cuts.c
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33 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
58 /* =========================================== general static functions =========================================== */
91 SCIPquadprecProdQD(coef, coef, (sol == NULL ? SCIPvarGetLPSol(vars[cutinds[i]]) : SCIPgetSolVal(scip, sol, vars[cutinds[i]])));
97 SCIPquadprecProdQD(coef, coef, (islocal ? SCIPvarGetLbLocal(vars[cutinds[i]]) : SCIPvarGetLbGlobal(vars[cutinds[i]])));
101 SCIPquadprecProdQD(coef, coef, (islocal ? SCIPvarGetUbLocal(vars[cutinds[i]]) : SCIPvarGetUbGlobal(vars[cutinds[i]])));
125 int*RESTRICT inds, /**< pointer to array with variable problem indices of non-zeros in variable vector */
170 int*RESTRICT inds, /**< pointer to array with variable problem indices of non-zeros in variable vector */
215 int* cutinds, /**< array of the problem indices of variables with a non-zero coefficient in the cut */
273 /** calculates the efficacy norm of the given aggregation row, which depends on the "separating/efficacynorm" parameter */
277 SCIP_Real* vals, /**< array of the non-zero coefficients in the vector; this is a quad precision array! */
278 int* inds, /**< array of the problem indices of variables with a non-zero coefficient in the vector */
335 /** calculates the cut efficacy for the given solution; the cut coefs are stored densely and in quad precision */
340 SCIP_Real* cutcoefs, /**< array of the non-zero coefficients in the cut; this is a quad precision array! */
342 int* cutinds, /**< array of the problem indices of variables with a non-zero coefficient in the cut */
418 int* cutinds, /**< array of the problem indices of variables with a non-zero coefficient in the cut */
511 int* cutinds, /**< array of the problem indices of variables with a non-zero coefficient in the cut */
520 /* loop over non-zeros and remove values below minval; values above QUAD_EPSILON are cancelled with their bound
635 /** change given coefficient to new given value, adjust right hand side using the variables bound;
680 /** change given (quad) coefficient to new given value, adjust right hand side using the variables bound;
725 /** scales the cut and then tightens the coefficients of the given cut based on the maximal activity;
726 * see cons_linear.c consdataTightenCoefs() for details; the cut is given in a semi-sparse quad precision array;
736 int* cutinds, /**< array of the problem indices of variables with a non-zero coefficient in the cut */
758 /* compute maximal activity and maximal absolute coefficient values for all and for integral variables in the cut */
770 SCIP_Real lb = cutislocal ? SCIPvarGetLbLocal(vars[cutinds[i]]) : SCIPvarGetLbGlobal(vars[cutinds[i]]);
788 SCIP_Real ub = cutislocal ? SCIPvarGetUbLocal(vars[cutinds[i]]) : SCIPvarGetUbGlobal(vars[cutinds[i]]);
838 (SCIP_Longint)scip->set->sepa_maxcoefratio, scip->set->sepa_maxcoefratio, &intscalar, &success) );
859 if( chgQuadCoeffWithBound(scip, vars[cutinds[i]], QUAD(val), intval, cutislocal, QUAD(cutrhs)) )
899 SCIP_Real lb = cutislocal ? SCIPvarGetLbLocal(vars[cutinds[i]]) : SCIPvarGetLbGlobal(vars[cutinds[i]]);
909 SCIP_Real ub = cutislocal ? SCIPvarGetUbLocal(vars[cutinds[i]]) : SCIPvarGetUbGlobal(vars[cutinds[i]]);
982 /* no coefficient tightening can be performed since the precondition doesn't hold for any of the variables */
988 /* loop over the integral variables and try to tighten the coefficients; see cons_linear for more details */
1003 if( QUAD_TO_DBL(val) < 0.0 && SCIPisLE(scip, maxact + QUAD_TO_DBL(val), QUAD_TO_DBL(*cutrhs)) )
1006 SCIP_Real lb = cutislocal ? SCIPvarGetLbLocal(vars[cutinds[i]]) : SCIPvarGetLbGlobal(vars[cutinds[i]]);
1012 /* if cut is integral, the true coefficient must also be integral; thus round it to exact integral value */
1026 SCIPdebugPrintf("tightened coefficient from %g to %g; rhs changed from %g to %g; the bounds are [%g,%g]\n",
1050 else if( QUAD_TO_DBL(val) > 0.0 && SCIPisLE(scip, maxact - QUAD_TO_DBL(val), QUAD_TO_DBL(*cutrhs)) )
1053 SCIP_Real ub = cutislocal ? SCIPvarGetUbLocal(vars[cutinds[i]]) : SCIPvarGetUbGlobal(vars[cutinds[i]]);
1059 /* if cut is integral, the true coefficient must also be integral; thus round it to exact integral value */
1073 SCIPdebugPrintf("tightened coefficient from %g to %g; rhs changed from %g to %g; the bounds are [%g,%g]\n",
1097 else /* due to sorting we can stop completely if the precondition was not fulfilled for this variable */
1106 /** scales the cut and then tightens the coefficients of the given cut based on the maximal activity;
1107 * see cons_linear.c consdataTightenCoefs() for details; the cut is given in a semi-sparse array;
1115 int* cutinds, /**< array of the problem indices of variables with a non-zero coefficient in the cut */
1137 /* compute maximal activity and maximal absolute coefficient values for all and for integral variables in the cut */
1149 SCIP_Real lb = cutislocal ? SCIPvarGetLbLocal(vars[cutinds[i]]) : SCIPvarGetLbGlobal(vars[cutinds[i]]);
1166 SCIP_Real ub = cutislocal ? SCIPvarGetUbLocal(vars[cutinds[i]]) : SCIPvarGetUbGlobal(vars[cutinds[i]]);
1213 SCIP_CALL( SCIPcalcIntegralScalar(intcoeffs, *cutnnz, -SCIPsumepsilon(scip), SCIPepsilon(scip),
1214 (SCIP_Longint)scip->set->sepa_maxcoefratio, scip->set->sepa_maxcoefratio, &intscalar, &success) );
1273 SCIP_Real lb = cutislocal ? SCIPvarGetLbLocal(vars[cutinds[i]]) : SCIPvarGetLbGlobal(vars[cutinds[i]]);
1283 SCIP_Real ub = cutislocal ? SCIPvarGetUbLocal(vars[cutinds[i]]) : SCIPvarGetUbGlobal(vars[cutinds[i]]);
1344 /* no coefficient tightening can be performed since the precondition doesn't hold for any of the variables */
1350 /* loop over the integral variables and try to tighten the coefficients; see cons_linear for more details */
1368 SCIP_Real lb = cutislocal ? SCIPvarGetLbLocal(vars[cutinds[i]]) : SCIPvarGetLbGlobal(vars[cutinds[i]]);
1374 /* if cut is integral, the true coefficient must also be integral; thus round it to exact integral value */
1388 SCIPdebugPrintf("tightened coefficient from %g to %g; rhs changed from %g to %g; the bounds are [%g,%g]\n",
1414 SCIP_Real ub = cutislocal ? SCIPvarGetUbLocal(vars[cutinds[i]]) : SCIPvarGetUbGlobal(vars[cutinds[i]]);
1420 /* if cut is integral, the true coefficient must also be integral; thus round it to exact integral value */
1434 SCIPdebugPrintf("tightened coefficient from %g to %g; rhs changed from %g to %g; the bounds are [%g,%g]\n",
1457 else /* due to sorting we can stop completely if the precondition was not fulfilled for this variable */
1466 /** perform activity based coefficient tightening on the given cut; returns TRUE if the cut was detected
1476 int* cutinds, /**< array of the problem indices of variables with a non-zero coefficient in the cut */
1508 SCIP_Real lb = cutislocal ? SCIPvarGetLbLocal(vars[cutinds[i]]) : SCIPvarGetLbGlobal(vars[cutinds[i]]);
1525 SCIP_Real ub = cutislocal ? SCIPvarGetUbLocal(vars[cutinds[i]]) : SCIPvarGetUbGlobal(vars[cutinds[i]]);
1551 /* terminate, because coefficient tightening cannot be performed; also excludes the case in which no integral variable is present */
1558 /* loop over the integral variables and try to tighten the coefficients; see cons_linear for more details */
1561 /* due to sorting, we can exit if we reached a continuous variable: all further integral variables have 0 coefficents anyway */
1570 SCIP_Real lb = cutislocal ? SCIPvarGetLbLocal(vars[cutinds[i]]) : SCIPvarGetLbGlobal(vars[cutinds[i]]);
1583 SCIPdebugPrintf("tightened coefficient from %g to %g; rhs changed from %g to %g; the bounds are [%g,%g]\n",
1611 SCIP_Real ub = cutislocal ? SCIPvarGetUbLocal(vars[cutinds[i]]) : SCIPvarGetUbGlobal(vars[cutinds[i]]);
1624 SCIPdebugPrintf("tightened coefficient from %g to %g; rhs changed from %g to %g; the bounds are [%g,%g]\n",
1649 else /* due to sorting we can stop completely if the precondition was not fulfilled for this variable */
1659 /* =========================================== aggregation row =========================================== */
1745 SCIPmessageFPrintInfo(messagehdlr, file, "%+.15g<%s> ", QUAD_TO_DBL(val), SCIPvarGetName(vars[aggrrow->inds[i]]));
1768 SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*aggrrow)->vals, source->vals, QUAD_ARRAY_SIZE(nvars)) );
1779 SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*aggrrow)->rowsinds, source->rowsinds, source->nrows) );
1780 SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*aggrrow)->slacksign, source->slacksign, source->nrows) );
1781 SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*aggrrow)->rowweights, source->rowweights, source->nrows) );
1824 SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &aggrrow->rowsinds, aggrrow->rowssize, newsize) );
1825 SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &aggrrow->slacksign, aggrrow->rowssize, newsize) );
1826 SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &aggrrow->rowweights, aggrrow->rowssize, newsize) );
1844 /* Automatically decide, whether we want to use the left or the right hand side of the row in the summation.
1871 SCIP_CALL( varVecAddScaledRowCoefsQuad(aggrrow->inds, aggrrow->vals, &aggrrow->nnz, row, weight) );
1876 /** Removes a given variable @p var from position @p pos the aggregation row and updates the right-hand side according
1877 * to sign of the coefficient, i.e., rhs -= coef * bound, where bound = lb if coef >= 0 and bound = ub, otherwise.
1879 * @note: The choice of global or local bounds depend on the validity (global or local) of the aggregation row.
1881 * @note: The list of non-zero indices will be updated by swapping the last non-zero index to @p pos.
1941 /** add the objective function with right-hand side @p rhs and scaled by @p scale to the aggregation row */
2084 /** calculates the efficacy norm of the given aggregation row, which depends on the "separating/efficacynorm" parameter
2086 * @return the efficacy norm of the given aggregation row, which depends on the "separating/efficacynorm" parameter
2096 /** Adds one row to the aggregation row. Differs from SCIPaggrRowAddRow() by providing some additional
2107 int negslack, /**< should negative slack variables allowed to be used? (0: no, 1: only for integral rows, 2: yes) */
2119 if( SCIPisFeasZero(scip, weight) || SCIProwIsModifiable(row) || (SCIProwIsLocal(row) && !allowlocal) )
2138 else if( SCIPisInfinity(scip, SCIProwGetRhs(row)) || (weight < 0.0 && ! SCIPisInfinity(scip, -SCIProwGetLhs(row))) )
2143 else if( (weight < 0.0 && !SCIPisInfinity(scip, -row->lhs)) || SCIPisInfinity(scip, row->rhs) )
2183 SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &aggrrow->rowsinds, aggrrow->rowssize, newsize) );
2184 SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &aggrrow->slacksign, aggrrow->rowssize, newsize) );
2185 SCIP_CALL( SCIPreallocBlockMemoryArray(scip, &aggrrow->rowweights, aggrrow->rowssize, newsize) );
2195 SCIP_CALL( varVecAddScaledRowCoefsQuad(aggrrow->inds, aggrrow->vals, &aggrrow->nnz, row, weight) );
2215 int negslack, /**< should negative slack variables allowed to be used? (0: no, 1: only for integral rows, 2: yes) */
2241 SCIP_CALL( addOneRow(scip, aggrrow, rows[rowinds[k]], weights[rowinds[k]], sidetypebasis, allowlocal, negslack, maxaggrlen, &rowtoolong) );
2253 SCIP_CALL( addOneRow(scip, aggrrow, rows[k], weights[k], sidetypebasis, allowlocal, negslack, maxaggrlen, &rowtoolong) );
2278 SCIP_Bool* success /**< pointer to return whether post-processing was succesful or cut is redundant */
2306 SCIP_CALL( cutTightenCoefs(scip, cutislocal, cutcoefs, QUAD(&rhs), cutinds, nnz, &redundant) );
2325 *success = ! removeZeros(scip, minallowedcoef, cutislocal, cutcoefs, QUAD(&rhs), cutinds, nnz);
2347 SCIP_Bool* success /**< pointer to return whether the cleanup was successful or if it is useless */
2363 if( removeZerosQuad(scip, SCIPfeastol(scip), cutislocal, cutcoefs, QUAD(cutrhs), cutinds, nnz) )
2372 SCIP_CALL( cutTightenCoefsQuad(scip, cutislocal, cutcoefs, QUAD(cutrhs), cutinds, nnz, &redundant) );
2393 *success = ! removeZerosQuad(scip, minallowedcoef, cutislocal, cutcoefs, QUAD(cutrhs), cutinds, nnz);
2409 *valid = ! removeZerosQuad(scip, SCIPsumepsilon(scip), useglbbounds ? FALSE : aggrrow->local, aggrrow->vals,
2468 /** gets the array of corresponding variable problem indices for each non-zero in the aggregation row */
2518 /* =========================================== c-MIR =========================================== */
2528 int usevbds, /**< should variable bounds be used in bound transformation? (0: no, 1: only binary, 2: all) */
2529 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
2561 if( bestvlbidx >= 0 && (bestvlb > *bestlb || (*bestlbtype < 0 && SCIPisGE(scip, bestvlb, *bestlb))) )
2565 /* we have to avoid cyclic variable bound usage, so we enforce to use only variable bounds variables of smaller index */
2566 /**@todo this check is not needed for continuous variables; but allowing all but binary variables
2589 int usevbds, /**< should variable bounds be used in bound transformation? (0: no, 1: only binary, 2: all) */
2590 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
2622 if( bestvubidx >= 0 && (bestvub < *bestub || (*bestubtype < 0 && SCIPisLE(scip, bestvub, *bestub))) )
2626 /* we have to avoid cyclic variable bound usage, so we enforce to use only variable bounds variables of smaller index */
2627 /**@todo this check is not needed for continuous variables; but allowing all but binary variables
2644 /** determine the best bounds with respect to the given solution for complementing the given variable */
2650 SCIP_Real boundswitch, /**< fraction of domain up to which lower bound is used in transformation */
2651 int usevbds, /**< should variable bounds be used in bound transformation? (0: no, 1: only binary, 2: all) */
2652 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
2653 SCIP_Bool fixintegralrhs, /**< should complementation tried to be adjusted such that rhs gets fractional? */
2655 int* boundsfortrans, /**< bounds that should be used for transformed variables: vlb_idx/vub_idx,
2658 SCIP_BOUNDTYPE* boundtypesfortrans, /**< type of bounds that should be used for transformed variables;
2664 SCIP_BOUNDTYPE* selectedbound, /**< pointer to store whether the lower bound or the upper bound should be preferred */
2677 assert(SCIPvarGetType(var) == SCIP_VARTYPE_CONTINUOUS || ( boundsfortrans[v] == -2 || boundsfortrans[v] == -1 ));
2708 *bestlb = vlbcoefs[k] * (sol == NULL ? SCIPvarGetLPSol(vlbvars[k]) : SCIPgetSolVal(scip, sol, vlbvars[k])) + vlbconsts[k];
2714 /* find closest upper bound in standard upper bound (and variable upper bounds for continuous variables) */
2715 SCIP_CALL( findBestUb(scip, var, sol, fixintegralrhs ? usevbds : 0, allowlocal && fixintegralrhs, bestub, &simpleub, bestubtype) );
2746 /* we have to avoid cyclic variable bound usage, so we enforce to use only variable bounds variables of smaller index */
2747 *bestub = vubcoefs[k] * (sol == NULL ? SCIPvarGetLPSol(vubvars[k]) : SCIPgetSolVal(scip, sol, vubvars[k])) + vubconsts[k];
2753 /* find closest lower bound in standard lower bound (and variable lower bounds for continuous variables) */
2754 SCIP_CALL( findBestLb(scip, var, sol, fixintegralrhs ? usevbds : 0, allowlocal && fixintegralrhs, bestlb, &simplelb, bestlbtype) );
2763 /* find closest lower bound in standard lower bound (and variable lower bounds for continuous variables) */
2766 /* find closest upper bound in standard upper bound (and variable upper bounds for continuous variables) */
2796 else if( ((*bestlbtype) >= 0 || (*bestubtype) >= 0) && !SCIPisEQ(scip, *bestlb - simplelb, simpleub - *bestub) )
2843 /** performs the bound substitution step with the given variable or simple bounds for the variable with the given problem index */
2854 SCIP_Real boundval, /**< array of best bound to be used for the substitution for each nonzero index */
2856 SCIP_Bool* localbdsused /**< pointer to updated whether a local bound was used for substitution */
2923 /** performs the bound substitution step with the simple bound for the variable with the given problem index */
2931 SCIP_Real boundval, /**< array of best bound to be used for the substitution for each nonzero index */
2933 SCIP_Bool* localbdsused /**< pointer to updated whether a local bound was used for substitution */
2958 * x^\prime_j := x_j - lb_j,& x_j = x^\prime_j + lb_j,& a^\prime_j = a_j,& \mbox{if lb is used in transformation}\\
2959 * x^\prime_j := ub_j - x_j,& x_j = ub_j - x^\prime_j,& a^\prime_j = -a_j,& \mbox{if ub is used in transformation}
2967 * x^\prime_j := x_j - (bl_j\, zl_j + dl_j),& x_j = x^\prime_j + (bl_j\, zl_j + dl_j),& a^\prime_j = a_j,& \mbox{if vlb is used in transf.} \\
2968 * x^\prime_j := (bu_j\, zu_j + du_j) - x_j,& x_j = (bu_j\, zu_j + du_j) - x^\prime_j,& a^\prime_j = -a_j,& \mbox{if vub is used in transf.}
2971 * move the constant terms \f$ a_j\, dl_j \f$ or \f$ a_j\, du_j \f$ to the rhs, and update the coefficient of the VLB variable:
2983 SCIP_Real boundswitch, /**< fraction of domain up to which lower bound is used in transformation */
2985 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
2986 SCIP_Bool fixintegralrhs, /**< should complementation tried to be adjusted such that rhs gets fractional? */
2988 int* boundsfortrans, /**< bounds that should be used for transformed variables: vlb_idx/vub_idx,
2991 SCIP_BOUNDTYPE* boundtypesfortrans, /**< type of bounds that should be used for transformed variables;
3002 SCIP_Bool* freevariable, /**< stores whether a free variable was found in MIR row -> invalid summation */
3003 SCIP_Bool* localbdsused /**< pointer to store whether local bounds were used in transformation */
3033 /* start with continuous variables, because using variable bounds can affect the untransformed integral
3034 * variables, and these changes have to be incorporated in the transformation of the integral variables
3046 SCIP_CALL( determineBestBounds(scip, vars[cutinds[i]], sol, boundswitch, usevbds ? 2 : 0, allowlocal, fixintegralrhs,
3048 bestlbs + i, bestubs + i, bestlbtypes + i, bestubtypes + i, selectedbounds + i, freevariable) );
3070 performBoundSubstitution(scip, cutinds, cutcoefs, QUAD(cutrhs), nnz, varsign[i], boundtype[i], bestlbs[i], v, localbdsused);
3080 performBoundSubstitution(scip, cutinds, cutcoefs, QUAD(cutrhs), nnz, varsign[i], boundtype[i], bestubs[i], v, localbdsused);
3084 /* remove integral variables that now have a zero coefficient due to variable bound usage of continuous variables
3106 /* determine the best bounds for the integral variable, usevbd can be set to 0 here as vbds are only used for continuous variables */
3109 bestlbs + i, bestubs + i, bestlbtypes + i, bestubtypes + i, selectedbounds + i, freevariable) );
3118 /* now perform the bound substitution on the remaining integral variables which only uses standard bounds */
3133 performBoundSubstitutionSimple(scip, cutcoefs, QUAD(cutrhs), boundtype[i], bestlbs[i], v, localbdsused);
3144 performBoundSubstitutionSimple(scip, cutcoefs, QUAD(cutrhs), boundtype[i], bestubs[i], v, localbdsused);
3226 /* prefer larger violations; for equal violations, prefer smaller f0 values since then the possibility that
3229 if( SCIPisGT(scip, violgain, bestviolgain) || (SCIPisGE(scip, violgain, bestviolgain) && newf0 < bestnewf0) )
3257 assert(bestubtypes[besti] < 0); /* cannot switch to a variable bound (would lead to further coef updates) */
3264 assert(bestlbtypes[besti] < 0); /* cannot switch to a variable bound (would lead to further coef updates) */
3285 /** Calculate fractionalities \f$ f_0 := b - down(b), f_j := a^\prime_j - down(a^\prime_j) \f$, and derive MIR cut \f$ \tilde{a} \cdot x' \leq down(b) \f$
3300 * x^\prime_j := x_j - lb_j,& x_j = x^\prime_j + lb_j,& a^\prime_j = a_j,& \hat{a}_j := \tilde{a}_j,& \mbox{if lb was used in transformation} \\
3301 * x^\prime_j := ub_j - x_j,& x_j = ub_j - x^\prime_j,& a^\prime_j = -a_j,& \hat{a}_j := -\tilde{a}_j,& \mbox{if ub was used in transformation}
3316 * x^\prime_j := x_j - (bl_j \cdot zl_j + dl_j),& x_j = x^\prime_j + (bl_j\, zl_j + dl_j),& a^\prime_j = a_j,& \hat{a}_j := \tilde{a}_j,& \mbox{(vlb)} \\
3317 * x^\prime_j := (bu_j\, zu_j + du_j) - x_j,& x_j = (bu_j\, zu_j + du_j) - x^\prime_j,& a^\prime_j = -a_j,& \hat{a}_j := -\tilde{a}_j,& \mbox{(vub)}
3330 * \hat{a}_{zl_j} := \hat{a}_{zl_j} - \tilde{a}_j\, bl_j = \hat{a}_{zl_j} - \hat{a}_j\, bl_j,& \mbox{or} \\
3340 int*RESTRICT cutinds, /**< array of variables problem indices for non-zero coefficients in cut */
3343 int*RESTRICT boundtype, /**< stores the bound used for transformed variable (vlb/vub_idx or -1 for lb/ub) */
3365 /* Loop backwards to process integral variables first and be able to delete coefficients of integral variables
3373 /*in debug mode check that all continuous variables of the aggrrow come before the integral variables */
3441 /* move the constant term -a~_j * lb_j == -a^_j * lb_j , or a~_j * ub_j == -a^_j * ub_j to the rhs */
3476 /* now process the continuous variables; postpone deletetion of zeros till all continuous variables have been processed */
3500 SCIPquadprecProdQQ(cutaj, onedivoneminusf0, aj); /* cutaj = varsign[i] * aj * onedivoneminusf0; // a^_j */
3524 /* move the constant term -a~_j * lb_j == -a^_j * lb_j , or a~_j * ub_j == -a^_j * ub_j to the rhs */
3631 * The coefficient of the slack variable s_r is equal to the row's weight times the slack's sign, because the slack
3634 * Depending on the slacks type (integral or continuous), its coefficient in the cut calculates as follows:
3638 * & \hat{a}_r = \tilde{a}_r = down(a^\prime_r) + (f_r - f0)/(1 - f0),& \mbox{if}\qquad f_r > f0 \\
3644 * Substitute \f$ \hat{a}_r \cdot s_r \f$ by adding \f$ \hat{a}_r \f$ times the slack's definition to the cut.
3708 || (slacksign[i] == -1 && SCIPisFeasIntegral(scip, row->lhs - row->constant))) ) /*lint !e613*/
3790 /** calculates an MIR cut out of the weighted sum of LP rows; The weights of modifiable rows are set to 0.0, because
3793 * @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
3805 SCIP_Real boundswitch, /**< fraction of domain up to which lower bound is used in transformation */
3807 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
3808 SCIP_Bool fixintegralrhs, /**< should complementation tried to be adjusted such that rhs gets fractional? */
3809 int* boundsfortrans, /**< bounds that should be used for transformed variables: vlb_idx/vub_idx,
3812 SCIP_BOUNDTYPE* boundtypesfortrans, /**< type of bounds that should be used for transformed variables;
3818 SCIP_Real* cutcoefs, /**< array to store the non-zero coefficients in the cut if its efficacy improves cutefficacy */
3819 SCIP_Real* cutrhs, /**< pointer to store the right hand side of the cut if its efficacy improves cutefficacy */
3820 int* cutinds, /**< array to store the indices of non-zero coefficients in the cut if its efficacy improves cutefficacy */
3821 int* cutnnz, /**< pointer to store the number of non-zeros in the cut if its efficacy improves cutefficacy */
3823 int* cutrank, /**< pointer to return rank of generated cut or NULL if it improves cutefficacy */
3824 SCIP_Bool* cutislocal, /**< pointer to store whether the generated cut is only valid locally if it improves cutefficacy */
3825 SCIP_Bool* success /**< pointer to store whether the returned coefficients are a valid MIR cut and it improves cutefficacy */
3891 * x'_j := x_j - (bl_j * zl_j + dl_j), x_j == x'_j + (bl_j * zl_j + dl_j), a'_j == a_j, if vlb is used in transf.
3892 * x'_j := (bu_j * zu_j + du_j) - x_j, x_j == (bu_j * zu_j + du_j) - x'_j, a'_j == -a_j, if vub is used in transf.
3893 * move the constant terms "a_j * dl_j" or "a_j * du_j" to the rhs, and update the coefficient of the VLB variable:
3897 SCIP_CALL( cutsTransformMIR(scip, sol, boundswitch, usevbds, allowlocal, fixintegralrhs, FALSE,
3898 boundsfortrans, boundtypesfortrans, minfrac, maxfrac, tmpcoefs, QUAD(&rhs), tmpinds, &tmpnnz, varsign, boundtype, &freevariable, &localbdsused) );
3917 * x'_j := x_j - lb_j, x_j == x'_j + lb_j, a'_j == a_j, a^_j := a~_j, if lb was used in transformation
3918 * x'_j := ub_j - x_j, x_j == ub_j - x'_j, a'_j == -a_j, a^_j := -a~_j, if ub was used in transformation
3925 * x'_j := x_j - (bl_j * zl_j + dl_j), x_j == x'_j + (bl_j * zl_j + dl_j), a'_j == a_j, a^_j := a~_j, (vlb)
3926 * x'_j := (bu_j * zu_j + du_j) - x_j, x_j == (bu_j * zu_j + du_j) - x'_j, a'_j == -a_j, a^_j := -a~_j, (vub)
3954 SCIP_CALL( cutsRoundMIR(scip, tmpcoefs, QUAD(&rhs), tmpinds, &tmpnnz, varsign, boundtype, QUAD(f0)) );
3960 * The coefficient of the slack variable s_r is equal to the row's weight times the slack's sign, because the slack
3964 * Depending on the slacks type (integral or continuous), its coefficient in the cut calculates as follows:
3978 /* remove all nearly-zero coefficients from MIR row and relax the right hand side correspondingly in order to
3981 SCIP_CALL( postprocessCutQuad(scip, tmpislocal, tmpinds, tmpcoefs, &tmpnnz, QUAD(&rhs), success) );
3985 *success = ! removeZerosQuad(scip, SCIPsumepsilon(scip), tmpislocal, tmpcoefs, QUAD(&rhs), tmpinds, &tmpnnz);
3992 SCIP_Real mirefficacy = calcEfficacyDenseStorageQuad(scip, sol, tmpcoefs, QUAD_TO_DBL(rhs), tmpinds, tmpnnz);
3994 if( SCIPisEfficacious(scip, mirefficacy) && (cutefficacy == NULL || mirefficacy > *cutefficacy) )
4119 * Given the aggregation, it is transformed to a mixed knapsack set via complementation (using bounds or variable bounds)
4122 * so one would prefer to have integer coefficients for integer variables which are far away from their bounds in the
4125 * @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
4137 SCIP_Real boundswitch, /**< fraction of domain up to which lower bound is used in transformation */
4139 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
4141 int* boundsfortrans, /**< bounds that should be used for transformed variables: vlb_idx/vub_idx,
4144 SCIP_BOUNDTYPE* boundtypesfortrans, /**< type of bounds that should be used for transformed variables;
4151 int* cutinds, /**< array to store the problem indices of variables with a non-zero coefficient in the cut */
4153 SCIP_Real* cutefficacy, /**< pointer to store efficacy of best cut; only cuts that are strictly better than the value of
4156 SCIP_Bool* cutislocal, /**< pointer to store whether the generated cut is only valid locally */
4205 /* we only compute bound distance for integer variables; we allocate an array of length aggrrow->nnz to store this, since
4206 * this is the largest number of integer variables. (in contrast to the number of total variables which can be 2 *
4207 * aggrrow->nnz variables: if all are continuous and we use variable bounds to completement, we introduce aggrrow->nnz
4239 * x'_j := x_j - (bl_j * zl_j + dl_j), x_j == x'_j + (bl_j * zl_j + dl_j), a'_j == a_j, if vlb is used in transf.
4240 * x'_j := (bu_j * zu_j + du_j) - x_j, x_j == (bu_j * zu_j + du_j) - x'_j, a'_j == -a_j, if vub is used in transf.
4241 * move the constant terms "a_j * dl_j" or "a_j * du_j" to the rhs, and update the coefficient of the VLB variable:
4246 boundsfortrans, boundtypesfortrans, minfrac, maxfrac, mksetcoefs, QUAD(&mksetrhs), mksetinds, &mksetnnz, varsign, boundtype, &freevariable, &localbdsused) );
4254 SCIPdebug( printCutQuad(scip, sol, mksetcoefs, QUAD(mksetrhs), mksetinds, mksetnnz, FALSE, FALSE) );
4292 SCIP_CALL( SCIPcalcIntegralScalar(deltacands, nbounddist, -QUAD_EPSILON, SCIPsumepsilon(scip), (SCIP_Longint)10000, 10000.0, &intscale, &intscalesuccess) );
4362 * x'_j := x_j - lb_j, x_j == x'_j + lb_j, a'_j == a_j, a^_j := a~_j, if lb was used in transformation
4363 * x'_j := ub_j - x_j, x_j == ub_j - x'_j, a'_j == -a_j, a^_j := -a~_j, if ub was used in transformation
4370 * x'_j := x_j - (bl_j * zl_j + dl_j), x_j == x'_j + (bl_j * zl_j + dl_j), a'_j == a_j, a^_j := a~_j, (vlb)
4371 * x'_j := (bu_j * zu_j + du_j) - x_j, x_j == (bu_j * zu_j + du_j) - x'_j, a'_j == -a_j, a^_j := -a~_j, (vub)
4563 efficacy = computeMIREfficacy(scip, tmpcoefs, tmpvalues, QUAD_TO_DBL(mksetrhs), contactivity, contsqrnorm, deltacands[i], ntmpcoefs, minfrac, maxfrac);
4586 efficacy = computeMIREfficacy(scip, tmpcoefs, tmpvalues, QUAD_TO_DBL(mksetrhs), contactivity, contsqrnorm, delta, ntmpcoefs, minfrac, maxfrac);
4596 /* try to improve efficacy by switching complementation of integral variables that are not at their bounds
4613 SCIP_CALL( findBestLb(scip, vars[mksetinds[k]], sol, 0, allowlocal, &bestlb, &simplebnd, &bestlbtype) );
4618 SCIP_CALL( findBestUb(scip, vars[mksetinds[k]], sol, 0, allowlocal, &bestub, &simplebnd, &bestubtype) );
4637 tmpvalues[k - intstart] = varsign[k] == +1 ? bestub - SCIPgetSolVal(scip, sol, vars[mksetinds[k]]) : SCIPgetSolVal(scip, sol, vars[mksetinds[k]]) - bestlb;
4640 newefficacy = computeMIREfficacy(scip, tmpcoefs, tmpvalues, QUAD_TO_DBL(newrhs), contactivity, contsqrnorm, bestdelta, ntmpcoefs, minfrac, maxfrac);
4652 assert(bestubtype < 0); /* cannot switch to a variable bound (would lead to further coef updates) */
4659 assert(bestlbtype < 0); /* cannot switch to a variable bound (would lead to further coef updates) */
4699 SCIPdebug(printCutQuad(scip, sol, mksetcoefs, QUAD(mksetrhs), mksetinds, mksetnnz, FALSE, FALSE));
4703 SCIP_CALL( cutsRoundMIR(scip, mksetcoefs, QUAD(&mksetrhs), mksetinds, &mksetnnz, varsign, boundtype, QUAD(f0)) );
4706 SCIPdebug(printCutQuad(scip, sol, mksetcoefs, QUAD(mksetrhs), mksetinds, mksetnnz, FALSE, FALSE));
4710 * The coefficient of the slack variable s_r is equal to the row's weight times the slack's sign, because the slack
4714 * Depending on the slacks type (integral or continuous), its coefficient in the cut calculates as follows:
4726 SCIPdebug(printCutQuad(scip, sol, mksetcoefs, QUAD(mksetrhs), mksetinds, mksetnnz, FALSE, FALSE));
4740 SCIPdebugMessage("efficacy of cmir cut is different than expected efficacy: %f != %f\n", efficacy, bestefficacy);
4747 /* remove all nearly-zero coefficients from MIR row and relax the right hand side correspondingly in order to
4752 SCIP_CALL( postprocessCutQuad(scip, *cutislocal, mksetinds, mksetcoefs, &mksetnnz, QUAD(&mksetrhs), success) );
4756 *success = ! removeZerosQuad(scip, SCIPsumepsilon(scip), *cutislocal, mksetcoefs, QUAD(&mksetrhs), mksetinds, &mksetnnz);
4760 SCIPdebug(printCutQuad(scip, sol, mksetcoefs, QUAD(mksetrhs), mksetinds, mksetnnz, FALSE, FALSE));
4764 mirefficacy = calcEfficacyDenseStorageQuad(scip, sol, mksetcoefs, QUAD_TO_DBL(mksetrhs), mksetinds, mksetnnz);
4819 /* =========================================== flow cover =========================================== */
4831 #define MAXABSVBCOEF 1e+5 /**< maximal absolute coefficient in variable bounds used for snf relaxation */
4848 SCIP_Real d1; /**< right hand side of single-node-flow set plus the sum of all \f$ u_j \f$ for \f$ j \in C^- \f$ */
4849 SCIP_Real d2; /**< right hand side of single-node-flow set plus the sum of all \f$ u_j \f$ for \f$ j \in N^- \f$ */
4851 SCIP_Real mp; /**< smallest variable bound coefficient of variable in \f$ C^{++} (min_{j \in C++} u_j) \f$ */
4855 /** structure that contains all the data that defines the single-node-flow relaxation of an aggregation row */
4867 SCIP_Real* aggrcoefsbin; /**< aggregation coefficient of the original binary var used to define the
4869 SCIP_Real* aggrcoefscont; /**< aggregation coefficient of the original continuous var used to define the
4871 SCIP_Real* aggrconstants; /**< aggregation constant used to define the continuous variable in the relaxed set */
4874 /** get solution value and index of variable lower bound (with binary variable) which is closest to the current LP
4875 * solution value of a given variable; candidates have to meet certain criteria in order to ensure the nonnegativity
4876 * of the variable upper bound imposed on the real variable in the 0-1 single node flow relaxation associated with the
4890 SCIP_Real* closestvlb, /**< pointer to store the LP sol value of the closest variable lower bound */
4891 int* closestvlbidx /**< pointer to store the index of the closest vlb; -1 if no vlb was found */
4899 assert(bestsub == SCIPvarGetUbGlobal(var) || bestsub == SCIPvarGetUbLocal(var)); /*lint !e777*/
4944 /* if the variable is not active the problem index is -1, so we cast to unsigned int before the comparison which
4952 /* check if current variable lower bound l~_i * x_i + d_i imposed on y_j meets the following criteria:
4956 * 0. no other non-binary variable y_k has used a variable bound with x_i to get transformed variable y'_k yet
5004 /** get LP solution value and index of variable upper bound (with binary variable) which is closest to the current LP
5005 * solution value of a given variable; candidates have to meet certain criteria in order to ensure the nonnegativity
5006 * of the variable upper bound imposed on the real variable in the 0-1 single node flow relaxation associated with the
5020 SCIP_Real* closestvub, /**< pointer to store the LP sol value of the closest variable upper bound */
5021 int* closestvubidx /**< pointer to store the index of the closest vub; -1 if no vub was found */
5029 assert(bestslb == SCIPvarGetLbGlobal(var) || bestslb == SCIPvarGetLbLocal(var)); /*lint !e777*/
5074 /* if the variable is not active the problem index is -1, so we cast to unsigned int before the comparison which
5086 * 0. no other non-binary variable y_k has used a variable bound with x_i to get transformed variable y'_k
5134 /** determines the bounds to use for constructing the single-node-flow relaxation of a variable in
5144 int varposinrow, /**< position of variable in the rowinds array for which the bounds should be determined */
5148 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
5149 SCIP_Real boundswitch, /**< fraction of domain up to which lower bound is used in transformation */
5158 SCIP_BOUNDTYPE* selectedbounds, /**< pointer to store the preferred bound for the transformation */
5186 SCIP_CALL( findBestLb(scip, var, sol, 0, allowlocal, &bestslb[varposinrow], &simplebound, &bestslbtype[varposinrow]) );
5187 SCIP_CALL( findBestUb(scip, var, sol, 0, allowlocal, &bestsub[varposinrow], &simplebound, &bestsubtype[varposinrow]) );
5198 SCIPdebugMsg(scip, " %d: %g <%s, idx=%d, lp=%g, [%g(%d),%g(%d)]>:\n", varposinrow, rowcoef, SCIPvarGetName(var), probidx,
5199 solval, bestslb[varposinrow], bestslbtype[varposinrow], bestsub[varposinrow], bestsubtype[varposinrow]);
5201 /* mixed integer set cannot be relaxed to 0-1 single node flow set because both simple bounds are -infinity
5204 if( SCIPisInfinity(scip, -bestslb[varposinrow]) && SCIPisInfinity(scip, bestsub[varposinrow]) )
5210 /* get closest lower bound that can be used to define the real variable y'_j in the 0-1 single node flow
5223 SCIP_CALL( getClosestVlb(scip, var, sol, rowcoefs, binvarused, bestsub[varposinrow], rowcoef, &bestvlb, &bestvlbidx) );
5232 /* get closest upper bound that can be used to define the real variable y'_j in the 0-1 single node flow
5245 SCIP_CALL( getClosestVub(scip, var, sol, rowcoefs, binvarused, bestslb[varposinrow], rowcoef, &bestvub, &bestvubidx) );
5253 SCIPdebugMsg(scip, " bestlb=%g(%d), bestub=%g(%d)\n", bestlb[varposinrow], bestlbtype[varposinrow], bestub[varposinrow], bestubtype[varposinrow]);
5255 /* mixed integer set cannot be relaxed to 0-1 single node flow set because there are no suitable bounds
5266 /* select best upper bound if it is closer to the LP value of y_j and best lower bound otherwise and use this bound
5267 * to define the real variable y'_j with 0 <= y'_j <= u'_j x_j in the 0-1 single node flow relaxation;
5270 if( SCIPisEQ(scip, solval, (1.0 - boundswitch) * bestlb[varposinrow] + boundswitch * bestub[varposinrow]) && bestlbtype[varposinrow] >= 0 )
5274 else if( SCIPisEQ(scip, solval, (1.0 - boundswitch) * bestlb[varposinrow] + boundswitch * bestub[varposinrow])
5279 else if( SCIPisLE(scip, solval, (1.0 - boundswitch) * bestlb[varposinrow] + boundswitch * bestub[varposinrow]) )
5285 assert(SCIPisGT(scip, solval, (1.0 - boundswitch) * bestlb[varposinrow] + boundswitch * bestub[varposinrow]));
5315 /** construct a 0-1 single node flow relaxation (with some additional simple constraints) of a mixed integer set
5322 SCIP_Real boundswitch, /**< fraction of domain up to which lower bound is used in transformation */
5323 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
5330 SCIP_Bool* localbdsused /**< pointer to store whether local bounds were used in transformation */
5353 SCIPdebugMsg(scip, "--------------------- construction of SNF relaxation ------------------------------------\n");
5371 /* array to store whether a binary variable is in the row (-1) or has been used (1) due to variable bound usage */
5385 SCIP_CALL( determineBoundForSNF(scip, sol, vars, rowcoefs, rowinds, i, binvarused, allowlocal, boundswitch,
5386 bestlb, bestub, bestslb, bestsub, bestlbtype, bestubtype, bestslbtype, bestsubtype, selectedbounds, &freevariable) );
5454 /* store for y_j that bestlb is the bound used to define y'_j and that y'_j is the associated real variable
5484 /* store aggregation information for y'_j for transforming cuts for the SNF relaxation back to the problem variables later */
5513 SCIPdebugMsg(scip, " --> bestlb used for trans: ... %s y'_%d + ..., y'_%d <= %g x_%d (=1), rhs=%g-(%g*%g)=%g\n",
5514 snf->transvarcoefs[snf->ntransvars] == 1 ? "+" : "-", snf->ntransvars, snf->ntransvars, snf->transvarvubcoefs[snf->ntransvars],
5515 snf->ntransvars, QUAD_TO_DBL(transrhs) + QUAD_TO_DBL(rowcoeftimesbestsub), QUAD_TO_DBL(rowcoef), bestsub[i], QUAD_TO_DBL(transrhs));
5531 * y'_j = - ( a_j ( y_j - d_j ) + c_j x_j ) with 0 <= y'_j <= - ( a_j l~_j + c_j ) x_j if a_j > 0
5563 /* store aggregation information for y'_j for transforming cuts for the SNF relaxation back to the problem variables later */
5593 SCIPdebugMsg(scip, " --> bestlb used for trans: ... %s y'_%d + ..., y'_%d <= %g x_%d (=%s), rhs=%g-(%g*%g)=%g\n",
5594 snf->transvarcoefs[snf->ntransvars] == 1 ? "+" : "-", snf->ntransvars, snf->ntransvars, snf->transvarvubcoefs[snf->ntransvars],
5595 snf->ntransvars, SCIPvarGetName(vlbvars[bestlbtype[i]]), QUAD_TO_DBL(transrhs) + QUAD_TO_DBL(rowcoeftimesvlbconst), QUAD_TO_DBL(rowcoef),
5638 /* store aggregation information for y'_j for transforming cuts for the SNF relaxation back to the problem variables later */
5667 SCIPdebugMsg(scip, " --> bestub used for trans: ... %s y'_%d + ..., Y'_%d <= %g x_%d (=1), rhs=%g-(%g*%g)=%g\n",
5668 snf->transvarcoefs[snf->ntransvars] == 1 ? "+" : "-", snf->ntransvars, snf->ntransvars, snf->transvarvubcoefs[snf->ntransvars],
5669 snf->ntransvars, QUAD_TO_DBL(transrhs) + QUAD_TO_DBL(rowcoeftimesbestslb), QUAD_TO_DBL(rowcoef), bestslb[i], QUAD_TO_DBL(transrhs));
5686 * y'_j = - ( a_j ( y_j - d_j ) + c_j x_j ) with 0 <= y'_j <= - ( a_j u~_j + c_j ) x_j if a_j < 0,
5715 /* store aggregation information for y'_j for transforming cuts for the SNF relaxation back to the problem variables later */
5745 /* store for x_j that y'_j is the associated real variable in the 0-1 single node flow relaxation */
5747 SCIPdebugMsg(scip, " --> bestub used for trans: ... %s y'_%d + ..., y'_%d <= %g x_%d (=%s), rhs=%g-(%g*%g)=%g\n",
5748 snf->transvarcoefs[snf->ntransvars] == 1 ? "+" : "-", snf->ntransvars, snf->ntransvars, snf->transvarvubcoefs[snf->ntransvars],
5749 snf->ntransvars, SCIPvarGetName(vubvars[bestubtype[i]]), QUAD_TO_DBL(transrhs) + QUAD_TO_DBL(rowcoeftimesvubconst), QUAD_TO_DBL(rowcoef),
5793 SCIPdebugMsg(scip, " %d: %g <%s, idx=%d, lp=%g, [%g, %g]>:\n", i, QUAD_TO_DBL(rowcoef), SCIPvarGetName(var), probidx, varsolval,
5806 /* store aggregation information for y'_j for transforming cuts for the SNF relaxation back to the problem variables later */
5834 assert(snf->transvarcoefs[snf->ntransvars] == 1 || snf->transvarcoefs[snf->ntransvars] == - 1 );
5840 SCIPdebugMsg(scip, " --> ... %s y'_%d + ..., y'_%d <= %g x_%d (=%s))\n", snf->transvarcoefs[snf->ntransvars] == 1 ? "+" : "-", snf->ntransvars, snf->ntransvars,
5914 /** solve knapsack problem in maximization form with "<" constraint approximately by greedy; if needed, one can provide
5954 /* allocate memory for temporary array used for sorting; array should contain profits divided by corresponding weights (p_1 / w_1 ... p_n / w_n )*/
5965 SCIPselectWeightedDownRealRealInt(tempsort, profits, items, weights, mediancapacity, nitems, &criticalitem);
6009 /** build the flow cover which corresponds to the given exact or approximate solution of KP^SNF; given unfinished
6024 int* flowcoverstatus, /**< pointer to store whether variable is in flow cover (+1) or not (-1) */
6088 /** checks, whether the given scalar scales the given value to an integral number with error in the given bounds */
6093 SCIP_Real mindelta, /**< minimal relative allowed difference of scaled coefficient s*c and integral i */
6094 SCIP_Real maxdelta /**< maximal relative allowed difference of scaled coefficient s*c and integral i */
6111 /** get integral number with error in the bounds which corresponds to given value scaled by a given scalar;
6118 SCIP_Real mindelta, /**< minimal relative allowed difference of scaled coefficient s*c and integral i */
6119 SCIP_Real maxdelta /**< maximal relative allowed difference of scaled coefficient s*c and integral i */
6142 * i.e., get sets C1 subset N1 and C2 subset N2 with sum_{j in C1} u_j - sum_{j in C2} u_j = b + lambda and lambda > 0
6150 int* flowcoverstatus, /**< pointer to store whether variable is in flow cover (+1) or not (-1) */
6194 SCIPdebugMsg(scip, "--------------------- get flow cover ----------------------------------------------------\n");
6234 assert(SCIPisFeasGE(scip, snf->transbinvarsolvals[j], 0.0) && SCIPisFeasLE(scip, snf->transbinvarsolvals[j], 1.0));
6299 * 1. to a knapsack problem in maximization form, such that all variables in the knapsack constraint have
6300 * positive weights and the constraint is a "<" constraint, by complementing all variables in N1
6308 * 2. to a knapsack problem in maximization form, such that all variables in the knapsack constraint have
6309 * positive integer weights and the constraint is a "<=" constraint, by complementing all variables in N1
6323 /* get weight and profit of variables in KP^SNF_rat and check, whether all weights are already integral */
6335 SCIPdebugMsg(scip, " <%d>: j in N1: w_%d = %g, p_%d = %g %s\n", items[j], items[j], transweightsreal[j],
6336 items[j], transprofitsreal[j], SCIPisIntegral(scip, transweightsreal[j]) ? "" : " ----> NOT integral");
6341 SCIPdebugMsg(scip, " <%d>: j in N2: w_%d = %g, p_%d = %g %s\n", items[j], items[j], transweightsreal[j],
6342 items[j], transprofitsreal[j], SCIPisIntegral(scip, transweightsreal[j]) ? "" : " ----> NOT integral");
6347 SCIPdebugMsg(scip, " transcapacity = -rhs(%g) + flowcoverweight(%g) + n1itemsweight(%g) = %g\n",
6350 /* there exists no flow cover if the capacity of knapsack constraint in KP^SNF_rat after fixing
6371 * solve KP^SNF_int exactly, if a suitable factor C is found and (nitems*capacity) <= MAXDYNPROGSPACE,
6385 SCIP_CALL( SCIPcalcIntegralScalar(transweightsreal, nitems, -MINDELTA, MAXDELTA, MAXDNOM, MAXSCALE, &scalar,
6389 /* initialize number of (non-)solution items, should be changed to a nonnegative number in all possible paths below */
6424 SCIP_CALL(SCIPsolveKnapsackExactly(scip, nitems, transweightsint, transprofitsint, transcapacityint,
6441 SCIP_CALL(SCIPsolveKnapsackApproximatelyLT(scip, nitems, transweightsreal, transprofitsreal, transcapacityreal,
6449 SCIP_CALL(SCIPsolveKnapsackApproximatelyLT(scip, nitems, transweightsreal, transprofitsreal, transcapacityreal,
6457 /* build the flow cover from the solution of KP^SNF_rat and KP^SNF_int, respectively and the fixing */
6459 buildFlowCover(scip, snf->transvarcoefs, snf->transvarvubcoefs, snf->transrhs, solitems, nonsolitems, nsolitems, nnonsolitems, nflowcovervars,
6463 /* if the found structure is not a flow cover, because of scaling, solve KP^SNF_rat approximately */
6469 SCIP_CALL(SCIPsolveKnapsackApproximatelyLT(scip, nitems, transweightsreal, transprofitsreal, transcapacityreal,
6471 #ifdef SCIP_DEBUG /* this time only for SCIP_DEBUG, because only then, the variable is used again */
6481 buildFlowCover(scip, snf->transvarcoefs, snf->transvarvubcoefs, snf->transrhs, solitems, nonsolitems, nsolitems, nnonsolitems, nflowcovervars,
6504 SCIPdebugMsg(scip, " flowcoverweight(%g) = rhs(%g) + lambda(%g)\n", QUAD_TO_DBL(flowcoverweight), snf->transrhs, *lambda);
6524 * \f${(x,y) in {0,1}^n x R^n : sum_{j in N1} y_j - sum_{j in N2} y_j <= b, 0 <= y_j <= u_j x_j}\f$,
6534 int* flowcoverstatus, /**< pointer to store whether variable is in flow cover (+1) or not (-1) */
6567 SCIPdebugMsg(scip, "--------------------- get flow cover ----------------------------------------------------\n");
6600 assert(SCIPisFeasGE(scip, snf->transbinvarsolvals[j], 0.0) && SCIPisFeasLE(scip, snf->transbinvarsolvals[j], 1.0));
6665 * 1. to a knapsack problem in maximization form, such that all variables in the knapsack constraint have
6666 * positive weights and the constraint is a "<" constraint, by complementing all variables in N1
6674 * 2. to a knapsack problem in maximization form, such that all variables in the knapsack constraint have
6675 * positive integer weights and the constraint is a "<=" constraint, by complementing all variables in N1
6689 /* get weight and profit of variables in KP^SNF_rat and check, whether all weights are already integral */
6697 SCIPdebugMsg(scip, " <%d>: j in N1: w_%d = %g, p_%d = %g %s\n", items[j], items[j], transweightsreal[j],
6698 items[j], transprofitsreal[j], SCIPisIntegral(scip, transweightsreal[j]) ? "" : " ----> NOT integral");
6703 SCIPdebugMsg(scip, " <%d>: j in N2: w_%d = %g, p_%d = %g %s\n", items[j], items[j], transweightsreal[j],
6704 items[j], transprofitsreal[j], SCIPisIntegral(scip, transweightsreal[j]) ? "" : " ----> NOT integral");
6708 transcapacityreal = - snf->transrhs + QUAD_TO_DBL(flowcoverweight) + n1itemsweight; /*lint !e644*/
6709 SCIPdebugMsg(scip, " transcapacity = -rhs(%g) + flowcoverweight(%g) + n1itemsweight(%g) = %g\n",
6712 /* there exists no flow cover if the capacity of knapsack constraint in KP^SNF_rat after fixing
6734 /* initialize number of (non-)solution items, should be changed to a nonnegative number in all possible paths below */
6740 SCIP_CALL(SCIPsolveKnapsackApproximatelyLT(scip, nitems, transweightsreal, transprofitsreal, transcapacityreal,
6746 /* build the flow cover from the solution of KP^SNF_rat and KP^SNF_int, respectively and the fixing */
6748 buildFlowCover(scip, snf->transvarcoefs, snf->transvarvubcoefs, snf->transrhs, solitems, nonsolitems, nsolitems, nnonsolitems, nflowcovervars,
6771 SCIPdebugMsg(scip, " flowcoverweight(%g) = rhs(%g) + lambda(%g)\n", QUAD_TO_DBL(flowcoverweight), snf->transrhs, *lambda);
6789 /** evaluate the super-additive lifting function for the lifted simple generalized flowcover inequalities
6917 int* transvarflowcoverstatus, /**< pointer to store whether non-binary var is in L2 (2) or not (-1 or 1) */
7027 SCIP_UNUSED( SCIPsortedvecFindDownReal(liftingdata->m, liftingdata->mp, liftingdata->r, &liftingdata->t) );
7028 assert(liftingdata->m[liftingdata->t] == liftingdata->mp || SCIPisInfinity(scip, liftingdata->mp)); /*lint !e777*/
7034 while( liftingdata->t < liftingdata->r && liftingdata->m[liftingdata->t] == liftingdata->mp ) /*lint !e777*/
7061 int* flowcoverstatus, /**< pointer to store whether variable is in flow cover (+1) or not (-1) */
7139 SCIP_Real liftedbincoef = evaluateLiftingFunction(scip, &liftingdata, snf->transvarvubcoefs[i]);
7322 /** calculates a lifted simple generalized flow cover cut out of the weighted sum of LP rows given by an aggregation row; the
7323 * aggregation row must not contain non-zero weights for modifiable rows, because these rows cannot
7327 * Gu, Z., Nemhauser, G. L., & Savelsbergh, M. W. (1999). Lifted flow cover inequalities for mixed 0-1 integer programs.
7330 * @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
7342 SCIP_Real boundswitch, /**< fraction of domain up to which lower bound is used in transformation */
7343 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
7347 int* cutinds, /**< array to store the problem indices of variables with a non-zero coefficient in the cut */
7351 SCIP_Bool* cutislocal, /**< pointer to store whether the generated cut is only valid locally */
7373 SCIPdebug( printCutQuad(scip, sol, aggrrow->vals, QUAD(aggrrow->rhs), aggrrow->inds, aggrrow->nnz, FALSE, aggrrow->local) );
7375 SCIP_CALL( constructSNFRelaxation(scip, sol, boundswitch, allowlocal, aggrrow->vals, QUAD(aggrrow->rhs), aggrrow->inds, aggrrow->nnz, &snf, success, &localbdsused) );
7386 SCIP_CALL( getFlowCover(scip, &snf, &nflowcovervars, &nnonflowcovervars, transvarflowcoverstatus, &lambda, success) );
7395 SCIP_CALL( generateLiftedFlowCoverCut(scip, &snf, aggrrow, transvarflowcoverstatus, lambda, tmpcoefs, cutrhs, cutinds, cutnnz, success) );
7398 /* if success is FALSE generateLiftedFlowCoverCut wont have touched the tmpcoefs array so we dont need to clean it then */
7410 *success = ! removeZeros(scip, SCIPsumepsilon(scip), *cutislocal, tmpcoefs, QUAD(&rhs), cutinds, cutnnz);
7452 /* =========================================== knapsack cover =========================================== */
7454 /** Relax the row to a possibly fractional knapsack row containing no integer or continuous variables
7455 * and only having positive coefficients for binary variables. General integer and continuous variables
7456 * are complemented with variable or simple bounds such that their coefficient becomes positive and then
7458 * All remaining binary variables are complemented with simple upper or lower bounds such that their
7465 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
7473 SCIP_Bool* localbdsused, /**< pointer to store whether local bounds were used in transformation */
7474 SCIP_Bool* success /**< stores whether the row could successfully be transformed into a knapsack constraint.
7495 /* start with continuous variables, because using variable bounds can affect the untransformed binary
7496 * variables, and these changes have to be incorporated in the transformation of the binary variables
7504 /* determine best bounds for the continuous and general integer variables such that they will have
7517 /* find closest lower bound in standard lower bound or variable lower bound for continuous variable
7519 SCIP_CALL( findBestLb(scip, vars[v], sol, 1, allowlocal, bestbds + i, &simplebound, boundtype + i) );
7531 /* find closest upper bound in standard upper bound or variable upper bound for continuous variable
7533 SCIP_CALL( findBestUb(scip, vars[v], sol, 1, allowlocal, bestbds + i, &simplebound, boundtype + i) );
7552 performBoundSubstitution(scip, cutinds, cutcoefs, QUAD(cutrhs), nnz, varsign[i], boundtype[i], bestbds[i], v, localbdsused);
7561 /* remove non-binary variables because their coefficients have been set to zero after bound substitution */
7569 /* after doing bound substitution of non-binary vars, some coefficients of binary vars might have changed, so here we
7570 * remove the ones that became 0 if any; also, we need that all remaining binary vars have positive coefficients,
7587 /* due to variable bound usage for bound substitution of continuous variables cancellation may have occurred */
7598 SCIP_CALL( findBestUb(scip, vars[v], sol, 0, allowlocal, &bestub, &simplebound, boundtype + i) );
7610 performBoundSubstitutionSimple(scip, cutcoefs, QUAD(cutrhs), boundtype[i], bestub, v, localbdsused);
7617 SCIP_CALL( findBestLb(scip, vars[v], sol, 0, allowlocal, &bestlb, &simplebound, boundtype + i) );
7622 performBoundSubstitutionSimple(scip, cutcoefs, QUAD(cutrhs), boundtype[i], bestlb, v, localbdsused);
7635 /* increase i or remove zero coefficient (i.e. var with 0 coef) by shifting last nonzero to current position */
7665 int* cutinds, /**< array of the problem indices of variables with a non-zero coefficient in the cut */
7669 int* coverstatus, /**< array to return the coverstatus for each variable in the knapsack row */
7744 SCIPdebugMessage("coverweight is %g and right hand side is %g\n", QUAD_TO_DBL(*coverweight), cutrhs);
7755 int* cutinds, /**< array of the problem indices of variables with a non-zero coefficient in the cut */
7823 /* now we partition C into C^+ and C^-, where C^+ are all the elements of C whose weight is strictly larger than
7824 * \bar{a} and C^- the rest. If a_i are the weights of the elements in C, let a_i^- = min(a_i, \bar{a}) We also
7825 * compute S^-(h) = sum of the h largest a_i^- and store S^-(h+1) in in covervals[h], for k = 0, ..., coversize - 1
7827 * we remember which elements of C^- in coverstatus, so that element in C^+ have coverstatus 1 and
7841 /* coefficient is in C^+ because it is greater than \bar{a} and contributes only \bar{a} to the sum */
7844 /* rather be on the safe side in numerical corner cases and relax the coefficient to exactly \bar{a}.
7845 * In that case the coefficient is not treated as in C^+ but as being <= \bar{a} and therefore in C^-.
7874 SCIP_Real* scale /**< pointer to update the scale to integrality when a fractional value is returned */
7883 /* the lifted value is at least the coeficient (a_k) divided by \bar{a} because the largest value
7892 /* if the coefficient is below \bar{a}, i.e. a / \bar{a} < 1 then g(a_k) = 0, otherwise g(a_k) > 0 */
7896 /* we perform h = MIN(h, coversize) in floating-point first because on some instances h was seen to exceed the range
7918 /* decrease by one to make sure rounding errors or coefficients that are larger than the right hand side by themselves
7924 * (todo: variables that have a coefficient above the right hand side can get an arbitrarily large coefficient but can
7925 * also be trivially fixed using the base row. Currently they get the coefficient |C| which is 1 above the right hand
7926 * side in the cover cut so that they can still be trivially fixed by propagating the cover cut.
7927 * We do not want to apply fixings here though because the LP should stay flushed during separation.
7928 * Possibly add a parameter to return additional fixings to the caller of the SCIPcalc*() functions in here
7942 SCIPdebugMessage("lifted coef %g < %g <= %g to %g\n", h == 0 ? 0 : covervals[h-1], QUAD_TO_DBL(x),
7948 /** calculates a lifted knapsack cover cut out of the weighted sum of LP rows given by an aggregation row; the
7949 * aggregation row must not contain non-zero weights for modifiable rows, because these rows cannot
7953 * Letchford, A. N., & Souli, G. (2019). On lifted cover inequalities: A new lifting procedure with unusual properties.
7956 * @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
7967 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
7971 int* cutinds, /**< array to store the problem indices of variables with a non-zero coefficient in the cut */
7975 SCIP_Bool* cutislocal, /**< pointer to store whether the generated cut is only valid locally */
8052 /* Transform aggregated row into a (fractional, i.e. with possibly fractional weights) knapsack constraint.
8054 * so that only binary variables remain and complements those such that they have a positive coefficient.
8068 if( !computeInitialKnapsackCover(scip, sol, tmpcoefs, tmpinds, QUAD_TO_DBL(rhs), nnz, varsign, coverstatus,
8072 SCIPdebugMessage("coverweight is %g and right hand side is %g\n", QUAD_TO_DBL(coverweight), QUAD_TO_DBL(rhs));
8118 * - h + 1/2 if z = k * \bar{a} for some integer k \in [1, |C^+| - 1] and S^-(h) < z <= S^-(h+1) for some h = 0, ..., coversize -1
8138 { /* variables is either in C^+ or not in the cover and its coefficient value is computed with the lifing function */
8142 cutcoef = evaluateLiftingFunctionKnapsack(QUAD(coef), QUAD(abar), covervals, coversize, cplussize, &scale);
8160 /* variable was complemented so we have cutcoef * (1-x) = cutcoef - cutcoef * x.Thus we need to adjust the rhs
8173 /* calculate the efficacy of the computed cut and store the success flag if the efficacy exceeds the
8205 /* calculate efficacy again to make sure it matches the coefficients after they where rounded to double values
8250 /* =========================================== strongcg =========================================== */
8255 * Differs from cutsTransformMIR for continuous variables for which the lower bound must be used
8257 * negative. This forces all continuous variable to have a positive coefficient in the transformed
8263 * x^\prime_j := x_j - lb_j,& x_j = x^\prime_j + lb_j,& a^\prime_j = a_j,& \mbox{if lb is used in transformation}\\
8264 * x^\prime_j := ub_j - x_j,& x_j = ub_j - x^\prime_j,& a^\prime_j = -a_j,& \mbox{if ub is used in transformation}
8272 * x^\prime_j := x_j - (bl_j\, zl_j + dl_j),& x_j = x^\prime_j + (bl_j\, zl_j + dl_j),& a^\prime_j = a_j,& \mbox{if vlb is used in transf.} \\
8273 * x^\prime_j := (bu_j\, zu_j + du_j) - x_j,& x_j = (bu_j\, zu_j + du_j) - x^\prime_j,& a^\prime_j = -a_j,& \mbox{if vub is used in transf.}
8276 * move the constant terms \f$ a_j\, dl_j \f$ or \f$ a_j\, du_j \f$ to the rhs, and update the coefficient of the VLB variable:
8288 SCIP_Real boundswitch, /**< fraction of domain up to which lower bound is used in transformation */
8290 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
8298 SCIP_Bool* freevariable, /**< stores whether a free variable was found in MIR row -> invalid summation */
8299 SCIP_Bool* localbdsused /**< pointer to store whether local bounds were used in transformation */
8320 /* start with continuous variables, because using variable bounds can affect the untransformed integral
8321 * variables, and these changes have to be incorporated in the transformation of the integral variables
8330 /* determine best bounds for the continuous variables such that they will have a positive coefficient in the transformation */
8342 /* find closest lower bound in standard lower bound or variable lower bound for continuous variable so that it will have a positive coefficient */
8343 SCIP_CALL( findBestLb(scip, vars[v], sol, usevbds ? 2 : 0, allowlocal, bestbds + i, &simplebound, boundtype + i) );
8358 /* find closest upper bound in standard upper bound or variable upper bound for continuous variable so that it will have a positive coefficient */
8359 SCIP_CALL( findBestUb(scip, vars[v], sol, usevbds ? 2 : 0, allowlocal, bestbds + i, &simplebound, boundtype + i) );
8378 performBoundSubstitution(scip, cutinds, cutcoefs, QUAD(cutrhs), nnz, varsign[i], boundtype[i], bestbds[i], cutinds[i], localbdsused);
8383 /* remove integral variables that now have a zero coefficient due to variable bound usage of continuous variables
8384 * and perform the bound substitution for the integer variables that are left using simple bounds
8411 /* determine the best bounds for the integral variable, usevbd can be set to 0 here as vbds are only used for continuous variables */
8412 SCIP_CALL( determineBestBounds(scip, vars[v], sol, boundswitch, 0, allowlocal, FALSE, FALSE, NULL, NULL,
8427 performBoundSubstitutionSimple(scip, cutcoefs, QUAD(cutrhs), boundtype[i], bestlb, v, localbdsused);
8435 performBoundSubstitutionSimple(scip, cutcoefs, QUAD(cutrhs), boundtype[i], bestub, v, localbdsused);
8455 /** Calculate fractionalities \f$ f_0 := b - down(b) \f$, \f$ f_j := a^\prime_j - down(a^\prime_j) \f$,
8456 * integer \f$ k \geq 1 \f$ with \f$ 1/(k + 1) \leq f_0 < 1/k \f$ \f$ (\Rightarrow k = up(1/f_0) - 1) \f$ and
8457 * integer \f$ 1 \leq p_j \leq k \f$ with \f$ f_0 + ((p_j - 1) \cdot (1 - f_0)/k) < f_j \leq f_0 + (p_j (1 - f_0)/k)\f$ \f$ (\Rightarrow p_j = up( k\,(f_j - f_0)/(1 - f_0) )) \f$
8473 * x^\prime_j := x_j - lb_j,& x_j == x^\prime_j + lb_j,& a^\prime_j == a_j,& \hat{a}_j := \tilde{a}_j,& \mbox{if lb was used in transformation} \\
8474 * x^\prime_j := ub_j - x_j,& x_j == ub_j - x^\prime_j,& a^\prime_j == -a_j,& \hat{a}_j := -\tilde{a}_j,& \mbox{if ub was used in transformation}
8489 * x^\prime_j := x_j - (bl_j * zl_j + dl_j),& x_j == x^\prime_j + (bl_j * zl_j + dl_j),& a^\prime_j == a_j,& \hat{a}_j := \tilde{a}_j,& \mbox{(vlb)} \\
8490 * x^\prime_j := (bu_j * zu_j + du_j) - x_j,& x_j == (bu_j * zu_j + du_j) - x^\prime_j,& a^\prime_j == -a_j,& \hat{a}_j := -\tilde{a}_j,& \mbox{(vub)}
8503 * \hat{a}_{zl_j} := \hat{a}_{zl_j} - \tilde{a}_j * bl_j == \hat{a}_{zl_j} - \hat{a}_j * bl_j,& \mbox{or} \\
8516 int* boundtype, /**< stores the bound used for transformed variable (vlb/vub_idx or -1 for lb/ub)*/
8538 /* Loop backwards to process integral variables first and be able to delete coefficients of integral variables
8546 /* in debug mode check, that all continuous variables of the aggrrow come before the integral variables */
8599 assert(pj >= 0); /* should be >= 1, but due to rounding bias can be 0 if fj almost equal to f0 */
8622 /* move the constant term -\tilde{a}_j * lb_j == -a_j * lb_j , or \tilde{a}_j * ub_j == -a_j * ub_j to the rhs */
8645 /* now process the continuous variables; postpone deletion of zeros until all continuous variables have been processed */
8649 /* in a strong CG cut, cut coefficients of continuous variables are always zero; check this in debug mode */
8686 /* fill empty positions of the continuous variables by integral variables; copy all indices to the front or only
8704 * The coefficient of the slack variable \f$s_r\f$ is equal to the row's weight times the slack's sign, because the slack
8705 * variable only appears in its own row: \f$ a^\prime_r = scale \cdot weight[r] \cdot slacksign[r] \f$.
8707 * Depending on the slack's type (integral or continuous), its coefficient in the cut calculates as follows:
8717 * Substitute \f$ \hat{a}_r \cdot s_r \f$ by adding \f$ \hat{a}_r \f$ times the slack's definition to the cut.
8794 assert(pr >= 0); /* should be >= 1, but due to rounding bias can be 0 if fr almost equal to f0 */
8863 /** calculates a strong CG cut out of the weighted sum of LP rows given by an aggregation row; the
8864 * aggregation row must not contain non-zero weights for modifiable rows, because these rows cannot
8867 * @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
8879 SCIP_Real boundswitch, /**< fraction of domain up to which lower bound is used in transformation */
8881 SCIP_Bool allowlocal, /**< should local information allowed to be used, resulting in a local cut? */
8888 int* cutinds, /**< array to store the problem indices of variables with a non-zero coefficient in the cut */
8892 SCIP_Bool* cutislocal, /**< pointer to store whether the generated cut is only valid locally */
8922 /* check whether a negative continuous slack variable in a non-integral row is present in the aggregation, since then
8926 if( aggrrow->rowweights[i] * aggrrow->slacksign[i] < 0.0 && !scip->lp->rows[aggrrow->rowsinds[i]]->integral )
8968 * x'_j := x_j - (bl_j * zl_j + dl_j), x_j == x'_j + (bl_j * zl_j + dl_j), a'_j == a_j, if vlb is used in transf.
8969 * x'_j := (bu_j * zu_j + du_j) - x_j, x_j == (bu_j * zu_j + du_j) - x'_j, a'_j == -a_j, if vub is used in transf.
8970 * move the constant terms "a_j * dl_j" or "a_j * du_j" to the rhs, and update the coefficient of the VLB variable:
8990 * - integer 1 <= p_j <= k with f_0 + ((p_j - 1) * (1 - f_0)/k) < f_j <= f_0 + (p_j * (1 - f_0)/k)
9002 * x'_j := x_j - lb_j, x_j == x'_j + lb_j, a'_j == a_j, a^_j := a~_j, if lb was used in transformation
9003 * x'_j := ub_j - x_j, x_j == ub_j - x'_j, a'_j == -a_j, a^_j := -a~_j, if ub was used in transformation
9010 * x'_j := x_j - (bl_j * zl_j + dl_j), x_j == x'_j + (bl_j * zl_j + dl_j), a'_j == a_j, a^_j := a~_j, (vlb)
9011 * x'_j := (bu_j * zu_j + du_j) - x_j, x_j == (bu_j * zu_j + du_j) - x'_j, a'_j == -a_j, a^_j := -a~_j, (vub)
9035 SCIP_CALL( cutsRoundStrongCG(scip, tmpcoefs, QUAD(&rhs), cutinds, cutnnz, varsign, boundtype, QUAD(f0), k) );
9041 * The coefficient of the slack variable s_r is equal to the row's weight times the slack's sign, because the slack
9045 * Depending on the slacks type (integral or continuous), its coefficient in the cut calculates as follows:
9053 SCIP_CALL( cutsSubstituteStrongCG(scip, aggrrow->rowweights, aggrrow->slacksign, aggrrow->rowsinds,
9057 /* remove all nearly-zero coefficients from strong CG row and relax the right hand side correspondingly in order to
9062 SCIP_CALL( postprocessCutQuad(scip, *cutislocal, cutinds, tmpcoefs, cutnnz, QUAD(&rhs), success) );
9066 *success = ! removeZerosQuad(scip, SCIPsumepsilon(scip), *cutislocal, tmpcoefs, QUAD(&rhs), cutinds, cutnnz);
void SCIPsortDownRealRealInt(SCIP_Real *realarray1, SCIP_Real *realarray2, int *intarray, int len)
static SCIP_RETCODE postprocessCutQuad(SCIP *scip, SCIP_Bool cutislocal, int *cutinds, SCIP_Real *cutcoefs, int *nnz, QUAD(SCIP_Real *cutrhs), SCIP_Bool *success)
Definition: cuts.c:2340
#define SCIPreallocBlockMemoryArray(scip, ptr, oldnum, newnum)
Definition: scip_mem.h:99
SCIP_RETCODE SCIPcalcStrongCG(SCIP *scip, SCIP_SOL *sol, SCIP_Bool postprocess, SCIP_Real boundswitch, SCIP_Bool usevbds, SCIP_Bool allowlocal, 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:8875
static SCIP_RETCODE computeLiftingData(SCIP *scip, SNF_RELAXATION *snf, int *transvarflowcoverstatus, SCIP_Real lambda, LIFTINGDATA *liftingdata, SCIP_Bool *valid)
Definition: cuts.c:6914
SCIP_RETCODE SCIPsolveKnapsackExactly(SCIP *scip, int nitems, SCIP_Longint *weights, SCIP_Real *profits, SCIP_Longint capacity, int *items, int *solitems, int *nonsolitems, int *nsolitems, int *nnonsolitems, SCIP_Real *solval, SCIP_Bool *success)
Definition: cons_knapsack.c:1100
SCIP_Bool SCIPisFeasEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:782
SCIP_Bool SCIPisFeasLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:795
Definition: struct_scip.h:68
SCIP_RETCODE SCIPaggrRowAddRow(SCIP *scip, SCIP_AGGRROW *aggrrow, SCIP_ROW *row, SCIP_Real weight, int sidetype)
Definition: cuts.c:1799
static SCIP_RETCODE varVecAddScaledRowCoefsQuad(int *RESTRICT inds, SCIP_Real *RESTRICT vals, int *RESTRICT nnz, SCIP_ROW *row, SCIP_Real scale)
Definition: cuts.c:169
public methods for memory management
static SCIP_RETCODE cutTightenCoefsQuad(SCIP *scip, SCIP_Bool cutislocal, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int *cutinds, int *cutnnz, SCIP_Bool *redundant)
Definition: cuts.c:731
Definition: struct_cuts.h:40
static void performBoundSubstitution(SCIP *scip, int *cutinds, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int *nnz, int varsign, int boundtype, SCIP_Real boundval, int probindex, SCIP_Bool *localbdsused)
Definition: cuts.c:2845
void SCIPaggrRowCancelVarWithBound(SCIP *scip, SCIP_AGGRROW *aggrrow, SCIP_VAR *var, int pos, SCIP_Bool *valid)
Definition: cuts.c:1883
SCIP_Bool SCIPisGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:499
static SCIP_RETCODE SCIPsolveKnapsackApproximatelyLT(SCIP *scip, int nitems, SCIP_Real *weights, SCIP_Real *profits, SCIP_Real capacity, int *items, int *solitems, int *nonsolitems, int *nsolitems, int *nnonsolitems, SCIP_Real *solval)
Definition: cuts.c:5918
Definition: struct_var.h:207
static SCIP_Real computeMIREfficacy(SCIP *scip, SCIP_Real *RESTRICT coefs, SCIP_Real *RESTRICT solvals, SCIP_Real rhs, SCIP_Real contactivity, SCIP_Real contsqrnorm, SCIP_Real delta, int nvars, SCIP_Real minfrac, SCIP_Real maxfrac)
Definition: cuts.c:4051
SCIP_Bool SCIPisFeasGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:834
SCIP_RETCODE SCIPgetVarsData(SCIP *scip, SCIP_VAR ***vars, int *nvars, int *nbinvars, int *nintvars, int *nimplvars, int *ncontvars)
Definition: scip_prob.c:1874
static SCIP_RETCODE generateLiftedFlowCoverCut(SCIP *scip, SNF_RELAXATION *snf, SCIP_AGGRROW *aggrrow, int *flowcoverstatus, SCIP_Real lambda, SCIP_Real *cutcoefs, SCIP_Real *cutrhs, int *cutinds, int *nnz, SCIP_Bool *success)
Definition: cuts.c:7057
struct LiftingData LIFTINGDATA
methods for the aggregation rows
Definition: struct_message.h:45
static SCIP_RETCODE cutsTransformStrongCG(SCIP *scip, SCIP_SOL *sol, SCIP_Real boundswitch, SCIP_Bool usevbds, SCIP_Bool allowlocal, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int *cutinds, int *nnz, int *varsign, int *boundtype, SCIP_Bool *freevariable, SCIP_Bool *localbdsused)
Definition: cuts.c:8285
Definition: type_var.h:62
SCIP_RETCODE SCIPcutGenerationHeuristicCMIR(SCIP *scip, SCIP_SOL *sol, SCIP_Bool postprocess, SCIP_Real boundswitch, SCIP_Bool usevbds, SCIP_Bool allowlocal, int maxtestdelta, int *boundsfortrans, SCIP_BOUNDTYPE *boundtypesfortrans, SCIP_Real minfrac, SCIP_Real maxfrac, 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:4133
static SCIP_RETCODE cutsSubstituteMIR(SCIP *scip, SCIP_Real *weights, int *slacksign, int *rowinds, int nrowinds, SCIP_Real scale, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int *cutinds, int *nnz, QUAD(SCIP_Real f0))
Definition: cuts.c:3647
static SCIP_Real evaluateLiftingFunction(SCIP *scip, LIFTINGDATA *liftingdata, SCIP_Real x)
Definition: cuts.c:6793
public methods for problem variables
static SCIP_RETCODE findBestUb(SCIP *scip, SCIP_VAR *var, SCIP_SOL *sol, int usevbds, SCIP_Bool allowlocal, SCIP_Real *bestub, SCIP_Real *simplebound, int *bestubtype)
Definition: cuts.c:2585
SCIP_RETCODE SCIPcalcKnapsackCover(SCIP *scip, SCIP_SOL *sol, 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:7964
void SCIPsortDownRealInt(SCIP_Real *realarray, int *intarray, int len)
void SCIPaggrRowPrint(SCIP *scip, SCIP_AGGRROW *aggrrow, FILE *file)
Definition: cuts.c:1716
SCIP_Bool SCIPisEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:447
defines macros for basic operations in double-double arithmetic giving roughly twice the precision of...
public methods for SCIP variables
Definition: cuts.c:4856
static void prepareLiftingData(SCIP *scip, SCIP_Real *cutcoefs, int *cutinds, QUAD(SCIP_Real cutrhs), int *coverpos, int coversize, QUAD(SCIP_Real coverweight), SCIP_Real *covervals, int *coverstatus, QUAD(SCIP_Real *abar), int *cplussize)
Definition: cuts.c:7752
internal methods for LP management
SCIP_RETCODE SCIPgetVarClosestVlb(SCIP *scip, SCIP_VAR *var, SCIP_SOL *sol, SCIP_Real *closestvlb, int *closestvlbidx)
Definition: scip_var.c:6615
SCIP_Real SCIPgetRowMaxActivity(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1950
static void getAlphaAndBeta(SCIP *scip, LIFTINGDATA *liftingdata, SCIP_Real vubcoef, int *alpha, SCIP_Real *beta)
Definition: cuts.c:6877
public methods for numerical tolerances
SCIP_Bool SCIPaggrRowHasRowBeenAdded(SCIP_AGGRROW *aggrrow, SCIP_ROW *row)
Definition: cuts.c:2446
static void destroyLiftingData(SCIP *scip, LIFTINGDATA *liftingdata)
Definition: cuts.c:7044
public methods for querying solving statistics
Definition: cuts.c:4836
Definition: struct_sol.h:73
SCIP_RETCODE SCIPaggrRowAddObjectiveFunction(SCIP *scip, SCIP_AGGRROW *aggrrow, SCIP_Real rhs, SCIP_Real scale)
Definition: cuts.c:1942
static SCIP_Real calcEfficacyNormQuad(SCIP *scip, SCIP_Real *vals, int *inds, int nnz)
Definition: cuts.c:275
static SCIP_RETCODE cutTightenCoefs(SCIP *scip, SCIP_Bool cutislocal, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int *cutinds, int *cutnnz, SCIP_Bool *redundant)
Definition: cuts.c:1110
#define SCIPallocCleanBufferArray(scip, ptr, num)
Definition: scip_mem.h:142
static SCIP_Bool removeZerosQuad(SCIP *scip, SCIP_Real minval, SCIP_Bool cutislocal, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int *cutinds, int *cutnnz)
Definition: cuts.c:412
#define SCIPduplicateBlockMemoryArray(scip, ptr, source, num)
Definition: scip_mem.h:105
void SCIPsortDownInd(int *indarray, SCIP_DECL_SORTINDCOMP((*indcomp)), void *dataptr, int len)
static SCIP_RETCODE varVecAddScaledRowCoefs(int *RESTRICT inds, SCIP_Real *RESTRICT vals, int *RESTRICT nnz, SCIP_ROW *row, SCIP_Real scale)
Definition: cuts.c:124
SCIP_Bool SCIPsortedvecFindDownReal(SCIP_Real *realarray, SCIP_Real val, int len, int *pos)
static SCIP_Bool isIntegralScalar(SCIP_Real val, SCIP_Real scalar, SCIP_Real mindelta, SCIP_Real maxdelta, SCIP_Real *intval)
Definition: lp.c:4904
SCIP_Bool SCIPisLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:460
Definition: type_retcode.h:51
Definition: type_lp.h:56
SCIP_Bool SCIPisEfficacious(SCIP *scip, SCIP_Real efficacy)
Definition: scip_cut.c:135
static SCIP_Bool chgCoeffWithBound(SCIP *scip, SCIP_VAR *var, SCIP_Real oldcoeff, SCIP_Real newcoeff, SCIP_Bool cutislocal, QUAD(SCIP_Real *cutrhs))
Definition: cuts.c:639
static SCIP_RETCODE cutsTransformMIR(SCIP *scip, SCIP_SOL *sol, SCIP_Real boundswitch, SCIP_Bool usevbds, SCIP_Bool allowlocal, SCIP_Bool fixintegralrhs, SCIP_Bool ignoresol, int *boundsfortrans, SCIP_BOUNDTYPE *boundtypesfortrans, SCIP_Real minfrac, SCIP_Real maxfrac, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int *cutinds, int *nnz, int *varsign, int *boundtype, SCIP_Bool *freevariable, SCIP_Bool *localbdsused)
Definition: cuts.c:2980
Definition: type_retcode.h:42
void SCIPaggrRowRemoveZeros(SCIP *scip, SCIP_AGGRROW *aggrrow, SCIP_Bool useglbbounds, SCIP_Bool *valid)
Definition: cuts.c:2399
static SCIP_Real evaluateLiftingFunctionKnapsack(QUAD(SCIP_Real x), QUAD(SCIP_Real abar), SCIP_Real *covervals, int coversize, int cplussize, SCIP_Real *scale)
Definition: cuts.c:7868
SCIP main data structure.
SCIP_Bool SCIPisFeasGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:821
SCIP_RETCODE SCIPgetVarClosestVub(SCIP *scip, SCIP_VAR *var, SCIP_SOL *sol, SCIP_Real *closestvub, int *closestvubidx)
Definition: scip_var.c:6638
SCIP_Bool SCIPisFeasLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:808
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:2013
static SCIP_RETCODE getClosestVlb(SCIP *scip, SCIP_VAR *var, SCIP_SOL *sol, SCIP_Real *rowcoefs, int8_t *binvarused, SCIP_Real bestsub, SCIP_Real rowcoef, SCIP_Real *closestvlb, int *closestvlbidx)
Definition: cuts.c:4880
static SCIP_Bool chgQuadCoeffWithBound(SCIP *scip, SCIP_VAR *var, QUAD(SCIP_Real oldcoeff), SCIP_Real newcoeff, SCIP_Bool cutislocal, QUAD(SCIP_Real *cutrhs))
Definition: cuts.c:684
static SCIP_RETCODE allocSNFRelaxation(SCIP *scip, SNF_RELAXATION *snf, int nvars)
Definition: cuts.c:5877
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:3801
public data structures and miscellaneous methods
static SCIP_RETCODE cutsSubstituteStrongCG(SCIP *scip, SCIP_Real *weights, int *slacksign, int *rowinds, int nrowinds, SCIP_Real scale, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int *cutinds, int *nnz, QUAD(SCIP_Real f0), SCIP_Real k)
Definition: cuts.c:8720
SCIP_Real SCIPaggrRowCalcEfficacyNorm(SCIP *scip, SCIP_AGGRROW *aggrrow)
Definition: cuts.c:2088
SCIP_Bool SCIPcutsTightenCoefficients(SCIP *scip, SCIP_Bool cutislocal, SCIP_Real *cutcoefs, SCIP_Real *cutrhs, int *cutinds, int *cutnnz, int *nchgcoefs)
Definition: cuts.c:1471
SCIP_Bool SCIPisSumLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:707
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:7338
Definition: struct_lp.h:201
static SCIP_RETCODE determineBoundForSNF(SCIP *scip, SCIP_SOL *sol, SCIP_VAR **vars, SCIP_Real *rowcoefs, int *rowinds, int varposinrow, int8_t *binvarused, SCIP_Bool allowlocal, SCIP_Real boundswitch, SCIP_Real *bestlb, SCIP_Real *bestub, SCIP_Real *bestslb, SCIP_Real *bestsub, int *bestlbtype, int *bestubtype, int *bestslbtype, int *bestsubtype, SCIP_BOUNDTYPE *selectedbounds, SCIP_Bool *freevariable)
Definition: cuts.c:5138
public methods for LP management
public methods for cuts and aggregation rows
static SCIP_RETCODE constructSNFRelaxation(SCIP *scip, SCIP_SOL *sol, SCIP_Real boundswitch, SCIP_Bool allowlocal, SCIP_Real *rowcoefs, QUAD(SCIP_Real rowrhs), int *rowinds, int nnz, SNF_RELAXATION *snf, SCIP_Bool *success, SCIP_Bool *localbdsused)
Definition: cuts.c:5319
SCIP_Real * SCIPaggrRowGetRowWeights(SCIP_AGGRROW *aggrrow)
Definition: cuts.c:2435
static SCIP_RETCODE cutsRoundStrongCG(SCIP *scip, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int *cutinds, int *nnz, int *varsign, int *boundtype, QUAD(SCIP_Real f0), SCIP_Real k)
Definition: cuts.c:8509
static SCIP_RETCODE addOneRow(SCIP *scip, SCIP_AGGRROW *aggrrow, SCIP_ROW *row, SCIP_Real weight, SCIP_Bool sidetypebasis, SCIP_Bool allowlocal, int negslack, int maxaggrlen, SCIP_Bool *rowtoolong)
Definition: cuts.c:2100
static SCIP_RETCODE getClosestVub(SCIP *scip, SCIP_VAR *var, SCIP_SOL *sol, SCIP_Real *rowcoefs, int8_t *binvarused, SCIP_Real bestslb, SCIP_Real rowcoef, SCIP_Real *closestvub, int *closestvubidx)
Definition: cuts.c:5010
SCIP_Real SCIPgetRowSolActivity(SCIP *scip, SCIP_ROW *row, SCIP_SOL *sol)
Definition: scip_lp.c:2138
struct SNF_Relaxation SNF_RELAXATION
public methods for the LP relaxation, rows and columns
methods for sorting joint arrays of various types
static SCIP_RETCODE cutsRoundMIR(SCIP *scip, SCIP_Real *RESTRICT cutcoefs, QUAD(SCIP_Real *RESTRICT cutrhs), int *RESTRICT cutinds, int *RESTRICT nnz, int *RESTRICT varsign, int *RESTRICT boundtype, QUAD(SCIP_Real f0))
Definition: cuts.c:3336
SCIP_RETCODE SCIPaggrRowCopy(SCIP *scip, SCIP_AGGRROW **aggrrow, SCIP_AGGRROW *source)
Definition: cuts.c:1753
SCIP_Bool SCIPisGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:486
static SCIP_RETCODE determineBestBounds(SCIP *scip, SCIP_VAR *var, SCIP_SOL *sol, SCIP_Real boundswitch, int usevbds, SCIP_Bool allowlocal, SCIP_Bool fixintegralrhs, SCIP_Bool ignoresol, int *boundsfortrans, SCIP_BOUNDTYPE *boundtypesfortrans, SCIP_Real *bestlb, SCIP_Real *bestub, int *bestlbtype, int *bestubtype, SCIP_BOUNDTYPE *selectedbound, SCIP_Bool *freevariable)
Definition: cuts.c:2646
SCIP_RETCODE SCIPaggrRowSumRows(SCIP *scip, SCIP_AGGRROW *aggrrow, SCIP_Real *weights, int *rowinds, int nrowinds, SCIP_Bool sidetypebasis, SCIP_Bool allowlocal, int negslack, int maxaggrlen, SCIP_Bool *valid)
Definition: cuts.c:2207
void SCIPselectWeightedDownRealRealInt(SCIP_Real *realarray1, SCIP_Real *realarray2, int *intarray, SCIP_Real *weights, SCIP_Real capacity, int len, int *medianpos)
public methods for solutions
static SCIP_Bool removeZeros(SCIP *scip, SCIP_Real minval, SCIP_Bool cutislocal, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int *cutinds, int *cutnnz)
Definition: cuts.c:505
Definition: type_lp.h:57
static void destroySNFRelaxation(SCIP *scip, SNF_RELAXATION *snf)
Definition: cuts.c:5898
static void buildFlowCover(SCIP *scip, int *coefs, SCIP_Real *vubcoefs, SCIP_Real rhs, int *solitems, int *nonsolitems, int nsolitems, int nnonsolitems, int *nflowcovervars, int *nnonflowcovervars, int *flowcoverstatus, QUAD(SCIP_Real *flowcoverweight), SCIP_Real *lambda)
Definition: cuts.c:6013
public methods for message output
data structures for LP management
Definition: type_lpi.h:91
void SCIPmessageFPrintInfo(SCIP_MESSAGEHDLR *messagehdlr, FILE *file, const char *formatstr,...)
Definition: message.c:618
void SCIPsortDownInt(int *intarray, int len)
static SCIP_RETCODE postprocessCut(SCIP *scip, SCIP_Bool cutislocal, int *cutinds, SCIP_Real *cutcoefs, int *nnz, SCIP_Real *cutrhs, SCIP_Bool *success)
Definition: cuts.c:2271
SCIP_Real SCIPgetRowMinActivity(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1933
public methods for message handling
static SCIP_RETCODE findBestLb(SCIP *scip, SCIP_VAR *var, SCIP_SOL *sol, int usevbds, SCIP_Bool allowlocal, SCIP_Real *bestlb, SCIP_Real *simplebound, int *bestlbtype)
Definition: cuts.c:2524
SCIP_RETCODE SCIPaggrRowCreate(SCIP *scip, SCIP_AGGRROW **aggrrow)
Definition: cuts.c:1663
SCIP_RETCODE SCIPcalcIntegralScalar(SCIP_Real *vals, int nvals, SCIP_Real mindelta, SCIP_Real maxdelta, SCIP_Longint maxdnom, SCIP_Real maxscale, SCIP_Real *intscalar, SCIP_Bool *success)
Definition: misc.c:9467
SCIP_Bool SCIPisLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
Definition: scip_numerics.c:473
#define SCIPfreeBlockMemoryArrayNull(scip, ptr, num)
Definition: scip_mem.h:111
SCIP_Bool SCIPisFeasIntegral(SCIP *scip, SCIP_Real val)
Definition: scip_numerics.c:883
SCIP_RETCODE SCIPgetLPRowsData(SCIP *scip, SCIP_ROW ***rows, int *nrows)
Definition: scip_lp.c:570
static SCIP_RETCODE getFlowCover(SCIP *scip, SNF_RELAXATION *snf, int *nflowcovervars, int *nnonflowcovervars, int *flowcoverstatus, SCIP_Real *lambda, SCIP_Bool *found)
Definition: cuts.c:6529
static SCIP_RETCODE cutsTransformKnapsackCover(SCIP *scip, SCIP_SOL *sol, SCIP_Bool allowlocal, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int *cutinds, int *nnz, int *varsign, int *boundtype, SCIP_Bool *localbdsused, SCIP_Bool *success)
Definition: cuts.c:7462
static SCIP_Bool computeInitialKnapsackCover(SCIP *scip, SCIP_SOL *sol, SCIP_Real *cutcoefs, int *cutinds, SCIP_Real cutrhs, int cutnnz, int *varsign, int *coverstatus, int *coverpos, SCIP_Real *covervals, int *coversize, QUAD(SCIP_Real *coverweight))
Definition: cuts.c:7661
Definition: objbenders.h:43
public methods for global and local (sub)problems
SCIP_Real SCIPgetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var)
Definition: scip_sol.c:1361
datastructures for global SCIP settings
static SCIP_Real calcEfficacyDenseStorageQuad(SCIP *scip, SCIP_SOL *sol, SCIP_Real *cutcoefs, SCIP_Real cutrhs, int *cutinds, int cutnnz)
Definition: cuts.c:337
static void performBoundSubstitutionSimple(SCIP *scip, SCIP_Real *cutcoefs, QUAD(SCIP_Real *cutrhs), int boundtype, SCIP_Real boundval, int probindex, SCIP_Bool *localbdsused)
Definition: cuts.c:2925
void SCIPsortDownReal(SCIP_Real *realarray, int len)
Definition: type_lpi.h:93
static SCIP_Real calcEfficacy(SCIP *scip, SCIP_SOL *sol, SCIP_Real *cutcoefs, SCIP_Real cutrhs, int *cutinds, int cutnnz)
Definition: cuts.c:210
methods for selecting (weighted) k-medians
memory allocation routines
Definition: type_var.h:67