benderscut_opt.c
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31/*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
53#define SCIP_DEFAULT_CALCMIR TRUE /** Should the mixed integer rounding procedure be used for the cut */
103/** verifying the activity of the cut when master variables are within epsilon of their upper or lower bounds
105 * When setting up the Benders' decomposition subproblem, master variables taking values that are within epsilon
106 * greater than their upper bound or less than their lower bound are set to their upper and lower bounds respectively.
107 * As such, there can be a difference between the subproblem dual solution objective and the optimality cut activity,
108 * when computed using the master problem solution directly. This check is to verify whether this difference is an
109 * actual error or due to the violation of the upper and lower bounds when setting up the Benders' decomposition
116 SCIP_VAR** vars, /**< pointer to array of variables in the generated cut with non-zero coefficient */
155/** when solving NLP subproblems, numerical issues are addressed by tightening the feasibility tolerance */
209 SCIP_VAR*** vars, /**< pointer to the array of variables in the generated cut with non-zero coefficient */
210 SCIP_Real** vals, /**< pointer to the array of coefficients of the variables in the generated cut */
246 SCIP_HASHMAP* var2idx /**< mapping from variable of the subproblem to the index in the dual arrays, can be NULL */
272 SCIP_VAR** vars, /**< pointer to array of variables in the generated cut with non-zero coefficient */
296 /* creating the aggregation row. There will be only a single row in this aggregation, since it is only used to
301 /* retrieving the indices for the variables in the optimality cut. All of the values must be negated, since the
316 SCIP_CALL( SCIPaggrRowAddCustomCons(masterprob, aggrrow, rowinds, rowvals, nvars, -lhs, 1.0, 1, FALSE) );
319 SCIP_CALL( SCIPcalcFlowCover(masterprob, sol, TRUE, 0.9999, FALSE, aggrrow, cutcoefs, cutrhs, cutinds, cutnnz,
324 SCIP_CALL( SCIPcalcMIR(masterprob, sol, TRUE, 0.9999, TRUE, FALSE, FALSE, NULL, NULL, 0.001, 0.999, 1.0, aggrrow,
337 redundant = SCIPcutsTightenCoefficients(masterprob, FALSE, cutcoefs, cutrhs, cutinds, cutnnz, &nchgcoefs);
356 SCIP_VAR*** vars, /**< pointer to array of variables in the generated cut with non-zero coefficient */
357 SCIP_Real** vals, /**< pointer to array of coefficients of the variables in the generated cut */
414 SCIPdebugMsg(masterprob, "Infinite bound when generating optimality cut. lhs = %g addval = %g.\n", (*lhs), addval);
501 SCIP_VAR*** vars, /**< pointer to array of variables in the generated cut with non-zero coefficient */
502 SCIP_Real** vals, /**< pointer to array of coefficients of the variables in the generated cut */
512 SCIP_HASHMAP* row2idx, /**< mapping between the row in the subproblem to the index in the dual array, can be NULL */
513 SCIP_HASHMAP* var2idx, /**< mapping from variable of the subproblem to the index in the dual arrays, can be NULL */
539 if( !(primalvals == NULL && consdualvals == NULL && varlbdualvals == NULL && varubdualvals == NULL && row2idx == NULL && var2idx == NULL)
540 && !(primalvals != NULL && consdualvals != NULL && varlbdualvals != NULL && varubdualvals != NULL && row2idx != NULL && var2idx != NULL) ) /*lint !e845*/
542 SCIPerrorMessage("The optimality cut must generated from either a SCIP instance or all of the dual solutions and indices must be supplied");
553 /* our optimality cut implementation assumes that SCIP did not modify the objective function and sense,
554 * that is, that the objective function value of the NLP corresponds to the value of the auxiliary variable
555 * if that wouldn't be the case, then the scaling and offset may have to be considered when adding the
600 *checkobj += SCIPvarGetUnchangedObj(fixedvars[i]) * getNlpVarSol(fixedvars[i], primalvals, var2idx);
609 SCIPdebugMsg(masterprob, "Infinite bound when generating optimality cut. lhs = %g dirderiv = %g.\n", *lhs, dirderiv);
619/** Adds the auxiliary variable to the generated cut. If this is the first optimality cut for the subproblem, then the
693 /* if the cuts are generated prior to the solving stage, then rows can not be generated. So constraints must be
702 (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "optimalitycut_%d_%" SCIP_LONGINT_FORMAT, probnumber,
709 SCIPdebugMsg(scip, "The subproblem %d is set to NULL. The <%s> Benders' decomposition cut can not be executed.\n",
727 SCIP_CALL( SCIPgenerateAndApplyBendersOptCut(scip, subproblem, benders, benderscut, sol, probnumber, cutname,
728 SCIPbendersGetSubproblemObjval(benders, probnumber), NULL, NULL, NULL, NULL, NULL, NULL, type, addcut,
731 /* if it was not possible to generate a cut, this could be due to numerical issues. So the solution to the LP is
732 * resolved and the generation of the cut is reattempted. For NLPs, we do not have such a polishing yet.
738 SCIPdebugMsg(scip, "Numerical trouble generating optimality cut for subproblem %d.\n", probnumber);
742 SCIPdebugMsg(scip, "Attempting to polish the LP solution to find an alternative dual extreme point.\n");
749 SCIP_CALL( SCIPgenerateAndApplyBendersOptCut(scip, subproblem, benders, benderscut, sol, probnumber, cutname,
750 SCIPbendersGetSubproblemObjval(benders, probnumber), NULL, NULL, NULL, NULL, NULL, NULL, type, addcut,
758 SCIPdebugMsg(scip, "Attempting to resolve the NLP with a tighter feasibility tolerance to find an "
767 SCIP_CALL( SCIPgenerateAndApplyBendersOptCut(scip, subproblem, benders, benderscut, sol, probnumber, cutname,
768 SCIPbendersGetSubproblemObjval(benders, probnumber), NULL, NULL, NULL, NULL, NULL, NULL, type, addcut,
804 SCIP_CALL( SCIPincludeBenderscutBasic(scip, benders, &benderscut, BENDERSCUT_NAME, BENDERSCUT_DESC,
816 "should cuts be generated and added to the cutpool instead of global constraints directly added to the problem.",
828/** Generates a classical Benders' optimality cut using the dual solutions from the subproblem or the input arrays. If
829 * the dual solutions are input as arrays, then a mapping between the array indices and the rows/variables is required.
830 * As a cut strengthening approach, when an optimality cut is being generated (i.e. not for feasibility cuts) a MIR
831 * procedure is performed on the row. This procedure attempts to find a stronger constraint, if this doesn't happen,
834 * This method can also be used to generate a feasibility cut, if a problem to minimise the infeasibilities has been solved
850 SCIP_HASHMAP* row2idx, /**< mapping between the row in the subproblem to the index in the dual array, can be NULL */
851 SCIP_HASHMAP* var2idx, /**< mapping from variable of the subproblem to the index in the dual arrays, can be NULL */
881 assert((primalvals == NULL && consdualvals == NULL && varlbdualvals == NULL && varubdualvals == NULL
883 || (primalvals != NULL && consdualvals != NULL && varlbdualvals != NULL && varubdualvals != NULL
889 calcmir = SCIPbenderscutGetData(benderscut)->calcmir && SCIPgetStage(masterprob) >= SCIP_STAGE_INITSOLVE && SCIPgetSubscipDepth(masterprob) == 0;
896 /* checking the optimality of the original problem with a comparison between the auxiliary variable and the
902 SCIP_CALL( SCIPcheckBendersSubproblemOptimality(masterprob, benders, sol, probnumber, &optimal) );
924 SCIP_CALL( computeStandardNLPOptimalityCut(masterprob, subproblem, benders, &vars, &vals, &lhs, &rhs, &nvars,
931 SCIP_CALL( computeStandardLPOptimalityCut(masterprob, subproblem, benders, &vars, &vals, &lhs, &rhs, &nvars,
935 /* if success is FALSE, then there was an error in generating the optimality cut. No cut will be added to the master
941 SCIPdebugMsg(masterprob, "Error in generating Benders' optimality cut for problem %d.\n", probnumber);
945 /* initially a row/constraint is created for the optimality cut using the master variables and coefficients
946 * computed in computeStandardLPOptimalityCut. At this stage, the auxiliary variable is not added since the
947 * activity of the row/constraint in its current form is used to determine the validity of the optimality cut.
951 SCIP_CALL( SCIPcreateEmptyRowConshdlr(masterprob, &row, consbenders, cutname, lhs, rhs, FALSE, FALSE, TRUE) );
956 SCIP_CALL( SCIPcreateConsBasicLinear(masterprob, &cons, cutname, nvars, vars, vals, lhs, rhs) );
961 /* computing the objective function from the cut activity to verify the accuracy of the constraint */
975 SCIPdebugMsg(masterprob, "The violation of the feasibility cut (%g) is too small. Skipping feasibility cut.\n", verifyobj);
978 /* it is possible that numerics will cause the generated cut to be invalid. This cut should not be added to the
979 * master problem, since its addition could cut off feasible solutions. The success flag is set of false, indicating
986 /* the difference in the checkobj and verifyobj could be due to the setup tolerances. This is checked, and if
994 SCIPdebugMsg(masterprob, "The objective function and cut activity are not equal (%g != %g).\n", checkobj,
998 /* we only need to abort if cut strengthen is not used. If cut strengthen has been used in this round and the
1007 printf("<%s> %g %g\n", SCIPvarGetName(vars[i]), vals[i], SCIPgetSolVal(masterprob, sol, vars[i]));
1017 /* adding the auxiliary variable to the optimality cut. The auxiliary variable is added to the vars and vals
1018 * arrays prior to the execution of the MIR procedure. This is necessary because the MIR procedure must be
1026 /* performing the MIR procedure. If the procedure is successful, then the vars and vals arrays are no longer
1027 * needed for creating the optimality cut. These are superseeded with the cutcoefs and cutinds arrays. In the
1028 * case that the MIR procedure is successful, the row/constraint that has been created previously is destroyed
1045 /* if the MIR cut was computed successfully, then the current row/constraint needs to be destroyed and
1093 /* adding the auxiliary variable coefficient to the row. This is only added if the MIR procedure is not
1094 * successful. If the MIR procedure was successful, then the auxiliary variable is already included in the
1117 /* adding the auxiliary variable coefficient to the row. This is only added if the MIR procedure is not
1118 * successful. If the MIR procedure was successful, then the auxiliary variable is already included in the
1139 SCIPdebugMsg(masterprob, "Error in generating Benders' %s cut for problem %d.\n", feasibilitycut ? "feasibility" : "optimality", probnumber);
1162/** adds the gradient of a nonlinear row in the current NLP solution of a subproblem to a linear row or constraint in the master problem
1174 SCIP_HASHMAP* var2idx, /**< mapping from variable of the subproblem to the index in the dual arrays, can be NULL */
1176 SCIP_VAR*** vars, /**< pointer to array of variables in the generated cut with non-zero coefficient */
1177 SCIP_Real** vals, /**< pointer to array of coefficients of the variables in the generated cut */
1229 /* TODO would be better to change primalvals to a SCIP_SOL and do this once for the whole NLP instead of repeating it for each expr */
1236 SCIP_CALL( SCIPsetSolVal(subproblem, primalsol, (SCIP_VAR*) SCIPhashmapEntryGetOrigin(entry), primalvals[SCIPhashmapEntryGetImageInt(entry)]) );
1247 assert(SCIPexprGetDerivative(expr) != SCIP_INVALID); /* TODO this should be a proper check&abort */ /*lint !e777*/
static SCIP_RETCODE checkSetupTolerances(SCIP *masterprob, SCIP_SOL *sol, SCIP_VAR **vars, SCIP_Real *vals, SCIP_Real lhs, SCIP_Real checkobj, int nvars, SCIP_Bool *valid)
Definition: benderscut_opt.c:113
static SCIP_RETCODE addVariableToArray(SCIP *masterprob, SCIP_VAR ***vars, SCIP_Real **vals, SCIP_VAR *addvar, SCIP_Real addval, int *nvars, int *varssize)
Definition: benderscut_opt.c:207
static SCIP_RETCODE computeStandardLPOptimalityCut(SCIP *masterprob, SCIP *subproblem, SCIP_BENDERS *benders, SCIP_VAR ***vars, SCIP_Real **vals, SCIP_Real *lhs, SCIP_Real *rhs, int *nvars, int *varssize, SCIP_Real *checkobj, SCIP_Bool *success)
Definition: benderscut_opt.c:352
static SCIP_RETCODE addAuxiliaryVariableToCut(SCIP *masterprob, SCIP_BENDERS *benders, SCIP_VAR **vars, SCIP_Real *vals, int *nvars, int probnumber)
Definition: benderscut_opt.c:623
static SCIP_RETCODE computeStandardNLPOptimalityCut(SCIP *masterprob, SCIP *subproblem, SCIP_BENDERS *benders, SCIP_VAR ***vars, SCIP_Real **vals, SCIP_Real *lhs, SCIP_Real *rhs, int *nvars, int *varssize, SCIP_Real objective, SCIP_Real *primalvals, SCIP_Real *consdualvals, SCIP_Real *varlbdualvals, SCIP_Real *varubdualvals, SCIP_HASHMAP *row2idx, SCIP_HASHMAP *var2idx, SCIP_Real *checkobj, SCIP_Bool *success)
Definition: benderscut_opt.c:497
static SCIP_DECL_BENDERSCUTEXEC(benderscutExecOpt)
Definition: benderscut_opt.c:676
static SCIP_Real getNlpVarSol(SCIP_VAR *var, SCIP_Real *primalvals, SCIP_HASHMAP *var2idx)
Definition: benderscut_opt.c:243
static SCIP_RETCODE computeMIRForOptimalityCut(SCIP *masterprob, SCIP_SOL *sol, SCIP_VAR **vars, SCIP_Real *vals, SCIP_Real lhs, SCIP_Real rhs, int nvars, SCIP_Real *cutcoefs, int *cutinds, SCIP_Real *cutrhs, int *cutnnz, SCIP_Bool *success)
Definition: benderscut_opt.c:269
static SCIP_RETCODE polishSolution(SCIP *subproblem, SCIP_Bool *success)
Definition: benderscut_opt.c:73
static SCIP_RETCODE resolveNLPWithTighterFeastol(SCIP *subproblem, SCIP_BENDERS *benders, SCIP_Real multiplier, SCIP_Bool *success)
Definition: benderscut_opt.c:157
static SCIP_DECL_BENDERSCUTFREE(benderscutFreeOpt)
Definition: benderscut_opt.c:655
Generates a standard Benders' decomposition optimality cut.
Constraint handler for linear constraints in their most general form, .
SCIP_RETCODE SCIPgenerateAndApplyBendersOptCut(SCIP *masterprob, SCIP *subproblem, SCIP_BENDERS *benders, SCIP_BENDERSCUT *benderscut, SCIP_SOL *sol, int probnumber, char *cutname, SCIP_Real objective, SCIP_Real *primalvals, SCIP_Real *consdualvals, SCIP_Real *varlbdualvals, SCIP_Real *varubdualvals, SCIP_HASHMAP *row2idx, SCIP_HASHMAP *var2idx, SCIP_BENDERSENFOTYPE type, SCIP_Bool addcut, SCIP_Bool feasibilitycut, SCIP_RESULT *result)
Definition: benderscut_opt.c:837
SCIP_RETCODE SCIPaddNlRowGradientBenderscutOpt(SCIP *masterprob, SCIP *subproblem, SCIP_BENDERS *benders, SCIP_NLROW *nlrow, SCIP_Real mult, SCIP_Real *primalvals, SCIP_HASHMAP *var2idx, SCIP_Real *dirderiv, SCIP_VAR ***vars, SCIP_Real **vals, int *nvars, int *varssize)
Definition: benderscut_opt.c:1167
SCIP_RETCODE SCIPincludeBenderscutOpt(SCIP *scip, SCIP_BENDERS *benders)
Definition: benderscut_opt.c:787
SCIP_RETCODE SCIPaddCoefLinear(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real val)
Definition: cons_linear.c:18207
SCIP_Real SCIPgetLhsLinear(SCIP *scip, SCIP_CONS *cons)
Definition: cons_linear.c:18455
SCIP_RETCODE SCIPcreateConsBasicLinear(SCIP *scip, SCIP_CONS **cons, const char *name, int nvars, SCIP_VAR **vars, SCIP_Real *vals, SCIP_Real lhs, SCIP_Real rhs)
Definition: cons_linear.c:18055
SCIP_Real SCIPgetActivityLinear(SCIP *scip, SCIP_CONS *cons, SCIP_SOL *sol)
Definition: cons_linear.c:18618
int SCIPhashmapGetImageInt(SCIP_HASHMAP *hashmap, void *origin)
Definition: misc.c:3281
int SCIPhashmapEntryGetImageInt(SCIP_HASHMAPENTRY *entry)
Definition: misc.c:3580
SCIP_HASHMAPENTRY * SCIPhashmapGetEntry(SCIP_HASHMAP *hashmap, int entryidx)
Definition: misc.c:3549
void * SCIPhashmapEntryGetOrigin(SCIP_HASHMAPENTRY *entry)
Definition: misc.c:3560
SCIP_Bool SCIPhashmapExists(SCIP_HASHMAP *hashmap, void *origin)
Definition: misc.c:3423
SCIP_RETCODE SCIPsetIntParam(SCIP *scip, const char *name, int value)
Definition: scip_param.c:487
SCIP_RETCODE SCIPaddBoolParam(SCIP *scip, const char *name, const char *desc, SCIP_Bool *valueptr, SCIP_Bool isadvanced, SCIP_Bool defaultvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:57
SCIP_RETCODE SCIPgetIntParam(SCIP *scip, const char *name, int *value)
Definition: scip_param.c:269
SCIP_VAR * SCIPbendersGetAuxiliaryVar(SCIP_BENDERS *benders, int probnumber)
Definition: benders.c:6160
SCIP_NLPPARAM SCIPbendersGetNLPParam(SCIP_BENDERS *benders)
Definition: benders.c:4755
SCIP_RETCODE SCIPgetBendersMasterVar(SCIP *scip, SCIP_BENDERS *benders, SCIP_VAR *var, SCIP_VAR **mappedvar)
Definition: scip_benders.c:660
int SCIPbendersGetNSubproblems(SCIP_BENDERS *benders)
Definition: benders.c:5968
SCIP * SCIPbendersSubproblem(SCIP_BENDERS *benders, int probnumber)
Definition: benders.c:5978
SCIP_RETCODE SCIPcheckBendersSubproblemOptimality(SCIP *scip, SCIP_BENDERS *benders, SCIP_SOL *sol, int probnumber, SCIP_Bool *optimal)
Definition: scip_benders.c:892
SCIP_Real SCIPbendersGetSubproblemObjval(SCIP_BENDERS *benders, int probnumber)
Definition: benders.c:6199
SCIP_Bool SCIPbendersInStrengthenRound(SCIP_BENDERS *benders)
Definition: benders.c:6447
SCIP_RETCODE SCIPincludeBenderscutBasic(SCIP *scip, SCIP_BENDERS *benders, SCIP_BENDERSCUT **benderscutptr, const char *name, const char *desc, int priority, SCIP_Bool islpcut, SCIP_DECL_BENDERSCUTEXEC((*benderscutexec)), SCIP_BENDERSCUTDATA *benderscutdata)
Definition: scip_benders.c:1138
SCIP_RETCODE SCIPsetBenderscutFree(SCIP *scip, SCIP_BENDERSCUT *benderscut, SCIP_DECL_BENDERSCUTFREE((*benderscutfree)))
Definition: scip_benders.c:1204
void SCIPbenderscutSetData(SCIP_BENDERSCUT *benderscut, SCIP_BENDERSCUTDATA *benderscutdata)
Definition: benderscut.c:413
const char * SCIPbenderscutGetName(SCIP_BENDERSCUT *benderscut)
Definition: benderscut.c:492
SCIP_BENDERSCUTDATA * SCIPbenderscutGetData(SCIP_BENDERSCUT *benderscut)
Definition: benderscut.c:403
SCIP_RETCODE SCIPstoreBendersCut(SCIP *scip, SCIP_BENDERS *benders, SCIP_VAR **vars, SCIP_Real *vals, SCIP_Real lhs, SCIP_Real rhs, int nvars)
Definition: scip_benders.c:1366
SCIP_Longint SCIPbenderscutGetNFound(SCIP_BENDERSCUT *benderscut)
Definition: benderscut.c:543
SCIP_CONSHDLR * SCIPfindConshdlr(SCIP *scip, const char *name)
Definition: scip_cons.c:941
SCIP_RETCODE SCIPsetConsDynamic(SCIP *scip, SCIP_CONS *cons, SCIP_Bool dynamic)
Definition: scip_cons.c:1450
SCIP_RETCODE SCIPsetConsRemovable(SCIP *scip, SCIP_CONS *cons, SCIP_Bool removable)
Definition: scip_cons.c:1475
SCIP_RETCODE SCIPreleaseCons(SCIP *scip, SCIP_CONS **cons)
Definition: scip_cons.c:1174
SCIP_Bool SCIPcutsTightenCoefficients(SCIP *scip, SCIP_Bool cutislocal, SCIP_Real *cutcoefs, SCIP_Real *cutrhs, int *cutinds, int *cutnnz, int *nchgcoefs)
Definition: cuts.c:1527
SCIP_RETCODE SCIPaggrRowCreate(SCIP *scip, SCIP_AGGRROW **aggrrow)
Definition: cuts.c:1723
SCIP_Bool SCIPisEfficacious(SCIP *scip, SCIP_Real efficacy)
Definition: scip_cut.c:135
SCIP_RETCODE SCIPaggrRowAddCustomCons(SCIP *scip, SCIP_AGGRROW *aggrrow, int *inds, SCIP_Real *vals, int len, SCIP_Real rhs, SCIP_Real weight, int rank, SCIP_Bool local)
Definition: cuts.c:2080
SCIP_RETCODE SCIPaddRow(SCIP *scip, SCIP_ROW *row, SCIP_Bool forcecut, SCIP_Bool *infeasible)
Definition: scip_cut.c:250
SCIP_RETCODE SCIPcalcFlowCover(SCIP *scip, SCIP_SOL *sol, SCIP_Bool postprocess, SCIP_Real boundswitch, SCIP_Bool allowlocal, SCIP_AGGRROW *aggrrow, SCIP_Real *cutcoefs, SCIP_Real *cutrhs, int *cutinds, int *cutnnz, SCIP_Real *cutefficacy, int *cutrank, SCIP_Bool *cutislocal, SCIP_Bool *success)
Definition: cuts.c:7417
SCIP_RETCODE SCIPcalcMIR(SCIP *scip, SCIP_SOL *sol, SCIP_Bool postprocess, SCIP_Real boundswitch, SCIP_Bool usevbds, SCIP_Bool allowlocal, SCIP_Bool fixintegralrhs, int *boundsfortrans, SCIP_BOUNDTYPE *boundtypesfortrans, SCIP_Real minfrac, SCIP_Real maxfrac, SCIP_Real scale, SCIP_AGGRROW *aggrrow, SCIP_Real *cutcoefs, SCIP_Real *cutrhs, int *cutinds, int *cutnnz, SCIP_Real *cutefficacy, int *cutrank, SCIP_Bool *cutislocal, SCIP_Bool *success)
Definition: cuts.c:3873
SCIP_RETCODE SCIPevalExprGradient(SCIP *scip, SCIP_EXPR *expr, SCIP_SOL *sol, SCIP_Longint soltag)
Definition: scip_expr.c:1667
SCIP_RETCODE SCIPcreateExpriter(SCIP *scip, SCIP_EXPRITER **iterator)
Definition: scip_expr.c:2337
SCIP_EXPR * SCIPexpriterGetNext(SCIP_EXPRITER *iterator)
Definition: expriter.c:858
SCIP_RETCODE SCIPexpriterInit(SCIP_EXPRITER *iterator, SCIP_EXPR *expr, SCIP_EXPRITER_TYPE type, SCIP_Bool allowrevisit)
Definition: expriter.c:501
#define SCIPallocClearBufferArray(scip, ptr, num)
Definition: scip_mem.h:126
SCIP_RETCODE SCIPsolveNLPParam(SCIP *scip, SCIP_NLPPARAM param)
Definition: scip_nlp.c:545
SCIP_RETCODE SCIPsolveProbingLP(SCIP *scip, int itlim, SCIP_Bool *lperror, SCIP_Bool *cutoff)
Definition: scip_probing.c:820
SCIP_RETCODE SCIPcreateEmptyRowConshdlr(SCIP *scip, SCIP_ROW **row, SCIP_CONSHDLR *conshdlr, const char *name, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool removable)
Definition: scip_lp.c:1391
SCIP_RETCODE SCIPaddVarToRow(SCIP *scip, SCIP_ROW *row, SCIP_VAR *var, SCIP_Real val)
Definition: scip_lp.c:1701
SCIP_RETCODE SCIPaddVarsToRow(SCIP *scip, SCIP_ROW *row, int nvars, SCIP_VAR **vars, SCIP_Real *vals)
Definition: scip_lp.c:1727
SCIP_Real SCIPgetRowSolActivity(SCIP *scip, SCIP_ROW *row, SCIP_SOL *sol)
Definition: scip_lp.c:2144
SCIP_RETCODE SCIPcreateSol(SCIP *scip, SCIP_SOL **sol, SCIP_HEUR *heur)
Definition: scip_sol.c:184
SCIP_RETCODE SCIPprintSol(SCIP *scip, SCIP_SOL *sol, FILE *file, SCIP_Bool printzeros)
Definition: scip_sol.c:1631
SCIP_RETCODE SCIPcreateNLPSol(SCIP *scip, SCIP_SOL **sol, SCIP_HEUR *heur)
Definition: scip_sol.c:254
SCIP_RETCODE SCIPsetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var, SCIP_Real val)
Definition: scip_sol.c:1077
SCIP_Real SCIPgetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var)
Definition: scip_sol.c:1217
SCIP_Bool SCIPisFeasEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:780
SCIP_Bool SCIPisGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:484
SCIP_Bool SCIPisLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:458
Definition: objbenders.h:44
public methods for Benders' decomposition
public methods for Benders' decomposition cuts
public functions to work with algebraic expressions
public methods for LP management
public methods for message output
public data structures and miscellaneous methods
internal miscellaneous methods for linear constraints
public methods for NLP management
public methods for problem variables
SCIP callable library.
Definition: struct_cuts.h:41
Definition: struct_benders.h:58
Definition: struct_benderscut.h:47
Definition: struct_cons.h:47
Definition: struct_cons.h:127
Definition: struct_expr.h:204
Definition: struct_expr.h:106
Definition: struct_misc.h:131
Definition: struct_misc.h:138
Definition: struct_nlp.h:65
Definition: type_nlpi.h:67
Definition: struct_lp.h:202
Definition: struct_sol.h:74
Definition: struct_var.h:208
Definition: struct_scip.h:70