj(), SCIPgetStage(), SCIPheurGetData(), SCIPheurGetFreq(), SCIPheurGetName(), SCIPisPositive(), SCIPisRelGT(), SCIPsolGetHeur(), SCIPsolSetHeur(), and SCIPunlinkSol().

Referenced by SCIP_DECL_CONSCHECK().

◆ SCIPgetStartCandidateHeurSubNlp()

SCIP_SOL* SCIPgetStartCandidateHeurSubNlp	(	SCIP *	scip,
		SCIP_HEUR *	heur
	)

gets startpoint candidate to be used in next call to NLP heuristic, or NULL if none

Parameters

scip	original SCIP data structure
heur	heuristic data structure

Definition at line 2005 of file heur_subnlp.c.

References HEUR_NAME, NULL, SCIPheurGetData(), and SCIPheurGetName().

◆ SCIPheurSyncPassSol()

SCIP_RETCODE SCIPheurSyncPassSol	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		SCIP_SOL *	sol
	)

pass solution to sync heuristic

Parameters

scip	SCIP data structure
heur	sync heuristic
sol	solution to be passed

Definition at line 190 of file heur_sync.c.

References HEUR_NAME, NULL, SCIP_CALL, SCIP_OKAY, SCIP_Real, SCIPfreeSol(), SCIPgetSolTransObj(), SCIPheurGetData(), SCIPheurGetName(), SCIPheurSetFreq(), and SCIPsolSetHeur().

Referenced by SCIPaddConcurrentSol().

◆ SCIPheurPassSolTrySol()

SCIP_RETCODE SCIPheurPassSolTrySol	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		SCIP_SOL *	sol
	)

pass solution to trysol heuristic

Parameters

scip	SCIP data structure
heur	trysol heuristic
sol	solution to be passed

Definition at line 252 of file heur_trysol.c.

References HEUR_NAME, NULL, SCIP_CALL, SCIP_OBJSENSE_MAXIMIZE, SCIP_OKAY, SCIPcreateSolCopy(), SCIPdebugMsg, SCIPfreeSol(), SCIPgetObjsense(), SCIPgetSolOrigObj(), SCIPheurGetData(), SCIPheurGetName(), SCIPisGT(), SCIPisLT(), SCIPsolSetHeur(), and SCIPunlinkSol().

Referenced by proposeFeasibleSolution(), SCIP_DECL_CONSCHECK(), SCIP_DECL_CONSENFOLP(), and SCIP_DECL_CONSENFOPS().

◆ SCIPheurPassSolAddSol()

SCIP_RETCODE SCIPheurPassSolAddSol	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		SCIP_SOL *	sol
	)

pass solution to trysol heuristic which just gets added (without checking feasibility

Parameters

scip	SCIP data structure
heur	trysol heuristic
sol	solution to be passed

Definition at line 293 of file heur_trysol.c.

References HEUR_NAME, NULL, SCIP_CALL, SCIP_OBJSENSE_MAXIMIZE, SCIP_OKAY, SCIPcreateSolCopy(), SCIPdebugMsg, SCIPfreeSol(), SCIPgetObjsense(), SCIPgetSolOrigObj(), SCIPheurGetData(), SCIPheurGetName(), SCIPisGT(), SCIPisLT(), SCIPsolSetHeur(), and SCIPunlinkSol().

Referenced by checkSystemGF2(), and constructValidSolution().

◆ SCIPcomputeCoverUndercover()

SCIP_RETCODE SCIPcomputeCoverUndercover	(	SCIP *	scip,
		int *	coversize,
		SCIP_VAR **	cover,
		SCIP_Real	timelimit,
		SCIP_Real	memorylimit,
		SCIP_Real	objlimit,
		SCIP_Bool	globalbounds,
		SCIP_Bool	onlyconvexify,
		SCIP_Bool	coverbd,
		char	coveringobj,
		SCIP_Bool *	success
	)

computes a minimal set of covering variables

Parameters

scip	SCIP data structure
coversize	buffer for the size of the computed cover
cover	pointer to store the variables (of the original SCIP) in the computed cover (should be ready to hold SCIPgetNVars(scip) entries)
timelimit	time limit
memorylimit	memory limit
objlimit	objective limit: upper bound on coversize
globalbounds	should global bounds on variables be used instead of local bounds at focus node?
onlyconvexify	should we only fix/dom.red. variables creating nonconvexity?
coverbd	should bounddisjunction constraints be covered (or just copied)?
coveringobj	objective function of the covering problem ('b'ranching status, influenced nonlinear 'c'onstraints/'t'erms, 'd'omain size, 'l'ocks, 'm'in of up/down locks, 'u'nit penalties, constraint 'v'iolation)
success	feasible cover found?

Definition at line 3320 of file heur_undercover.c.

References computeCoverUndercover(), FALSE, NULL, SCIP_CALL, SCIP_OKAY, SCIPcreate(), and SCIPfree().

Referenced by computeCoverUndercover().

◆ SCIPapplyZeroobj()

SCIP_RETCODE SCIPapplyZeroobj	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		SCIP_RESULT *	result,
		SCIP_Real	minimprove,
		SCIP_Longint	nnodes
	)

main procedure of the zeroobj heuristic, creates and solves a sub-SCIP

Parameters

scip	original SCIP data structure
heur	heuristic data structure
result	result data structure
minimprove	factor by which zeroobj should at least improve the incumbent
nnodes	node limit for the subproblem

Definition at line 504 of file heur_zeroobj.c.

References NULL, SCIP_Bool, SCIP_CALL, SCIP_DIDNOTFIND, SCIP_DIDNOTRUN, SCIP_OKAY, SCIPcheckCopyLimits(), SCIPcreate(), SCIPfree(), SCIPgetDepth(), SCIPgetNSolsFound(), SCIPheurGetData(), SCIPheurGetNCalls(), and setupAndSolveSubscip().

Referenced by SCIP_DECL_HEUREXEC().

SCIP

Detailed Description

Modules

Functions

Files

Function Documentation

◆ SCIPapplyHeurDualval()

◆ SCIPheurPassIndicator()

◆ SCIPapplyProximity()

◆ SCIPdeleteSubproblemProximity()

◆ SCIPapplyRens()

◆ SCIPreoptsolsGetNCheckedsols()

◆ SCIPreoptsolsGetNImprovingsols()

◆ SCIPapplyHeurSubNlp()

◆ SCIPupdateStartpointHeurSubNlp()

◆ SCIPgetStartCandidateHeurSubNlp()

◆ SCIPheurSyncPassSol()

◆ SCIPheurPassSolTrySol()

◆ SCIPheurPassSolAddSol()

◆ SCIPcomputeCoverUndercover()

◆ SCIPapplyZeroobj()