cons_xor.c
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18 * @brief Constraint handler for "xor" constraints, \f$rhs = x_1 \oplus x_2 \oplus \dots \oplus x_n\f$
30 * where \f$x_i\f$ is a binary variable for all \f$i\f$ and \f$rhs\f$ is bool. The variables \f$x\f$'s are called
31 * operators. This constraint is satisfied if \f$rhs\f$ is TRUE and an odd number of the operators are TRUE or if the
32 * \f$rhs\f$ is FALSE and a even number of operators are TRUE. Hence, if the sum of \f$rhs\f$ and operators is even.
36 * - static functions for certain operations that respect deleteintvar flag properly (e.g., deletion of constraints)
38 * (right now, we do not remove fixed variables from the constraint, because we must ensure that the intvar gets
40 * @todo check if preprocessConstraintPairs can also be executed for non-artificial intvars (after the previous changes)
43 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
81 #define CONSHDLR_ENFOPRIORITY -850200 /**< priority of the constraint handler for constraint enforcing */
82 #define CONSHDLR_CHECKPRIORITY -850200 /**< priority of the constraint handler for checking feasibility */
83 #define CONSHDLR_SEPAFREQ 0 /**< frequency for separating cuts; zero means to separate only in the root node */
84 #define CONSHDLR_PROPFREQ 1 /**< frequency for propagating domains; zero means only preprocessing propagation */
85 #define CONSHDLR_EAGERFREQ 100 /**< frequency for using all instead of only the useful constraints in separation,
87 #define CONSHDLR_MAXPREROUNDS -1 /**< maximal number of presolving rounds the constraint handler participates in (-1: no limit) */
88 #define CONSHDLR_DELAYSEPA FALSE /**< should separation method be delayed, if other separators found cuts? */
89 #define CONSHDLR_DELAYPROP FALSE /**< should propagation method be delayed, if other propagators found reductions? */
90 #define CONSHDLR_NEEDSCONS TRUE /**< should the constraint handler be skipped, if no constraints are available? */
98 #define LINCONSUPGD_PRIORITY +600000 /**< priority of the constraint handler for upgrading of linear constraints */
100 #define DEFAULT_PRESOLPAIRWISE TRUE /**< should pairwise constraint comparison be performed in presolving? */
101 #define DEFAULT_ADDEXTENDEDFORM FALSE /**< should the extended formulation be added in presolving? */
102 #define DEFAULT_ADDFLOWEXTENDED FALSE /**< should the extended flow formulation be added (nonsymmetric formulation otherwise)? */
106 #define DEFAULT_PRESOLUSEHASHING TRUE /**< should hash table be used for detecting redundant constraints in advance */
108 #define MINGAINPERNMINCOMPARISONS 1e-06 /**< minimal gain per minimal pairwise presolving comparisons to repeat pairwise comparison round */
109 #define MAXXORCONSSSYSTEM 1000 /**< maximal number of active constraints for which checking the system over GF2 is performed */
110 #define MAXXORVARSSYSTEM 1000 /**< maximal number of variables in xor constraints for which checking the system over GF2 is performed */
127 SCIP_VAR** extvars; /**< variables in extended (flow|asymmetric) formulation (order for flow formulation: nn, ns, sn, ss) */
148 SCIP_Bool presolpairwise; /**< should pairwise constraint comparison be performed in presolving? */
149 SCIP_Bool presolusehashing; /**< should hash table be used for detecting redundant constraints in advance? */
151 SCIP_Bool addflowextended; /**< should the extended flow formulation be added (nonsymmetric formulation otherwise)? */
162 {
168 };
276 SCIP_CALL( SCIPdropVarEvent(scip, consdata->vars[consdata->watchedvar1], SCIP_EVENTTYPE_BOUNDCHANGED, eventhdlr,
282 SCIP_CALL( SCIPdropVarEvent(scip, consdata->vars[consdata->watchedvar2], SCIP_EVENTTYPE_BOUNDCHANGED, eventhdlr,
289 SCIP_CALL( SCIPcatchVarEvent(scip, consdata->vars[watchedvar1], SCIP_EVENTTYPE_BOUNDCHANGED, eventhdlr,
294 SCIP_CALL( SCIPcatchVarEvent(scip, consdata->vars[watchedvar2], SCIP_EVENTTYPE_BOUNDCHANGED, eventhdlr,
369 SCIP_CALL( SCIPgetTransformedVars(scip, (*consdata)->nvars, (*consdata)->vars, (*consdata)->vars) );
389 SCIP_CALL( SCIPcatchVarEvent(scip, (*consdata)->vars[v], SCIP_EVENTTYPE_VARFIXED, conshdlrdata->eventhdlr,
474 assert( SCIPisEQ(scip, SCIPvarGetLbGlobal((*consdata)->intvar), SCIPvarGetLbGlobal((*consdata)->intvar)) );
476 /* We do not delete the integral variable, but leave the handling to SCIP, because it might happen that the
611 * we need to catch this event also during exiting presolving because we call applyFixings to clean up the constraint
612 * and this can lead to an insertion of a replacement of variables for which we will try to drop the VARFIXED event.
614 if( SCIPgetStage(scip) == SCIP_STAGE_PRESOLVING || SCIPgetStage(scip) == SCIP_STAGE_INITPRESOLVE
632 SCIPerrorMessage("cannot add coefficients to xor constraint after LP relaxation was created\n");
661 if( SCIPgetStage(scip) == SCIP_STAGE_PRESOLVING || SCIPgetStage(scip) == SCIP_STAGE_INITPRESOLVE
743 /* since negated variables exist, we need to loop over all variables to find the old variable and cannot use
777 assert(v == consdata->nvars-1 || SCIPvarCompareActiveAndNegated(consdata->vars[v], consdata->vars[v+1]) <= 0);
792 /** returns TRUE iff both keys are equal; two constraints are equal if they have the same variables */
795 {
852 assert(SCIPvarIsActive(consdata->vars[0]) || SCIPvarGetStatus(consdata->vars[0]) == SCIP_VARSTATUS_NEGATED || SCIPvarGetStatus(consdata->vars[0]) == SCIP_VARSTATUS_FIXED);
853 assert(SCIPvarIsActive(consdata->vars[consdata->nvars / 2]) || SCIPvarGetStatus(consdata->vars[consdata->nvars / 2]) == SCIP_VARSTATUS_NEGATED || SCIPvarGetStatus(consdata->vars[consdata->nvars / 2]) == SCIP_VARSTATUS_FIXED);
854 assert(SCIPvarIsActive(consdata->vars[consdata->nvars - 1]) || SCIPvarGetStatus(consdata->vars[consdata->nvars - 1]) == SCIP_VARSTATUS_NEGATED || SCIPvarGetStatus(consdata->vars[consdata->nvars - 1]) == SCIP_VARSTATUS_FIXED);
859 /* note that for all indices it does not hold that they are sorted, because variables are sorted with
951 /* delete pairs of equal or negated variables; scan from back to front because deletion doesn't affect the
976 * assuming we have an integer variable y it needs to be replaced by z with y = x1 + z and z in [lb_y, ub_y]
1021 SCIPconsGetName(cons), SCIPvarGetName(consdata->vars[v]), SCIPvarGetName(consdata->vars[v+1])); /*lint !e679*/
1031 * assuming we have an integer variable y it needs to be replaced by z with y = 1 + z and z in [lb_y, ub_y - 1]
1054 SCIP_CALL( SCIPaggregateVars(scip, consdata->intvar, newvar, 1.0, -1.0, 1.0, &infeasible, &redundant, &aggregated) );
1072 /* the new variable should only by inactive if it was fixed due to the aggregation, so also the old variable
1080 assert(SCIPisEQ(scip, SCIPvarGetLbGlobal(consdata->intvar), SCIPvarGetUbGlobal(consdata->intvar)));
1116 assert(SCIPvarGetProbvar(consdata->vars[v]) != SCIPvarGetProbvar(consdata->vars[v+1])); /*lint !e679*/
1128 * The extended flow formulation is built as follows: Let \f$x_1, \dots, x_k\f$ be the variables contained in the given
1129 * XOR constraint. We construct a two layered flow network. The upper layer is called the north layer and the lower is
1130 * called the south layer. For each \f$x_i,\; i = 2, \ldots, k-1\f$, we add arcs that stay in the north and south layer
1131 * (denoted by 'nn' and 'ss', respectively), as well as arcs that change the layers (denoted by 'ns' and 'sn'). For
1132 * \f$x_1\f$, we only add two arcs from the source to the two layers. The source is located on the north layer. For
1133 * \f$x_k\f$, we add two arcs connecting the two layers to the sink. Depending on the rhs of the constraint the sink is
1134 * located on the north or south layer. A change in the layers corresponds to a parity change, i.e., the corresponding
1171 /* xor constraints with at most 3 variables are handled directly through rows for the convex hull */
1175 SCIPdebugMsg(scip, "Add extended formulation for xor constraint <%s> ...\n", SCIPconsGetName(cons));
1203 SCIP_CALL( SCIPcreateVar(scip, &varnn, name, 0.0, 1.0, 0.0, SCIP_VARTYPE_IMPLINT, SCIPconsIsInitial(cons), SCIPconsIsRemovable(cons), NULL, NULL, NULL, NULL, NULL) );
1207 SCIP_CALL( SCIPcreateVar(scip, &varns, name, 0.0, 1.0, 0.0, SCIP_VARTYPE_IMPLINT, SCIPconsIsInitial(cons), SCIPconsIsRemovable(cons), NULL, NULL, NULL, NULL, NULL) );
1215 SCIP_CALL( SCIPaggregateVars(scip, varns, consdata->vars[0], 1.0, -1.0, 0.0, &infeasible, &redundant, &aggregated) );
1229 SCIP_CALL( SCIPcreateVar(scip, &varns, name, 0.0, 1.0, 0.0, SCIP_VARTYPE_IMPLINT, SCIPconsIsInitial(cons), SCIPconsIsRemovable(cons), NULL, NULL, NULL, NULL, NULL) );
1233 SCIP_CALL( SCIPcreateVar(scip, &varss, name, 0.0, 1.0, 0.0, SCIP_VARTYPE_IMPLINT, SCIPconsIsInitial(cons), SCIPconsIsRemovable(cons), NULL, NULL, NULL, NULL, NULL) );
1241 SCIP_CALL( SCIPaggregateVars(scip, varns, consdata->vars[i], 1.0, -1.0, 0.0, &infeasible, &redundant, &aggregated) );
1251 SCIP_CALL( SCIPcreateVar(scip, &varnn, name, 0.0, 1.0, 0.0, SCIP_VARTYPE_IMPLINT, SCIPconsIsInitial(cons), SCIPconsIsRemovable(cons), NULL, NULL, NULL, NULL, NULL) );
1255 SCIP_CALL( SCIPcreateVar(scip, &varsn, name, 0.0, 1.0, 0.0, SCIP_VARTYPE_IMPLINT, SCIPconsIsInitial(cons), SCIPconsIsRemovable(cons), NULL, NULL, NULL, NULL, NULL) );
1263 SCIP_CALL( SCIPaggregateVars(scip, varsn, consdata->vars[i], 1.0, -1.0, 0.0, &infeasible, &redundant, &aggregated) );
1274 SCIP_CALL( SCIPcreateVar(scip, &varnn, name, 0.0, 1.0, 0.0, SCIP_VARTYPE_IMPLINT, SCIPconsIsInitial(cons), SCIPconsIsRemovable(cons), NULL, NULL, NULL, NULL, NULL) );
1278 SCIP_CALL( SCIPcreateVar(scip, &varns, name, 0.0, 1.0, 0.0, SCIP_VARTYPE_IMPLINT, SCIPconsIsInitial(cons), SCIPconsIsRemovable(cons), NULL, NULL, NULL, NULL, NULL) );
1282 SCIP_CALL( SCIPcreateVar(scip, &varsn, name, 0.0, 1.0, 0.0, SCIP_VARTYPE_IMPLINT, SCIPconsIsInitial(cons), SCIPconsIsRemovable(cons), NULL, NULL, NULL, NULL, NULL) );
1286 SCIP_CALL( SCIPcreateVar(scip, &varss, name, 0.0, 1.0, 0.0, SCIP_VARTYPE_IMPLINT, SCIPconsIsInitial(cons), SCIPconsIsRemovable(cons), NULL, NULL, NULL, NULL, NULL) );
1312 /* not initial, separate, do not enforce, do not check, propagate, not local, not modifiable, dynamic, removable, not sticking */
1350 /* not initial, separate, do not enforce, do not check, propagate, not local, not modifiable, dynamic, removable, not sticking */
1393 /* not initial, separate, do not enforce, do not check, propagate, not local, not modifiable, dynamic, removable, not sticking */
1428 * The extended asymmetric formulation is constructed as follows: Let \f$x_1, \dots, x_k\f$ be the variables contained
1429 * in the given XOR constraint. We introduce variables \f$p_1, \ldots, p_k\f$ with the following constraints: \f$p_1 =
1443 * In Harvey Greenberg, editor, Tutorials on emerging methodologies and applications in Operations Research,@n
1477 /* xor constraints with at most 3 variables are handled directly through rows for the convex hull */
1481 SCIPdebugMsg(scip, "Add extended formulation for xor constraint <%s> ...\n", SCIPconsGetName(cons));
1518 SCIP_CALL( SCIPcreateVar(scip, &artvar, name, lb, ub, 0.0, SCIP_VARTYPE_IMPLINT, SCIPconsIsInitial(cons), SCIPconsIsRemovable(cons), NULL, NULL, NULL, NULL, NULL) );
1526 SCIP_CALL( SCIPaggregateVars(scip, artvar, consdata->vars[0], 1.0, -1.0, 0.0, &infeasible, &redundant, &aggregated) );
1545 /* not initial, separate, do not enforce, do not check, propagate, not local, not modifiable, dynamic, removable, not sticking */
1562 /* not initial, separate, do not enforce, do not check, propagate, not local, not modifiable, dynamic, removable, not sticking */
1579 /* not initial, separate, do not enforce, do not check, propagate, not local, not modifiable, dynamic, removable, not sticking */
1596 /* not initial, separate, do not enforce, do not check, propagate, not local, not modifiable, dynamic, removable, not sticking */
1682 SCIP_CALL( SCIPcreateEmptyRowCons(scip, &consdata->rows[0], cons, SCIPconsGetName(cons), rhsval, rhsval,
1685 SCIP_CALL( SCIPaddVarsToRowSameCoef(scip, consdata->rows[0], consdata->nvars, consdata->vars, 1.0) );
1698 SCIP_CALL( SCIPcreateEmptyRowCons(scip, &consdata->rows[r], cons, rowname, -SCIPinfinity(scip), 0.0,
1702 SCIP_CALL( SCIPaddVarToRow(scip, consdata->rows[r], consdata->vars[v], v == r ? +1.0 : -1.0) );
1708 SCIP_CALL( SCIPcreateEmptyRowCons(scip, &consdata->rows[3], cons, rowname, -SCIPinfinity(scip), 2.0,
1710 SCIP_CALL( SCIPaddVarsToRowSameCoef(scip, consdata->rows[3], consdata->nvars, consdata->vars, 1.0) );
1715 SCIP_CALL( SCIPcreateEmptyRowCons(scip, &consdata->rows[4], cons, SCIPconsGetName(cons), 0.0, 0.0,
1718 SCIP_CALL( SCIPaddVarsToRowSameCoef(scip, consdata->rows[4], consdata->nvars, consdata->vars, 1.0) );
1732 SCIP_CALL( SCIPcreateEmptyRowCons(scip, &consdata->rows[r], cons, rowname, -SCIPinfinity(scip), 1.0,
1736 SCIP_CALL( SCIPaddVarToRow(scip, consdata->rows[r], consdata->vars[v], v == r ? -1.0 : +1.0) );
1742 SCIP_CALL( SCIPcreateEmptyRowCons(scip, &consdata->rows[3], cons, rowname, -SCIPinfinity(scip), -1.0,
1744 SCIP_CALL( SCIPaddVarsToRowSameCoef(scip, consdata->rows[3], consdata->nvars, consdata->vars, -1.0) );
1749 SCIP_CALL( SCIPcreateEmptyRowCons(scip, &consdata->rows[4], cons, SCIPconsGetName(cons), 1.0, 1.0,
1752 SCIP_CALL( SCIPaddVarsToRowSameCoef(scip, consdata->rows[4], consdata->nvars, consdata->vars, 1.0) );
1813 /** checks xor constraint for feasibility of given solution: returns TRUE iff constraint is feasible */
1819 SCIP_Bool checklprows, /**< Do constraints represented by rows in the current LP have to be checked? */
1840 /* increase age of constraint; age is reset to zero, if a violation was found only in case we are in
1896 * with \f$b \in \{0,1\}\f$ and a solution \f$x^*\f$ to be cut off. Small XOR constraints are handled by adding the
1901 * "Adaptive Cut Generation Algorithm for Improved Linear Programming Decoding of Binary Linear Codes"@n
1908 * with \f$|S| \equiv (b+1) \mbox{ mod } 2\f$ as follows. That these inequalities are valid can be seen as follows: Let
1909 * \f$x\f$ be a feasible solution and suppose that the inequality is violated for some \f$S\f$. Then \f$x_j = 1\f$ for
1916 * Let \f$L= \{j \;:\; x^*_j > \frac{1}{2}\}\f$. Suppose that \f$|L|\f$ has @em not the same parity as \f$b\f$ rhs. Then
1926 * Otherwise let \f$k = \mbox{argmin}\{x^*_j \;:\; j \in L\}\f$ and check the inequality for \f$L \setminus \{k\}\f$
2027 SCIP_CALL( SCIPcreateEmptyRowCons(scip, &row, cons, name, -SCIPinfinity(scip), (SCIP_Real) (cnt - 1), FALSE, FALSE, TRUE) );
2052 /* If the parity is equal: check removing the element with smallest value from the set and adding the
2053 * element with largest value to the set. If we remove the element with smallest value, we have to subtract (1
2059 SCIPdebugMsg(scip, "found violated parity cut (efficiacy: %f, minval: %f)\n", 1.0 - (sum - 1.0 + 2.0 * minval), minval);
2063 SCIP_CALL( SCIPcreateEmptyRowCons(scip, &row, cons, name, -SCIPinfinity(scip), (SCIP_Real) (cnt - 2), FALSE, FALSE, TRUE) );
2090 /* If we add the element with largest value, we have to add (1 - maxval) and subtract maxval to get the correct sum. */
2095 SCIPdebugMsg(scip, "found violated parity cut (efficiacy: %f, maxval: %f)\n", 1.0 - (sum + 1.0 - 2.0 * maxval), maxval);
2099 SCIP_CALL( SCIPcreateEmptyRowCons(scip, &row, cons, name, -SCIPinfinity(scip), (SCIP_Real) cnt, FALSE, FALSE, TRUE) );
2135 /** Transform linear system \f$A x = b\f$ into row echolon form via the Gauss algorithm with row pivoting over GF2
2138 * Here, \f$A \in R^{m \times n},\; b \in R^m\f$. On exit, the vector @p p contains a permutation of the row indices
2139 * used for pivoting and the function returns the rank @p r of @p A. For each row \f$i = 1, \ldots, r\f$, the entry @p
2181 /* find pivot row (i.e., first nonzero entry), if all entries in current row are 0 we search the next column */
2198 /* if not pivot entry was found (checked all columns), the rank of A is equal to the current index i; in this case
2241 /* at this point we have treated all rows in which a step can occur; the rank is the minimum of the number of rows or
2250 * Compute solution of \f$A x = b\f$, which is already in row echolon form (@see computeRowEcholonGF2()) */
2301 /** solve equation system over GF 2 by Gauss algorithm and create solution out of it or return cutoff
2303 * Collect all information in xor constraints into a linear system over GF2. Then solve the system by computing a row
2304 * echolon form. If the system is infeasible, the current node is infeasible. Otherwise, we can compute a solution for
2307 * We sort the columns with respect to the product of the objective coefficients and 1 minus the current LP solution
2308 * value. The idea is that columns that are likely to provide the steps in the row echolon form should appear towards
2309 * the front of the matrix. The smaller the product, the more it makes sense to set the variable to 1 (because the
2312 * Note that this function is called from propagation where usually no solution is available. However, the solution is
2313 * only used for sorting the columns. Thus, the procedure stays correct even with nonsense solutions.
2321 SCIP_RESULT* result /**< result of propagation (possibly cutoff, no change if primal solution has been tried) */
2351 SCIPdebugMsg(scip, "Checking feasibility via the linear equation system over GF2 using Gauss.\n");
2409 /* The following can save time, if there are constraints with all variables fixed that are infeasible; this
2413 /* all variables are fixed - check whether constraint is feasible (could be that the constraint is not propagated) */
2425 SCIPdebugMsg(scip, "constraint <%s> with all variables fixed is violated.\n", SCIPconsGetName(conss[i]));
2435 if ( nconssactive > MAXXORCONSSSYSTEM || nvarsmat > MAXXORVARSSYSTEM || *result == SCIP_CUTOFF )
2437 SCIPdebugMsg(scip, "Skip checking the xor system over GF2 (%d conss, %d vars).\n", nconssactive, nvarsmat);
2450 /* Sort variables non-decreasingly with respect to product of objective and 1 minus the current solution value: the
2451 * smaller the value the better it would be to set the variable to 1. This is more likely if the variable appears
2452 * towards the front of the matrix, because only the entries on the steps in the row echolon form will have the
2533 /* If the constraint contains multiaggregated variables, the solution might not be valid, since the
2561 SCIPdebugMsg(scip, "Found %d non-fixed variables in %d nonempty xor constraints.\n", nvarsmat, nconssmat);
2715 /* only try for active constraints and integral variable; hope for the best if they are not active */
2731 if ( SCIPisGE(scip, val, SCIPvarGetLbGlobal(consdata->intvar)) && SCIPisLE(scip, val, SCIPvarGetUbGlobal(consdata->intvar)) )
2794 /** for each variable in the xor constraint, add it to conflict set; for integral variable add corresponding bound */
2799 SCIP_VAR* infervar, /**< variable that was deduced, or NULL (not equal to integral variable) */
2800 SCIP_BDCHGIDX* bdchgidx, /**< bound change index (time stamp of bound change), or NULL for current time */
2824 assert( SCIPisEQ(scip, SCIPgetVarLbAtIndex(scip, vars[i], bdchgidx, FALSE), SCIPgetVarUbAtIndex(scip, vars[i], bdchgidx, FALSE)) );
2878 /* the variable was fixed, because of upper bound of the integral variable and the other fixed variables */
2894 SCIPerrorMessage("invalid inference information %d in xor constraint <%s>\n", proprule, SCIPconsGetName(cons));
2902 /** analyzes conflicting assignment on given constraint, and adds conflict constraint to problem */
2907 SCIP_VAR* infervar, /**< variable that was deduced, or NULL (not equal to integral variable) */
2912 if( (SCIPgetStage(scip) != SCIP_STAGE_SOLVING && !SCIPinProbing(scip)) || !SCIPisConflictAnalysisApplicable(scip) )
2915 /* initialize conflict analysis, and add all variables of infeasible constraint to conflict candidate queue */
2973 /* don't process the constraint, if the watched variables weren't fixed to any value since last propagation call */
2977 /* increase age of constraint; age is reset to zero, if a conflict or a propagation was found */
2984 * that means, we only have to watch (i.e. capture events) of two variables, and switch to other variables
3010 /* if the watched variables are invalid (fixed), find new ones if existing; count the parity */
3049 SCIPdebugMsg(scip, "constraint <%s>: all vars fixed, constraint is infeasible\n", SCIPconsGetName(cons));
3069 SCIPdebugMsg(scip, "fix integral variable <%s> to %d\n", SCIPvarGetName(consdata->intvar), fixval);
3075 SCIPdebugMsg(scip, "node infeasible: activity is %d, bounds of integral variable are [%g,%g]\n",
3086 SCIPdebugMsg(scip, "node infeasible: activity is %d, bounds of integral variable are [%g,%g]\n",
3098 SCIP_CALL( SCIPinferVarLbCons(scip, consdata->intvar, (SCIP_Real) fixval, cons, (int)PROPRULE_0, FALSE, &infeasible, &tightened) );
3105 SCIP_CALL( SCIPinferVarUbCons(scip, consdata->intvar, (SCIP_Real) fixval, cons, (int)PROPRULE_0, FALSE, &infeasible, &tightened) );
3115 SCIPdebugMsg(scip, "constraint <%s>: all vars fixed, constraint is feasible\n", SCIPconsGetName(cons));
3131 SCIP_CALL( SCIPinferBinvarCons(scip, vars[watchedvar1], odd, cons, (int)PROPRULE_1, &infeasible, &tightened) );
3138 if ( consdata->intvar != NULL && !consdata->deleteintvar && SCIPvarGetStatus(consdata->intvar) != SCIP_VARSTATUS_MULTAGGR )
3149 SCIPdebugMsg(scip, "should fix integral variable <%s> to %d\n", SCIPvarGetName(consdata->intvar), fixval);
3155 SCIPdebugMsg(scip, "node infeasible: activity is %d, bounds of integral variable are [%g,%g]\n",
3166 SCIPdebugMsg(scip, "node infeasible: activity is %d, bounds of integral variable are [%g,%g]\n",
3178 SCIP_CALL( SCIPinferVarLbCons(scip, consdata->intvar, (SCIP_Real) fixval, cons, (int)PROPRULE_1, TRUE, &infeasible, &tightened) );
3185 SCIP_CALL( SCIPinferVarUbCons(scip, consdata->intvar, (SCIP_Real) fixval, cons, (int)PROPRULE_1, TRUE, &infeasible, &tightened) );
3189 assert(SCIPisFeasEQ(scip, SCIPvarGetLbLocal(consdata->intvar), SCIPvarGetUbLocal(consdata->intvar)));
3214 nonesmin = 2 * (int)(SCIPvarGetLbLocal(consdata->intvar) + 0.5) + (int) consdata->rhs; /*lint !e713*/
3215 nonesmax = 2 * (int)(SCIPvarGetUbLocal(consdata->intvar) + 0.5) + (int) consdata->rhs; /*lint !e713*/
3220 SCIPdebugMsg(scip, "constraint <%s>: at most %d variables can take value 1, but there should be at least %d.\n", SCIPconsGetName(cons), nvars - nfixedones, nonesmin);
3233 SCIPdebugMsg(scip, "constraint <%s>: at least %d variables are fixed to 1, but there should be at most %d.\n", SCIPconsGetName(cons), nfixedones, nonesmax);
3252 SCIPdebugMsg(scip, "constraint <%s>: propagated lower bound of integral variable <%s> to %g\n", SCIPconsGetName(cons), SCIPvarGetName(consdata->intvar), newlb);
3253 SCIP_CALL( SCIPinferVarLbCons(scip, consdata->intvar, newlb, cons, (int)PROPRULE_INTUB, TRUE, &infeasible, &tightened) );
3259 nonesmin = 2 * (int)(SCIPvarGetLbLocal(consdata->intvar) + 0.5) + (int) consdata->rhs; /*lint !e713*/
3265 SCIPdebugMsg(scip, "constraint <%s>: propagated upper bound of integral variable <%s> to %g\n", SCIPconsGetName(cons), SCIPvarGetName(consdata->intvar), newub);
3266 SCIP_CALL( SCIPinferVarUbCons(scip, consdata->intvar, newub, cons, (int)PROPRULE_INTLB, TRUE, &infeasible, &tightened) );
3272 nonesmax = 2 * (int)(SCIPvarGetUbLocal(consdata->intvar) + 0.5) + (int) consdata->rhs; /*lint !e713*/
3278 /* the number of variables that are free or fixed to 1 is exactly the minimum required -> fix free variables to 1 */
3281 SCIPdebugMsg(scip, "constraint <%s>: fix %d free variables to 1 to reach lower bound of %d\n", SCIPconsGetName(cons), nvars - nfixedzeros - nfixedones, nonesmin);
3287 SCIP_CALL( SCIPinferBinvarCons(scip, vars[i], TRUE, cons, (int)PROPRULE_INTLB, &infeasible, &tightened) );
3300 /* the number of variables that are fixed to 1 is exactly the maximum required -> fix free variables to 0 */
3303 SCIPdebugMsg(scip, "constraint <%s>: fix %d free variables to 0 to guarantee upper bound of %d\n", SCIPconsGetName(cons), nvars - nfixedzeros - nfixedones, nonesmax);
3309 SCIP_CALL( SCIPinferBinvarCons(scip, vars[i], FALSE, cons, (int)PROPRULE_INTUB, &infeasible, &tightened) );
3332 /** resolves a conflict on the given variable by supplying the variables needed for applying the corresponding
3341 SCIP_BDCHGIDX* bdchgidx, /**< bound change index (time stamp of bound change), or NULL for current time */
3342 SCIP_RESULT* result /**< pointer to store the result of the propagation conflict resolving call */
3355 /** try to use clique information to delete a part of the xor constraint or even fix variables */
3402 #if 0 /* try to evaluate if clique presolving should only be done multiple times when the constraint changed */
3407 /* @todo: if clique information would have saved the type of the clique, like <= 1, or == 1 we could do more
3414 /* 1. we have only clique information "<=", so we can check if all variables are in the same clique
3416 * (xor(x1,x2,x3) = 1 and clique(x1,x2,x3) <= 1) => (add set-partioning constraint x1 + x2 + x3 = 1 and delete old
3419 * (xor(x1,x2,x3) = 0 and clique(x1,x2,x3) <= 1) => (fix all variables x1 = x2 = x3 = 0 and delete old xor-
3423 /* 2. we have only clique information "<=", so we can check if all but one variable are in the same clique
3425 * (xor(x1,x2,x3,x4) = 1 and clique(x1,x2,x3) <= 1) => (add set-partioning constraint x1 + x2 + x3 + x4 = 1 and
3428 * (xor(x1,x2,x3,x4) = 0 and clique(x1,x2,x3) <= 1) => (add set-partioning constraint x1 + x2 + x3 + ~x4 = 1 and
3445 assert(SCIPvarIsActive(vars[v]) || (SCIPvarGetStatus(vars[v]) == SCIP_VARSTATUS_NEGATED && SCIPvarIsActive(SCIPvarGetNegationVar(vars[v]))));
3474 /* if the position of the variable which is not in the clique with all other variables is not yet
3515 /* all variables of xor constraints <%s> (with rhs == 1) are in one clique, so create a setpartitioning
3536 /* all variables of xor constraints <%s> (with rhs == 0) are in one clique, so fixed all variables to 0 */
3542 SCIPdebugMsg(scip, "all variables of xor constraints <%s> are in one clique, so fixed all variables to 0\n",
3574 /* if rhs == FALSE we need to exchange the variable not appaering in the clique with the negated variables */
3624 SCIPdebugMsg(scip, "also fix the integer variable <%s> to 0\n", SCIPvarGetName(consdata->intvar));
3646 /** compares each constraint with all other constraints for possible redundancy and removes or changes constraint
3697 /* it can happen that during preprocessing some variables got aggregated and a constraint now has not active
3703 SCIP_CALL( applyFixings(scip, cons0, conshdlrdata->eventhdlr, nchgcoefs, naggrvars, naddconss, cutoff) );
3730 SCIP_CALL( SCIPfixVar(scip, consdata0->vars[0], (SCIP_Real) consdata0->rhs, &infeasible, &fixed) );
3794 SCIP_CALL( SCIPaggregateVars(scip, consdata0->intvar, consdata1->intvar, 1.0, -1.0, 0.0, &infeasible, &redundant, &aggregated) );
3806 /* the special case that only cons0 has a parity variable 'intvar' is treated by swapping cons0 and cons1 */
3889 /* it can happen that during preprocessing some variables got aggregated and a constraint now has not active
3895 SCIP_CALL( applyFixings(scip, cons0, conshdlrdata->eventhdlr, nchgcoefs, naggrvars, naddconss, cutoff) );
3906 for( c = (cons0changed ? 0 : firstchange); c < chkind && !(*cutoff) && SCIPconsIsActive(cons0) && !SCIPisStopped(scip); ++c )
3935 /* it can happen that during preprocessing some variables got aggregated and a constraint now has not active
3941 SCIP_CALL( applyFixings(scip, cons1, conshdlrdata->eventhdlr, nchgcoefs, naggrvars, naddconss, cutoff) );
3982 SCIP_CALL( SCIPfixVar(scip, consdata1->vars[0], (SCIP_Real) consdata1->rhs, &infeasible, &fixed) );
4001 SCIP_CALL( applyFixings(scip, cons0, conshdlrdata->eventhdlr, nchgcoefs, naggrvars, naddconss, cutoff) );
4032 SCIP_CALL( applyFixings(scip, cons0, conshdlrdata->eventhdlr, nchgcoefs, naggrvars, naddconss, cutoff) );
4091 * (b) the problem variable sets are almost equal with only one variable in each constraint that is not
4176 if( (cons0hastwoothervars && singlevar1 != NULL) || (cons1hastwoothervars && singlevar0 != NULL) )
4202 * if intvar0 = NULL we have to assign intvar0 = y1. otherwise, we have to ensure that y1 = y0 holds.
4203 * if aggregation is allowed, we can aggregate both variables. otherwise, we have to add a linear
4284 /* more than one additional variable in cons0: add cons1 to cons0, thus eliminating the equal variables */
4294 SCIP_CALL( applyFixings(scip, cons0, conshdlrdata->eventhdlr, nchgcoefs, naggrvars, naddconss, cutoff) );
4296 assert(consdata0->nvars >= 2); /* at least the two "other" variables should remain in the constraint */
4329 /* more than one additional variable in cons1: add cons0 to cons1, thus eliminating the equal variables */
4338 SCIP_CALL( applyFixings(scip, cons1, conshdlrdata->eventhdlr, nchgcoefs, naggrvars, naddconss, cutoff) );
4340 assert(consdata1->nvars >= 2); /* at least the two "other" variables should remain in the constraint */
4354 /* sum of constraints is parity == singlevar0 xor singlevar1: aggregate variables and delete cons1 */
4407 /* if aggregation in the core of SCIP is not changed we do not need to call applyFixing, this would be the correct
4413 SCIP_CALL( applyFixings(scip, cons0, conshdlrdata->eventhdlr, nchgcoefs, naggrvars, naddconss, cutoff) );
4424 /** creates and captures a xor constraint x_0 xor ... xor x_{k-1} = rhs with a given artificial integer variable for the
4427 * @note the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()
4456 SCIP_Bool removable, /**< should the relaxation be removed from the LP due to aging or cleanup?
4458 SCIP_Bool stickingatnode /**< should the constraint always be kept at the node where it was added, even
4478 SCIP_CALL( SCIPcreateCons(scip, cons, name, conshdlr, consdata, initial, separate, enforce, check, propagate,
4492 * Assuming all variables are binary and have coefficients with an absolute value 1, except for an integer (or binary) variable
4493 * \f$z\f$ which has coefficient \f$a \in \{-2,2\}\f$ with absolute value 2 and appears only in this constraint,
4499 * \Leftrightarrow & \sum_{i \in I} \bar{x}_i + \sum_{j \in J} x_j - 2 \cdot y = (r + |I|) \text{ mod } 2,
4509 * If \f$a = -2\f$ and \f$z \in [\ell_z, u_z]\f$, then \f$y \in [\ell_y, u_y]\f$, where \f$\ell_y = \left\lfloor
4510 * \frac{r + |I|}{2} \right\rfloor + \ell_z\f$ and \f$u_y = \left\lfloor \frac{r + |I|}{2} \right\rfloor + u_z\f$.
4512 * If \f$a = 2\f$, then \f$\ell_y = \left\lfloor \frac{r + |I|}{2} \right\rfloor - u_z\f$ and \f$u_y = \left\lfloor
4519 * If \f$\ell_y \leq 0\f$ and \f$u_y \geq (|I| + |J|)/2\f$, then the XOR constraint is a reformulation of the above
4520 * transformed constraint, otherwise it is a relaxation because the bounds on the \f$y\f$-variable may disallow
4521 * too many (or too few) operators set to 1. Therefore, the XOR constraint handler verifies in this case that the linear
4532 /* @todo also applicable if the integer variable has a coefficient different from 2, e.g. a coefficient like 0.5 then
4533 * we could generate a new integer variable aggregated to the old one, possibly the constraint was then
4534 * normalized and all binary variables have coefficients of 2.0, if the coefficient is 4 then we need holes ...
4536 if( integral && nposcont + nnegcont == 0 && nposbin + nnegbin + nposimplbin + nnegimplbin >= nvars-1 && ncoeffspone + ncoeffsnone == nvars-1 && ncoeffspint + ncoeffsnint == 1 )
4600 /* we need a new variable if the rhs is not 0 or 1 or if the coefficient was +2, since in these cases, we
4607 /* check if we can use the parity variable as integer variable of the XOR constraint or do we need to
4692 SCIP_CALL( createConsXorIntvar(scip, upgdcons, SCIPconsGetName(cons), rhsparity, nvars - 1, xorvars, intvar,
4737 /** destructor of constraint handler to free constraint handler data (called when SCIP is exiting) */
4754 /** solving process deinitialization method of constraint handler (called before branch and bound process data is freed) */
4781 if( SCIPgetStage(scip) == SCIP_STAGE_PRESOLVING || SCIPgetStage(scip) == SCIP_STAGE_INITPRESOLVE )
4787 SCIP_CALL( SCIPdropVarEvent(scip, (*consdata)->vars[v], SCIP_EVENTTYPE_VARFIXED, conshdlrdata->eventhdlr,
4811 SCIP_CALL( consdataCreate(scip, &targetdata, sourcedata->rhs, sourcedata->nvars, sourcedata->vars, sourcedata->intvar) );
4815 SCIPconsIsInitial(sourcecons), SCIPconsIsSeparated(sourcecons), SCIPconsIsEnforced(sourcecons),
4818 SCIPconsIsDynamic(sourcecons), SCIPconsIsRemovable(sourcecons), SCIPconsIsStickingAtNode(sourcecons)) );
4824 /** LP initialization method of constraint handler (called before the initial LP relaxation at a node is solved) */
4861 SCIP_CALL( separateCons(scip, conss[c], NULL, conshdlrdata->separateparity, &separated, &cutoff) );
4892 SCIP_CALL( separateCons(scip, conss[c], sol, conshdlrdata->separateparity, &separated, &cutoff) );
4926 SCIP_CALL( separateCons(scip, conss[i], NULL, conshdlrdata->separateparity, &separated, &cutoff) );
4963 SCIP_CALL( separateCons(scip, conss[i], sol, conshdlrdata->separateparity, &separated, &cutoff) );
5039 SCIPinfoMessage(scip, NULL, ";\nviolation: %d operands are set to TRUE but integer variable has value of %g\n", sum, SCIPgetSolVal(scip, sol, consdata->intvar));
5073 SCIP_CALL( propagateCons(scip, conss[c], conshdlrdata->eventhdlr, &cutoff, &nfixedvars, &nchgbds) );
5102 /** presolving initialization method of constraint handler (called when presolving is about to begin) */
5123 SCIP_CALL( SCIPcatchVarEvent(scip, consdata->vars[v], SCIP_EVENTTYPE_VARFIXED, conshdlrdata->eventhdlr,
5131 /** presolving deinitialization method of constraint handler (called after presolving has been finished) */
5154 SCIP_CALL( SCIPdropVarEvent(scip, consdata->vars[v], SCIP_EVENTTYPE_VARFIXED, conshdlrdata->eventhdlr,
5213 SCIP_CALL( applyFixings(scip, cons, conshdlrdata->eventhdlr, nchgcoefs, naggrvars, naddconss, &cutoff) );
5266 fixedintvar = consdata->intvar == NULL ? TRUE : SCIPisEQ(scip, SCIPvarGetLbGlobal(consdata->intvar), SCIPvarGetUbGlobal(consdata->intvar));
5281 assert(consdata->deleteintvar || (consdata->rhs && SCIPvarGetLbGlobal(consdata->intvar) < 0.5));
5291 /* try to use clique information to upgrade the constraint to a set-partitioning constraint or fix
5300 * only apply this expensive procedure, if the single constraint preprocessing did not find any reductions
5302 if( !cutoff && (presoltiming & SCIP_PRESOLTIMING_EXHAUSTIVE) != 0 && SCIPisPresolveFinished(scip) )
5306 /* detect redundant constraints; fast version with hash table instead of pairwise comparison */
5307 SCIP_CALL( detectRedundantConstraints(scip, SCIPblkmem(scip), conss, nconss, &firstchange, nchgcoefs,
5321 npaircomparisons += (SCIPconsGetData(conss[c])->changed) ? (SCIP_Longint) c : ((SCIP_Longint) c - (SCIP_Longint) firstchange);
5328 if( ((SCIP_Real) (*ndelconss - lastndelconss)) / ((SCIP_Real) npaircomparisons) < MINGAINPERNMINCOMPARISONS )
5348 if ( conshdlrdata->addextendedform && *result == SCIP_DIDNOTFIND && SCIPisPresolveFinished(scip) )
5403 SCIP_CALL( SCIPaddVarLocksType(scip, consdata->vars[i], locktype, nlockspos + nlocksneg, nlockspos + nlocksneg) );
5409 SCIP_CALL( SCIPaddVarLocksType(scip, consdata->intvar, locktype, nlockspos + nlocksneg, nlockspos + nlocksneg) );
5466 SCIP_CALL( SCIPgetVarCopy(sourcescip, scip, intvar, &targetintvar, varmap, consmap, global, valid) );
5471 SCIPdebugMsg(scip, "Copied integral variable <%s> (bounds: [%g,%g])\n", SCIPvarGetName(targetintvar),
5479 SCIP_CALL( createConsXorIntvar(scip, cons, consname, SCIPgetRhsXor(sourcescip, sourcecons), 0, NULL,
5480 targetintvar, initial, separate, enforce, check, propagate, local, modifiable, dynamic, removable,
5493 SCIP_CALL( SCIPgetVarCopy(sourcescip, scip, sourcevars[v], &targetvars[v], varmap, consmap, global, valid) );
5497 /* map artificial relaxation variable of the source constraint to variable of the target SCIP */
5500 SCIP_CALL( SCIPgetVarCopy(sourcescip, scip, intvar, &targetintvar, varmap, consmap, global, valid) );
5503 SCIPdebugMsg(scip, "Copied integral variable <%s> (bounds: [%g,%g])\n", SCIPvarGetName(targetintvar),
5511 SCIP_CALL( createConsXorIntvar(scip, cons, consname, SCIPgetRhsXor(sourcescip, sourcecons), nvars, targetvars,
5512 targetintvar, initial, separate, enforce, check, propagate, local, modifiable, dynamic, removable,
5542 SCIP_CALL( SCIPparseVarsList(scip, str, vars, &nvars, varssize, &requiredsize, &endptr, ',', success) );
5556 SCIP_CALL( SCIPparseVarsList(scip, str, vars, &nvars, varssize, &requiredsize, &endptr, ',', success) );
5631 SCIP_CALL( createConsXorIntvar(scip, cons, name, (rhs > 0.5 ? TRUE : FALSE), nvars, vars, intvar,
5632 initial, separate, enforce, check, propagate, local, modifiable, dynamic, removable, stickingatnode) );
5638 initial, separate, enforce, check, propagate, local, modifiable, dynamic, removable, stickingatnode) );