SCIP Doxygen Documentation
 
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Detailed Description

methods for the nonlinear relaxation

Topics

 Nonlinear Rows
 methods for the creation and interaction with rows of the NLP relaxation
 
 NLP Diving
 methods to initiate and conduct NLP Diving
 

Macros

#define SCIPsolveNLP(...)
 

Functions

SCIP_Bool SCIPisNLPEnabled (SCIP *scip)
 
void SCIPenableNLP (SCIP *scip)
 
SCIP_Bool SCIPisNLPConstructed (SCIP *scip)
 
SCIP_RETCODE SCIPhasNLPContinuousNonlinearity (SCIP *scip, SCIP_Bool *result)
 
SCIP_RETCODE SCIPgetNLPVarsData (SCIP *scip, SCIP_VAR ***vars, int *nvars)
 
SCIP_VAR ** SCIPgetNLPVars (SCIP *scip)
 
int SCIPgetNNLPVars (SCIP *scip)
 
SCIP_RETCODE SCIPgetNLPVarsNonlinearity (SCIP *scip, int *nlcount)
 
SCIP_RealSCIPgetNLPVarsLbDualsol (SCIP *scip)
 
SCIP_RealSCIPgetNLPVarsUbDualsol (SCIP *scip)
 
SCIP_RETCODE SCIPgetNLPNlRowsData (SCIP *scip, SCIP_NLROW ***nlrows, int *nnlrows)
 
SCIP_NLROW ** SCIPgetNLPNlRows (SCIP *scip)
 
int SCIPgetNNLPNlRows (SCIP *scip)
 
SCIP_RETCODE SCIPgetNLPNlRowsStat (SCIP *scip, int *nlinear, int *nconvexineq, int *nnonconvexineq, int *nnonlineareq)
 
SCIP_RETCODE SCIPaddNlRow (SCIP *scip, SCIP_NLROW *nlrow)
 
SCIP_RETCODE SCIPdelNlRow (SCIP *scip, SCIP_NLROW *nlrow)
 
SCIP_RETCODE SCIPflushNLP (SCIP *scip)
 
SCIP_RETCODE SCIPsetNLPInitialGuess (SCIP *scip, SCIP_Real *initialguess)
 
SCIP_RETCODE SCIPsetNLPInitialGuessSol (SCIP *scip, SCIP_SOL *sol)
 
SCIP_RETCODE SCIPsolveNLPParam (SCIP *scip, SCIP_NLPPARAM param)
 
SCIP_NLPSOLSTAT SCIPgetNLPSolstat (SCIP *scip)
 
SCIP_NLPTERMSTAT SCIPgetNLPTermstat (SCIP *scip)
 
SCIP_RETCODE SCIPgetNLPStatistics (SCIP *scip, SCIP_NLPSTATISTICS *statistics)
 
SCIP_Real SCIPgetNLPObjval (SCIP *scip)
 
SCIP_Bool SCIPhasNLPSolution (SCIP *scip)
 
SCIP_RETCODE SCIPgetNLPFracVars (SCIP *scip, SCIP_VAR ***fracvars, SCIP_Real **fracvarssol, SCIP_Real **fracvarsfrac, int *nfracvars, int *npriofracvars)
 
SCIP_RETCODE SCIPwriteNLP (SCIP *scip, const char *filename)
 
SCIP_RETCODE SCIPgetNLPI (SCIP *scip, SCIP_NLPI **nlpi, SCIP_NLPIPROBLEM **nlpiproblem)
 

Macro Definition Documentation

◆ SCIPsolveNLP

#define SCIPsolveNLP ( ...)
Value:
SCIPsolveNLPParam(SCIP_VARARGS_FIRST((__VA_ARGS__, ignored)), \
(SCIP_NLPPARAM){ SCIP_NLPPARAM_DEFAULT_INITS(SCIP_VARARGS_FIRST((__VA_ARGS__, ignored))), SCIP_VARARGS_REST(__VA_ARGS__, .caller = __FILE__) })
#define SCIP_VARARGS_FIRST(args)
Definition def.h:81
#define SCIP_VARARGS_REST(firstarg,...)
Definition def.h:84
SCIP_RETCODE SCIPsolveNLPParam(SCIP *scip, SCIP_NLPPARAM param)
Definition scip_nlp.c:545
#define SCIP_NLPPARAM_DEFAULT_INITS(scip)
Definition type_nlpi.h:102

solves the current NLP (or diving NLP if in diving mode) with non-default parameters given as optional arguments

Typical use is

SCIP_CALL( SCIPsolveNLP(scip) );

to solve with default parameters. Additionally, one or several values of SCIP_NLPPARAM can be set:

SCIP_CALL( SCIPsolveNLP(scip, .iterlimit = 42, .verblevel = 1) );    //lint !e666
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:

Definition at line 361 of file scip_nlp.h.

Referenced by computeFixingrate(), getFixingValue(), SCIP_DECL_HEUREXEC(), SCIPapplyHeurDualval(), and solveSubNLP().

Function Documentation

◆ SCIPisNLPEnabled()

SCIP_Bool SCIPisNLPEnabled ( SCIP * scip)

returns whether the NLP relaxation has been enabled

If the NLP relaxation is enabled, then SCIP will construct the NLP relaxation when the solving process is about to begin. To check whether an NLP is existing, use SCIPisNLPConstructed().

Precondition
This method can be called if SCIP is in one of the following stages:
See also
SCIPenableNLP
Parameters
scipSCIP data structure

Definition at line 74 of file scip_nlp.c.

References FALSE, SCIP_CALL_ABORT, SCIPcheckStage(), and TRUE.

Referenced by SCIP_DECL_PRESOLEXEC(), SCIP_DECL_PRESOLEXEC(), SCIP_DECL_PRESOLEXEC(), SCIP_DECL_PRESOLEXEC(), SCIP_DECL_PRESOLEXEC(), and setupAndSolve().

◆ SCIPenableNLP()

void SCIPenableNLP ( SCIP * scip)

notifies SCIP that the NLP relaxation should be initialized in INITSOLVE

This method is typically called by a constraint handler that handles constraints that have a nonlinear representation as nonlinear rows, e.g., cons_nonlinear.

The function should be called before the branch-and-bound process is initialized, e.g., when presolve is exiting.

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure

Definition at line 95 of file scip_nlp.c.

References FALSE, SCIP_CALL_ABORT, SCIPcheckStage(), and TRUE.

Referenced by SCIP_DECL_CONSEXITPRE().

◆ SCIPisNLPConstructed()

SCIP_Bool SCIPisNLPConstructed ( SCIP * scip)

returns, whether an NLP has been constructed

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure

Definition at line 110 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL_ABORT, SCIPcheckStage(), and TRUE.

Referenced by addNlrow(), addNlrow(), addNlrow(), addNlrow(), addNlrow(), addNlrow(), addNlrow(), computeFixingrate(), computeStandardNLPFeasibilityCut(), computeStandardNLPOptimalityCut(), countNonlinearities(), createSubSCIP(), generateAndApplyBendersCuts(), getFixingValue(), initBounds(), initSolve(), isRestartApplicable(), runHeuristic(), SCIP_DECL_BENDERSCUTEXEC(), SCIP_DECL_BENDERSCUTEXEC(), SCIP_DECL_BENDERSCUTEXEC(), SCIP_DECL_CONSACTIVE(), SCIP_DECL_CONSACTIVE(), SCIP_DECL_CONSACTIVE(), SCIP_DECL_CONSACTIVE(), SCIP_DECL_CONSACTIVE(), SCIP_DECL_CONSACTIVE(), SCIP_DECL_CONSACTIVE(), SCIP_DECL_CONSINITSOL(), SCIP_DECL_CONSINITSOL(), SCIP_DECL_CONSINITSOL(), SCIP_DECL_CONSINITSOL(), SCIP_DECL_CONSINITSOL(), SCIP_DECL_CONSINITSOL(), SCIP_DECL_CONSINITSOL(), SCIP_DECL_CONSINITSOL(), SCIP_DECL_CONSINITSOL(), SCIP_DECL_DIALOGEXEC(), SCIP_DECL_DIALOGEXEC(), SCIP_DECL_HEUREXEC(), SCIP_DECL_HEUREXEC(), SCIP_DECL_HEUREXEC(), SCIP_DECL_HEUREXEC(), SCIP_DECL_PROPEXEC(), SCIP_DECL_PROPEXEC(), SCIP_DECL_RELAXEXEC(), SCIP_DECL_SEPAEXECLP(), SCIP_DECL_SEPAEXECLP(), SCIP_DECL_SEPAEXECLP(), SCIPapplyHeurDualval(), SCIPapplyUndercover(), SCIPbendersComputeSubproblemLowerbound(), SCIPbendersSolSlackVarsActive(), SCIPbendersSolveSubproblemLP(), SCIPcreateNLPSol(), SCIPgenerateAndApplyBendersOptCut(), solveLp(), and solveSubNLP().

◆ SCIPhasNLPContinuousNonlinearity()

SCIP_RETCODE SCIPhasNLPContinuousNonlinearity ( SCIP * scip,
SCIP_Bool * result )

checks whether the NLP has a continuous variable in a nonlinear term

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure
resultbuffer to store result

Definition at line 125 of file scip_nlp.c.

References FALSE, NULL, result, SCIP_CALL, SCIP_ERROR, SCIP_OKAY, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpHasContinuousNonlinearity(), and TRUE.

Referenced by runHeuristic().

◆ SCIPgetNLPVarsData()

SCIP_RETCODE SCIPgetNLPVarsData ( SCIP * scip,
SCIP_VAR *** vars,
int * nvars )

gets current NLP variables along with the current number of NLP variables

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure
varspointer to store the array of NLP variables, or NULL
nvarspointer to store the number of NLP variables, or NULL

Definition at line 149 of file scip_nlp.c.

References FALSE, NULL, nvars, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetNVars(), SCIPnlpGetVars(), TRUE, and vars.

◆ SCIPgetNLPVars()

SCIP_VAR ** SCIPgetNLPVars ( SCIP * scip)

gets array with variables of the NLP

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure

Definition at line 179 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL_ABORT, SCIPABORT, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetVars(), and TRUE.

Referenced by computeStandardNLPOptimalityCut(), SCIPapplyHeurDualval(), separateCuts(), and solveSubNLP().

◆ SCIPgetNNLPVars()

int SCIPgetNNLPVars ( SCIP * scip)

gets current number of variables in NLP

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure

Definition at line 201 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL_ABORT, SCIPABORT, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetNVars(), and TRUE.

Referenced by computeStandardNLPOptimalityCut(), countNonlinearities(), initBounds(), SCIPapplyHeurDualval(), separateCuts(), and solveSubNLP().

◆ SCIPgetNLPVarsNonlinearity()

SCIP_RETCODE SCIPgetNLPVarsNonlinearity ( SCIP * scip,
int * nlcount )

computes for each variables the number of NLP rows in which the variable appears in the nonlinear part

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure
nlcountan array of length at least SCIPnlpGetNVars() to store nonlinearity counts of variables

Definition at line 223 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetVarsNonlinearity(), and TRUE.

Referenced by countNonlinearities(), and initBounds().

◆ SCIPgetNLPVarsLbDualsol()

SCIP_Real * SCIPgetNLPVarsLbDualsol ( SCIP * scip)

returns dual solution values associated with lower bounds of NLP variables

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure

Definition at line 247 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL_ABORT, SCIPABORT, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetVarsLbDualsol(), and TRUE.

◆ SCIPgetNLPVarsUbDualsol()

SCIP_Real * SCIPgetNLPVarsUbDualsol ( SCIP * scip)

returns dual solution values associated with upper bounds of NLP variables

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure

Definition at line 269 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL_ABORT, SCIPABORT, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetVarsUbDualsol(), and TRUE.

◆ SCIPgetNLPNlRowsData()

SCIP_RETCODE SCIPgetNLPNlRowsData ( SCIP * scip,
SCIP_NLROW *** nlrows,
int * nnlrows )

gets current NLP nonlinear rows along with the current number of NLP nonlinear rows

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure
nlrowspointer to store the array of NLP nonlinear rows, or NULL
nnlrowspointer to store the number of NLP nonlinear rows, or NULL

Definition at line 291 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetNlRows(), SCIPnlpGetNNlRows(), and TRUE.

◆ SCIPgetNLPNlRows()

SCIP_NLROW ** SCIPgetNLPNlRows ( SCIP * scip)

◆ SCIPgetNNLPNlRows()

◆ SCIPgetNLPNlRowsStat()

SCIP_RETCODE SCIPgetNLPNlRowsStat ( SCIP * scip,
int * nlinear,
int * nconvexineq,
int * nnonconvexineq,
int * nnonlineareq )

gets statistics on convexity of rows in NLP

Reports counts on the current number of linear rows, convex inequalities, nonconvex inequalities, and nonlinear equalities or ranged rows.

  • A nonlinear inequality with infinity left-hand-side is accounted as convex if its expression has been marked as convex.
  • A nonlinear inequality with infinity right-hand-side is accounted as convex if its expression has been marked as concave.
  • Other nonlinear rows are accounted as nonconvex. Note that convexity for a nonlinear row may just not have been detected.
Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure
nlinearbuffer to store number of linear rows in NLP, or NULL
nconvexineqbuffer to store number of convex inequalities in NLP, or NULL
nnonconvexineqbuffer to store number of nonconvex inequalities in NLP, or NULL
nnonlineareqbuffer to store number of nonlinear equalities or ranged rows in NLP, or NULL

Definition at line 369 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_ERROR, SCIP_OKAY, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetNlRowsStat(), and TRUE.

Referenced by SCIPprintNLPStatistics().

◆ SCIPaddNlRow()

SCIP_RETCODE SCIPaddNlRow ( SCIP * scip,
SCIP_NLROW * nlrow )

adds a nonlinear row to the NLP. This row is captured by the NLP.

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure
nlrownonlinear row to add to NLP

Definition at line 396 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPblkmem(), SCIPcheckStage(), SCIPerrorMessage, SCIPnlpAddNlRow(), and TRUE.

Referenced by addKnapsackConstraints(), addLinearConstraints(), addLogicOrConstraints(), addNlrow(), addNlrow(), addNlrow(), addNlrow(), addNlrow(), addNlrow(), addNlrow(), addSetppcConstraints(), addVarboundConstraints(), initSolve(), SCIP_DECL_CONSINITSOL(), and SCIP_DECL_CONSINITSOL().

◆ SCIPdelNlRow()

SCIP_RETCODE SCIPdelNlRow ( SCIP * scip,
SCIP_NLROW * nlrow )

removes a nonlinear row from the NLP

This row is released in the NLP.

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure
nlrownonlinear row to add to NLP

Definition at line 424 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPblkmem(), SCIPcheckStage(), SCIPerrorMessage, SCIPnlpDelNlRow(), and TRUE.

Referenced by deinitSolve(), SCIP_DECL_CONSDEACTIVE(), SCIP_DECL_CONSDEACTIVE(), SCIP_DECL_CONSDEACTIVE(), SCIP_DECL_CONSDEACTIVE(), SCIP_DECL_CONSDEACTIVE(), SCIP_DECL_CONSDEACTIVE(), and SCIP_DECL_CONSDEACTIVE().

◆ SCIPflushNLP()

SCIP_RETCODE SCIPflushNLP ( SCIP * scip)

makes sure that the NLP of the current node is flushed

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure

Definition at line 448 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpFlush(), and TRUE.

◆ SCIPsetNLPInitialGuess()

SCIP_RETCODE SCIPsetNLPInitialGuess ( SCIP * scip,
SCIP_Real * initialguess )

sets or clears initial primal guess for NLP solution (start point for NLP solver)

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
initialguessvalues of initial guess (corresponding to variables from SCIPgetNLPVarsData), or NULL to use no start point

Definition at line 474 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPblkmem(), SCIPcheckStage(), SCIPerrorMessage, SCIPnlpSetInitialGuess(), and TRUE.

Referenced by SCIPapplyHeurDualval(), and solveSubNLP().

◆ SCIPsetNLPInitialGuessSol()

SCIP_RETCODE SCIPsetNLPInitialGuessSol ( SCIP * scip,
SCIP_SOL * sol )

sets initial primal guess for NLP solution (start point for NLP solver)

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
solsolution which values should be taken as initial guess, or NULL for LP solution

Definition at line 501 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPallocBufferArray, SCIPblkmem(), SCIPcheckStage(), SCIPerrorMessage, SCIPfreeBufferArray, SCIPgetSolVals(), SCIPnlpGetNVars(), SCIPnlpGetVars(), SCIPnlpSetInitialGuess(), sol, and TRUE.

Referenced by computeFixingrate(), getFixingValue(), and SCIP_DECL_HEUREXEC().

◆ SCIPsolveNLPParam()

SCIP_RETCODE SCIPsolveNLPParam ( SCIP * scip,
SCIP_NLPPARAM param )

solves the current NLP (or diving NLP if in diving mode) with given parameters

Typical use is

SCIP_NLPPARAM nlparam = { SCIP_NLPPARAM_DEFAULT(scip); }
nlpparam.iterlimit = 42;
SCIP_CALL( SCIPsolveNLPParam(scip, nlpparam) );

or, in one line:

SCIP_CALL( SCIPsolveNLPParam(scip, (SCIP_NLPPARAM){ SCIP_NLPPARAM_DEFAULT(scip), .iterlimit = 42 }) );

To get the latter, also SCIPsolveNLP can be used.

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
paramNLP solve parameters

Definition at line 545 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPblkmem(), SCIPcheckStage(), SCIPerrorMessage, SCIPnlpSolve(), and TRUE.

Referenced by resolveNLPWithTighterFeastol(), SCIPbendersComputeSubproblemLowerbound(), and SCIPbendersSolveSubproblemLP().

◆ SCIPgetNLPSolstat()

◆ SCIPgetNLPTermstat()

SCIP_NLPTERMSTAT SCIPgetNLPTermstat ( SCIP * scip)

gets termination status of last NLP solve

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure

Definition at line 596 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL_ABORT, SCIP_NLPTERMSTAT_OTHER, SCIPABORT, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetTermstat(), and TRUE.

Referenced by resolveNLPWithTighterFeastol(), SCIP_DECL_HEUREXEC(), SCIPbendersComputeSubproblemLowerbound(), SCIPbendersSolveSubproblemLP(), and solveSubNLP().

◆ SCIPgetNLPStatistics()

SCIP_RETCODE SCIPgetNLPStatistics ( SCIP * scip,
SCIP_NLPSTATISTICS * statistics )

gives statistics (number of iterations, solving time, ...) of last NLP solve

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
statisticspointer to store statistics

Definition at line 621 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetStatistics(), and TRUE.

Referenced by SCIP_DECL_HEUREXEC(), and solveSubNLP().

◆ SCIPgetNLPObjval()

SCIP_Real SCIPgetNLPObjval ( SCIP * scip)

gets objective value of current NLP

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure

Definition at line 645 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL_ABORT, SCIP_INVALID, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetObjval(), and TRUE.

Referenced by processNLPSol(), SCIP_DECL_HEUREXEC(), SCIPbendersComputeSubproblemLowerbound(), SCIPbendersSolveSubproblemLP(), separateCuts(), and solveSubNLP().

◆ SCIPhasNLPSolution()

SCIP_Bool SCIPhasNLPSolution ( SCIP * scip)

indicates whether a solution for the current NLP is available

The solution may be optimal, feasible, or infeasible. Thus, returns whether the NLP solution status is at most SCIP_NLPSOLSTAT_LOCINFEASIBLE.

Precondition
This method can be called if SCIP is in one of the following stages:
Parameters
scipSCIP data structure

Definition at line 671 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL_ABORT, SCIPABORT, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpHasSolution(), and TRUE.

Referenced by computeStandardNLPOptimalityCut(), createSolFromNLP(), and processNLPSol().

◆ SCIPgetNLPFracVars()

SCIP_RETCODE SCIPgetNLPFracVars ( SCIP * scip,
SCIP_VAR *** fracvars,
SCIP_Real ** fracvarssol,
SCIP_Real ** fracvarsfrac,
int * nfracvars,
int * npriofracvars )

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
fracvarspointer to store the array of NLP fractional variables, or NULL
fracvarssolpointer to store the array of NLP fractional variables solution values, or NULL
fracvarsfracpointer to store the array of NLP fractional variables fractionalities, or NULL
nfracvarspointer to store the number of NLP fractional variables , or NULL
npriofracvarspointer to store the number of NLP fractional variables with maximal branching priority, or NULL

Definition at line 696 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPblkmem(), SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetFracVars(), and TRUE.

Referenced by getNLPFracVars().

◆ SCIPwriteNLP()

SCIP_RETCODE SCIPwriteNLP ( SCIP * scip,
const char * filename )

writes current NLP to a file

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
filenamefile name

Definition at line 727 of file scip_nlp.c.

References FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpWrite(), and TRUE.

Referenced by SCIP_DECL_DIALOGEXEC().

◆ SCIPgetNLPI()

SCIP_RETCODE SCIPgetNLPI ( SCIP * scip,
SCIP_NLPI ** nlpi,
SCIP_NLPIPROBLEM ** nlpiproblem )

gets the NLP interface and problem used by the SCIP NLP

Warning
With the NLPI and its problem, all methods defined in scip_nlpi.h and pub_nlpi.h can be used. It needs to be ensured that the full internal state of the NLPI does not change or is recovered completely after the end of the method that uses the NLPI. In particular, if the NLP or its solution is manipulated (e.g. by calling one of the SCIPaddNlpi...() or the SCIPsolveNlpi() method), one has to check in advance whether the NLP is currently solved. If this is the case, one has to make sure that the internal solution status is recovered completely again. Additionally one has to resolve the NLP with SCIPsolveNlpi() in order to reinstall the internal solution status.
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
nlpipointer to store the NLP solver interface
nlpiproblempointer to store the NLP solver interface problem

Definition at line 762 of file scip_nlp.c.

References assert(), FALSE, NULL, SCIP_CALL, SCIP_INVALIDCALL, SCIP_OKAY, SCIPcheckStage(), SCIPerrorMessage, SCIPnlpGetNLPI(), SCIPnlpGetNLPIProblem(), and TRUE.