Detailed Description

multistart heuristic for convex and nonconvex MINLPs

Author: Benjamin Mueller

#include <assert.h>
#include <string.h>
#include "scip/heur_multistart.h"
#include "scip/heur_subnlp.h"
#include "nlpi/exprinterpret.h"

Go to the source code of this file.

Macros
#define	HEUR_NAME "multistart"

#define	HEUR_DESC "multistart heuristic for convex and nonconvex MINLPs"

#define	HEUR_DISPCHAR 'm'

#define	HEUR_PRIORITY -2100000

#define	HEUR_FREQ 0

#define	HEUR_FREQOFS 0

#define	HEUR_MAXDEPTH -1

#define	HEUR_TIMING SCIP_HEURTIMING_AFTERNODE

#define	HEUR_USESSUBSCIP TRUE

#define	DEFAULT_RANDSEED 131

#define	DEFAULT_NRNDPOINTS 100

#define	DEFAULT_MAXBOUNDSIZE 2e+4

#define	DEFAULT_MAXITER 300

#define	DEFAULT_MINIMPRFAC 0.05

#define	DEFAULT_MINIMPRITER 10

#define	DEFAULT_MAXRELDIST 0.15

#define	DEFAULT_NLPMINIMPR 0.00

#define	DEFAULT_GRADLIMIT 5e+6

#define	DEFAULT_MAXNCLUSTER 3

#define	DEFAULT_ONLYNLPS TRUE

#define	MINFEAS -1e+4

#define	MINIMPRFAC 0.95

#define	GRADCOSTFAC_LINEAR 1.0

#define	GRADCOSTFAC_QUAD 2.0

#define	GRADCOSTFAC_NONLINEAR 3.0

Functions
static int	getVarIndex (SCIP_HASHMAP varindex, SCIP_VAR var)

static SCIP_RETCODE	sampleRandomPoints (SCIP scip, SCIP_SOL rndpoints, int nmaxrndpoints, SCIP_Real maxboundsize, SCIP_RANDNUMGEN randnumgen, SCIP_Real bestobj, int *nstored)

static SCIP_RETCODE	getMinFeas (SCIP scip, SCIP_NLROW nlrows, int nnlrows, SCIP_SOL sol, SCIP_Real *minfeas)

static SCIP_RETCODE	computeGradient (SCIP scip, SCIP_NLROW nlrow, SCIP_EXPRINT exprint, SCIP_SOL sol, SCIP_HASHMAP varindex, SCIP_Real grad, SCIP_Real *norm)

static SCIP_RETCODE	improvePoint (SCIP scip, SCIP_NLROW nlrows, int nnlrows, SCIP_HASHMAP varindex, SCIP_EXPRINT exprinterpreter, SCIP_SOL point, int maxiter, SCIP_Real minimprfac, int minimpriter, SCIP_Real minfeas, SCIP_Real nlrowgradcosts, SCIP_Real *gradcosts)

static SCIP_RETCODE	filterPoints (SCIP scip, SCIP_SOL points, SCIP_Real feasibilities, int npoints, int *nusefulpoints)

static SCIP_Real	getRelDistance (SCIP scip, SCIP_SOL x, SCIP_SOL *y, SCIP_Real maxboundsize)

static SCIP_RETCODE	clusterPointsGreedy (SCIP scip, SCIP_SOL points, int npoints, int clusteridx, int *ncluster, SCIP_Real maxboundsize, SCIP_Real maxreldist, int maxncluster)

static SCIP_RETCODE	solveNLP (SCIP scip, SCIP_HEUR heur, SCIP_HEUR nlpheur, SCIP_SOL points, int npoints, SCIP_Longint itercontingent, SCIP_Real timelimit, SCIP_Real minimprove, SCIP_Bool success)

static int	getExprSize (SCIP_EXPR *expr)

static int	getExprtreeSize (SCIP_EXPRTREE *tree)

static SCIP_RETCODE	applyHeur (SCIP scip, SCIP_HEUR heur, SCIP_HEURDATA heurdata, SCIP_RESULT result)

static	SCIP_DECL_HEURCOPY (heurCopyMultistart)

static	SCIP_DECL_HEURFREE (heurFreeMultistart)

static	SCIP_DECL_HEURINIT (heurInitMultistart)

static	SCIP_DECL_HEUREXIT (heurExitMultistart)

static	SCIP_DECL_HEUREXEC (heurExecMultistart)

SCIP_RETCODE	SCIPincludeHeurMultistart (SCIP *scip)

Macro Definition Documentation

◆ HEUR_NAME

#define HEUR_NAME "multistart"

Definition at line 31 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ HEUR_DESC

#define HEUR_DESC "multistart heuristic for convex and nonconvex MINLPs"

Definition at line 32 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ HEUR_DISPCHAR

#define HEUR_DISPCHAR 'm'

Definition at line 33 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ HEUR_PRIORITY

#define HEUR_PRIORITY -2100000

Definition at line 34 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ HEUR_FREQ

#define HEUR_FREQ 0

Definition at line 35 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ HEUR_FREQOFS

#define HEUR_FREQOFS 0

Definition at line 36 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ HEUR_MAXDEPTH

#define HEUR_MAXDEPTH -1

Definition at line 37 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ HEUR_TIMING

#define HEUR_TIMING SCIP_HEURTIMING_AFTERNODE

Definition at line 38 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ HEUR_USESSUBSCIP

#define HEUR_USESSUBSCIP TRUE

does the heuristic use a secondary SCIP instance?

Definition at line 39 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ DEFAULT_RANDSEED

#define DEFAULT_RANDSEED 131

initial random seed

Definition at line 41 of file heur_multistart.c.

◆ DEFAULT_NRNDPOINTS

#define DEFAULT_NRNDPOINTS 100

default number of generated random points per call

Definition at line 42 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ DEFAULT_MAXBOUNDSIZE

#define DEFAULT_MAXBOUNDSIZE 2e+4

default maximum variable domain size for unbounded variables

Definition at line 43 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ DEFAULT_MAXITER

#define DEFAULT_MAXITER 300

default number of iterations to reduce the violation of a point

Definition at line 44 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ DEFAULT_MINIMPRFAC

#define DEFAULT_MINIMPRFAC 0.05

default minimum required improving factor to proceed in improvement of a point

Definition at line 45 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ DEFAULT_MINIMPRITER

#define DEFAULT_MINIMPRITER 10

default number of iteration when checking the minimum improvement

Definition at line 46 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ DEFAULT_MAXRELDIST

#define DEFAULT_MAXRELDIST 0.15

default maximum distance between two points in the same cluster

Definition at line 47 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ DEFAULT_NLPMINIMPR

#define DEFAULT_NLPMINIMPR 0.00

default factor by which heuristic should at least improve the incumbent

Definition at line 48 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ DEFAULT_GRADLIMIT

#define DEFAULT_GRADLIMIT 5e+6

default limit for gradient computations for all improvePoint() calls

Definition at line 49 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ DEFAULT_MAXNCLUSTER

#define DEFAULT_MAXNCLUSTER 3

default maximum number of considered clusters per heuristic call

Definition at line 50 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ DEFAULT_ONLYNLPS

#define DEFAULT_ONLYNLPS TRUE

should the heuristic run only on continuous problems?

Definition at line 51 of file heur_multistart.c.

Referenced by SCIPincludeHeurMultistart().

◆ MINFEAS

#define MINFEAS -1e+4

minimum feasibility for a point; used for filtering and improving feasibility

Definition at line 53 of file heur_multistart.c.

Referenced by filterPoints(), and improvePoint().

◆ MINIMPRFAC

#define MINIMPRFAC 0.95

improvement factor used to discard randomly generated points with a too large objective value

Definition at line 56 of file heur_multistart.c.

Referenced by applyHeur().

◆ GRADCOSTFAC_LINEAR

#define GRADCOSTFAC_LINEAR 1.0

gradient cost factor for the number of linear variables

Definition at line 59 of file heur_multistart.c.

Referenced by applyHeur().

◆ GRADCOSTFAC_QUAD

#define GRADCOSTFAC_QUAD 2.0

gradient cost factor for the number of quadratic terms

Definition at line 60 of file heur_multistart.c.

Referenced by applyHeur().

◆ GRADCOSTFAC_NONLINEAR

#define GRADCOSTFAC_NONLINEAR 3.0

gradient cost factor for the number of nodes in nonlinear expression

Definition at line 61 of file heur_multistart.c.

Referenced by applyHeur().

Function Documentation

◆ getVarIndex()

static int getVarIndex	(	SCIP_HASHMAP *	varindex,
		SCIP_VAR *	var
	)

static

returns an unique index of a variable in the range of 0,..,SCIPgetNVars(scip)-1

Parameters

varindex	maps variables to indicies between 0,..,SCIPgetNVars(scip)-1
var	variable

Definition at line 96 of file heur_multistart.c.

References sampleRandomPoints(), SCIPhashmapExists(), and SCIPhashmapGetImage().

Referenced by computeGradient().

◆ sampleRandomPoints()

static SCIP_RETCODE sampleRandomPoints	(	SCIP *	scip,
		SCIP_SOL **	rndpoints,
		int	nmaxrndpoints,
		SCIP_Real	maxboundsize,
		SCIP_RANDNUMGEN *	randnumgen,
		SCIP_Real	bestobj,
		int *	nstored
	)

static

samples and stores random points; stores points which have a better objective value than the current incumbent solution

Parameters

scip	SCIP data structure
rndpoints	array to store all random points
nmaxrndpoints	maximum number of random points to compute
maxboundsize	maximum variable domain size for unbounded variables
randnumgen	random number generator
bestobj	objective value in the transformed space of the current incumbent
nstored	pointer to store the number of randomly generated points

Definition at line 115 of file heur_multistart.c.

References getMinFeas(), MAX, SCIP_CALL, SCIP_OKAY, SCIP_Real, SCIP_VARTYPE_CONTINUOUS, SCIPcreateSol(), SCIPcreateSolCopy(), SCIPdebugMsg, SCIPfeasRound(), SCIPfreeSol(), SCIPgetNVars(), SCIPgetSolTransObj(), SCIPgetVars(), SCIPisFeasEQ(), SCIPisFeasGE(), SCIPisFeasLE(), SCIPisInfinity(), SCIPisLE(), SCIPrandomGetReal(), SCIPsetSolVal(), SCIPvarGetLbLocal(), SCIPvarGetType(), and SCIPvarGetUbLocal().

Referenced by applyHeur(), and getVarIndex().

◆ getMinFeas()

static SCIP_RETCODE getMinFeas	(	SCIP *	scip,
		SCIP_NLROW **	nlrows,
		int	nnlrows,
		SCIP_SOL *	sol,
		SCIP_Real *	minfeas
	)

static

computes the minimum feasibility of a given point; a negative value means that there is an infeasibility

Parameters

scip	SCIP data structure
nlrows	array containing all nlrows
nnlrows	total number of nlrows
sol	solution
minfeas	buffer to store the minimum feasibility

Definition at line 193 of file heur_multistart.c.

References computeGradient(), SCIP_CALL, SCIP_OKAY, SCIP_Real, SCIPgetNlRowSolFeasibility(), and SCIPinfinity().

Referenced by improvePoint(), and sampleRandomPoints().

◆ computeGradient()

static SCIP_RETCODE computeGradient	(	SCIP *	scip,
		SCIP_NLROW *	nlrow,
		SCIP_EXPRINT *	exprint,
		SCIP_SOL *	sol,
		SCIP_HASHMAP *	varindex,
		SCIP_Real *	grad,
		SCIP_Real *	norm
	)

static

computes the gradient for a given point and nonlinear row

Parameters

scip	SCIP data structure
nlrow	nonlinear row
exprint	expressions interpreter
sol	solution to compute the gradient for
varindex	maps variables to indicies between 0,..,SCIPgetNVars(scip)-1 uniquely
grad	buffer to store the gradient; grad[varindex(i)] corresponds to SCIPgetVars(scip)[i]
norm	buffer to store \|\|grad\|\|^2

Definition at line 225 of file heur_multistart.c.

References BMSclearMemoryArray, SCIP_QuadElement::coef, getVarIndex(), SCIP_QuadElement::idx1, SCIP_QuadElement::idx2, improvePoint(), SCIP_CALL, SCIP_OKAY, SCIP_Real, SCIPallocBufferArray, SCIPexprintCompile(), SCIPexprintGrad(), SCIPexprtreeGetInterpreterData(), SCIPexprtreeGetNVars(), SCIPexprtreeGetVars(), SCIPfreeBufferArray, SCIPgetNVars(), SCIPgetSolVal(), SCIPnlrowGetExprtree(), SCIPnlrowGetLinearCoefs(), SCIPnlrowGetLinearVars(), SCIPnlrowGetNLinearVars(), SCIPnlrowGetNQuadElems(), SCIPnlrowGetNQuadVars(), SCIPnlrowGetQuadElems(), SCIPnlrowGetQuadVars(), and TRUE.

Referenced by getMinFeas(), and improvePoint().

◆ improvePoint()

static SCIP_RETCODE improvePoint	(	SCIP *	scip,
		SCIP_NLROW **	nlrows,
		int	nnlrows,
		SCIP_HASHMAP *	varindex,
		SCIP_EXPRINT *	exprinterpreter,
		SCIP_SOL *	point,
		int	maxiter,
		SCIP_Real	minimprfac,
		int	minimpriter,
		SCIP_Real *	minfeas,
		SCIP_Real *	nlrowgradcosts,
		SCIP_Real *	gradcosts
	)

static

use consensus vectors to improve feasibility for a given starting point

Parameters

scip	SCIP data structure
nlrows	array containing all nlrows
nnlrows	total number of nlrows
varindex	maps variables to indicies between 0,..,SCIPgetNVars(scip)-1
exprinterpreter	expression interpreter
point	random generated point
maxiter	maximum number of iterations
minimprfac	minimum required improving factor to proceed in the improvement of a single point
minimpriter	number of iteration when checking the minimum improvement
minfeas	pointer to store the minimum feasibility
nlrowgradcosts	estimated costs for each gradient computation
gradcosts	pointer to store the estimated gradient costs

Definition at line 325 of file heur_multistart.c.

References BMSclearMemoryArray, computeGradient(), filterPoints(), getMinFeas(), MAX, MINFEAS, REALABS, SCIP_CALL, SCIP_OKAY, SCIP_Real, SCIPallocBufferArray, SCIPfreeBufferArray, SCIPgetNlRowSolActivity(), SCIPgetNlRowSolFeasibility(), SCIPgetNVars(), SCIPgetSolVal(), SCIPgetVars(), SCIPisEQ(), SCIPisFeasGE(), SCIPisFeasLT(), SCIPisGT(), SCIPisHugeValue(), SCIPisInfinity(), SCIPisZero(), SCIPnlrowGetRhs(), SCIPsetSolVal(), SCIPvarGetLbLocal(), and SCIPvarGetUbLocal().

Referenced by applyHeur(), and computeGradient().

◆ filterPoints()

static SCIP_RETCODE filterPoints	(	SCIP *	scip,
		SCIP_SOL **	points,
		SCIP_Real *	feasibilities,
		int	npoints,
		int *	nusefulpoints
	)

static

sorts points w.r.t their feasibilities; points with a feasibility which is too small (w.r.t. the geometric mean of all feasibilities) will be filtered out

Parameters

scip	SCIP data structure
points	array containing improved points
feasibilities	array containing feasibility for each point (sorted)
npoints	total number of points
nusefulpoints	pointer to store the total number of useful points

Definition at line 473 of file heur_multistart.c.

References getRelDistance(), MINFEAS, npoints, pow(), SCIP_OKAY, SCIP_Real, SCIPdebugMsg, SCIPisFeasGE(), SCIPisFeasLT(), SCIPisLE(), and SCIPsortDownRealPtr().

Referenced by applyHeur(), and improvePoint().

◆ getRelDistance()

static SCIP_Real getRelDistance	(	SCIP *	scip,
		SCIP_SOL *	x,
		SCIP_SOL *	y,
		SCIP_Real	maxboundsize
	)

static

returns the relative distance between two points; considers a smaller bounded domain for unbounded variables

Parameters

scip	SCIP data structure
x	first point
y	second point
maxboundsize	maximum variable domain size for unbounded variables

Definition at line 528 of file heur_multistart.c.

References clusterPointsGreedy(), MAX, REALABS, SCIP_Real, SCIPgetNVars(), SCIPgetSolVal(), SCIPgetVars(), SCIPisInfinity(), SCIPvarGetLbLocal(), and SCIPvarGetUbLocal().

Referenced by clusterPointsGreedy(), and filterPoints().

◆ clusterPointsGreedy()

static SCIP_RETCODE clusterPointsGreedy	(	SCIP *	scip,
		SCIP_SOL **	points,
		int	npoints,
		int *	clusteridx,
		int *	ncluster,
		SCIP_Real	maxboundsize,
		SCIP_Real	maxreldist,
		int	maxncluster
	)

static

cluster useful points with a greedy algorithm

Parameters

scip	SCIP data structure
points	array containing improved points
npoints	total number of points
clusteridx	array to store for each point the index of the cluster
ncluster	pointer to store the total number of cluster
maxboundsize	maximum variable domain size for unbounded variables
maxreldist	maximum relative distance between any two points of the same cluster
maxncluster	maximum number of clusters to compute

Definition at line 584 of file heur_multistart.c.

References getRelDistance(), npoints, SCIP_OKAY, and solveNLP().

Referenced by applyHeur(), and getRelDistance().

◆ solveNLP()

static SCIP_RETCODE solveNLP	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		SCIP_HEUR *	nlpheur,
		SCIP_SOL **	points,
		int	npoints,
		SCIP_Longint	itercontingent,
		SCIP_Real	timelimit,
		SCIP_Real	minimprove,
		SCIP_Bool *	success
	)

static

calls the sub-NLP heuristic for a given cluster

Parameters

scip	SCIP data structure
heur	multi-start heuristic
nlpheur	pointer to NLP local search heuristics
points	array containing improved points
npoints	total number of points
itercontingent	iteration limit for NLP solver
timelimit	time limit for NLP solver
minimprove	desired minimal relative improvement in objective function value
success	pointer to store if we could find a solution

Definition at line 643 of file heur_multistart.c.

References FALSE, getExprSize(), MAX, npoints, SCIP_CALL, SCIP_FOUNDSOL, SCIP_OKAY, SCIP_Real, SCIPapplyHeurSubNlp(), SCIPcreateSol(), SCIPdebugMsg, SCIPfreeSol(), SCIPgetSolVal(), SCIPgetVarsData(), SCIPisFeasIntegral(), SCIPround(), SCIProundSol(), SCIPsetSolVal(), SCIPvarGetLbLocal(), and SCIPvarGetUbLocal().

Referenced by applyHeur(), and clusterPointsGreedy().

◆ getExprSize()

static int getExprSize ( SCIP_EXPR * expr )

static

recursive helper function to count the number of nodes in a sub-tree

Parameters

expr	expression

Definition at line 728 of file heur_multistart.c.

References getExprtreeSize(), SCIPexprGetChildren(), and SCIPexprGetNChildren().

Referenced by getExprtreeSize(), and solveNLP().

◆ getExprtreeSize()

static int getExprtreeSize ( SCIP_EXPRTREE * tree )

static

returns the number of nodes in an expression tree

Parameters

tree	expression tree

Definition at line 748 of file heur_multistart.c.

References applyHeur(), getExprSize(), and SCIPexprtreeGetRoot().

Referenced by applyHeur(), and getExprSize().

◆ applyHeur()

static SCIP_RETCODE applyHeur	(	SCIP *	scip,
		SCIP_HEUR *	heur,
		SCIP_HEURDATA *	heurdata,
		SCIP_RESULT *	result
	)

static

main function of the multi-start heuristic (see heur_multistart.h for more details); it consists of the following four steps:

sampling points in the current domain; for unbounded variables we use a bounded box
reduce infeasibility by using a gradient descent method
cluster points; filter points with a too large infeasibility
compute start point for each cluster and use it in the sub-NLP heuristic (heur_subnlp.h)

Parameters

scip	SCIP data structure
heur	heuristic
heurdata	heuristic data
result	pointer to store the result

Definition at line 769 of file heur_multistart.c.

References clusterPointsGreedy(), filterPoints(), getExprtreeSize(), GRADCOSTFAC_LINEAR, GRADCOSTFAC_NONLINEAR, GRADCOSTFAC_QUAD, improvePoint(), MINIMPRFAC, npoints, sampleRandomPoints(), SCIP_Bool, SCIP_CALL, SCIP_DECL_HEURCOPY(), SCIP_FOUNDSOL, SCIP_OKAY, SCIP_Real, SCIPallocBufferArray, SCIPblkmem(), SCIPdebugMsg, SCIPexprintCreate(), SCIPfreeBufferArray, SCIPfreeSol(), SCIPgetBestSol(), SCIPgetNLPNlRows(), SCIPgetNNLPNlRows(), SCIPgetNSols(), SCIPgetNVars(), SCIPgetRealParam(), SCIPgetSolTransObj(), SCIPgetSolvingTime(), SCIPgetVars(), SCIPhashmapCreate(), SCIPhashmapFree(), SCIPhashmapInsert(), SCIPinfinity(), SCIPisInfinity(), SCIPisStopped(), SCIPnlrowGetExprtree(), SCIPnlrowGetNLinearVars(), SCIPnlrowGetNQuadElems(), SCIPsortIntPtr(), and solveNLP().

Referenced by getExprtreeSize().

◆ SCIP_DECL_HEURCOPY()

static SCIP_DECL_HEURCOPY ( heurCopyMultistart )

static

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

Definition at line 937 of file heur_multistart.c.

Referenced by applyHeur().

◆ SCIP_DECL_HEURFREE()

static SCIP_DECL_HEURFREE ( heurFreeMultistart )

static

destructor of primal heuristic to free user data (called when SCIP is exiting)

Definition at line 949 of file heur_multistart.c.

◆ SCIP_DECL_HEURINIT()

static SCIP_DECL_HEURINIT ( heurInitMultistart )

static

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

Definition at line 969 of file heur_multistart.c.

◆ SCIP_DECL_HEUREXIT()

static SCIP_DECL_HEUREXIT ( heurExitMultistart )

static

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

Definition at line 989 of file heur_multistart.c.

◆ SCIP_DECL_HEUREXEC()

static SCIP_DECL_HEUREXEC ( heurExecMultistart )

static

execution method of primal heuristic

Definition at line 1006 of file heur_multistart.c.

SCIP

Detailed Description

Macros

Functions

Macro Definition Documentation

◆ HEUR_NAME

◆ HEUR_DESC

◆ HEUR_DISPCHAR

◆ HEUR_PRIORITY

◆ HEUR_FREQ

◆ HEUR_FREQOFS

◆ HEUR_MAXDEPTH

◆ HEUR_TIMING

◆ HEUR_USESSUBSCIP

◆ DEFAULT_RANDSEED

◆ DEFAULT_NRNDPOINTS

◆ DEFAULT_MAXBOUNDSIZE

◆ DEFAULT_MAXITER

◆ DEFAULT_MINIMPRFAC

◆ DEFAULT_MINIMPRITER

◆ DEFAULT_MAXRELDIST

◆ DEFAULT_NLPMINIMPR

◆ DEFAULT_GRADLIMIT

◆ DEFAULT_MAXNCLUSTER

◆ DEFAULT_ONLYNLPS

◆ MINFEAS

◆ MINIMPRFAC

◆ GRADCOSTFAC_LINEAR

◆ GRADCOSTFAC_QUAD

◆ GRADCOSTFAC_NONLINEAR

Function Documentation

◆ getVarIndex()

◆ sampleRandomPoints()

◆ getMinFeas()

◆ computeGradient()

◆ improvePoint()

◆ filterPoints()

◆ getRelDistance()

◆ clusterPointsGreedy()

◆ solveNLP()

◆ getExprSize()

◆ getExprtreeSize()

◆ applyHeur()

◆ SCIP_DECL_HEURCOPY()

◆ SCIP_DECL_HEURFREE()

◆ SCIP_DECL_HEURINIT()

◆ SCIP_DECL_HEUREXIT()

◆ SCIP_DECL_HEUREXEC()