/** execution method of primal heuristic */ static SCIP_DECL_HEUREXEC(heurExecZirounding) { /*lint --e{715}*/ SCIP_HEURDATA* heurdata; SCIP_SOL* sol; SCIP_VAR** lpcands; SCIP_VAR** zilpcands; SCIP_VAR** slackvars; SCIP_Real* upslacks; SCIP_Real* downslacks; SCIP_Real* activities; SCIP_Real* slackvarcoeffs; SCIP_Bool* rowneedsslackvar; SCIP_ROW** rows; SCIP_Real* lpcandssol; SCIP_Real* solarray; SCIP_Longint nlps; int currentlpcands; int nlpcands; int nimplfracs; int i; int c; int nslacks; int nroundings; SCIP_RETCODE retcode; SCIP_Bool improvementfound; SCIP_Bool numericalerror; assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0); assert(result != NULL); assert(SCIPhasCurrentNodeLP(scip)); *result = SCIP_DIDNOTRUN; /* do not call heuristic of node was already detected to be infeasible */ if( nodeinfeasible ) return SCIP_OKAY; /* only call heuristic if an optimal LP-solution is at hand */ if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL ) return SCIP_OKAY; /* only call heuristic, if the LP objective value is smaller than the cutoff bound */ if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) ) return SCIP_OKAY; /* get heuristic data */ heurdata = SCIPheurGetData(heur); assert(heurdata != NULL); /* Do not call heuristic if deactivation check is enabled and percentage of found solutions in relation * to number of calls falls below heurdata->stoppercentage */ if( heurdata->stopziround && SCIPheurGetNCalls(heur) >= heurdata->minstopncalls && SCIPheurGetNSolsFound(heur)/(SCIP_Real)SCIPheurGetNCalls(heur) < heurdata->stoppercentage ) return SCIP_OKAY; /* assure that heuristic has not already been called after the last LP had been solved */ nlps = SCIPgetNLPs(scip); if( nlps == heurdata->lastlp ) return SCIP_OKAY; heurdata->lastlp = nlps; /* get fractional variables */ SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, &nimplfracs) ); nlpcands = nlpcands + nimplfracs; /* make sure that there is at least one fractional variable that should be integral */ if( nlpcands == 0 ) return SCIP_OKAY; assert(nlpcands > 0); assert(lpcands != NULL); assert(lpcandssol != NULL); /* get LP rows data */ rows = SCIPgetLPRows(scip); nslacks = SCIPgetNLPRows(scip); /* cannot do anything if LP is empty */ if( nslacks == 0 ) return SCIP_OKAY; assert(rows != NULL); assert(nslacks > 0); /* get the working solution from heuristic's local data */ sol = heurdata->sol; assert(sol != NULL); *result = SCIP_DIDNOTFIND; solarray = NULL; zilpcands = NULL; retcode = SCIP_OKAY; /* copy the current LP solution to the working solution and allocate memory for local data */ SCIP_CALL( SCIPlinkLPSol(scip, sol) ); SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &solarray, nlpcands), TERMINATE); SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &zilpcands, nlpcands), TERMINATE); /* copy necessary data to local arrays */ BMScopyMemoryArray(solarray, lpcandssol, nlpcands); BMScopyMemoryArray(zilpcands, lpcands, nlpcands); /* allocate buffer data arrays */ SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &slackvars, nslacks), TERMINATE); SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &upslacks, nslacks), TERMINATE); SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &downslacks, nslacks), TERMINATE); SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &slackvarcoeffs, nslacks), TERMINATE); SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &rowneedsslackvar, nslacks), TERMINATE); SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &activities, nslacks), TERMINATE); BMSclearMemoryArray(slackvars, nslacks); BMSclearMemoryArray(slackvarcoeffs, nslacks); BMSclearMemoryArray(rowneedsslackvar, nslacks); numericalerror = FALSE; nroundings = 0; /* loop over fractional variables and involved LP rows to find all rows which require a slack variable */ for( c = 0; c < nlpcands; ++c ) { SCIP_VAR* cand; SCIP_ROW** candrows; int r; int ncandrows; cand = zilpcands[c]; assert(cand != NULL); assert(SCIPcolGetLPPos(SCIPvarGetCol(cand)) >= 0); candrows = SCIPcolGetRows(SCIPvarGetCol(cand)); ncandrows = SCIPcolGetNLPNonz(SCIPvarGetCol(cand)); assert(candrows == NULL || ncandrows > 0); for( r = 0; r < ncandrows; ++r ) { int rowpos; assert(candrows != NULL); /* to please flexelint */ assert(candrows[r] != NULL); rowpos = SCIProwGetLPPos(candrows[r]); if( rowpos >= 0 && SCIPisFeasEQ(scip, SCIProwGetLhs(candrows[r]), SCIProwGetRhs(candrows[r])) ) { rowneedsslackvar[rowpos] = TRUE; SCIPdebugMessage(" Row %s needs slack variable for variable %s\n", SCIProwGetName(candrows[r]), SCIPvarGetName(cand)); } } } /* calculate row slacks for every every row that belongs to the current LP and ensure, that the current solution * has no violated constraint -- if any constraint is violated, i.e. a slack is significantly smaller than zero, * this will cause the termination of the heuristic because Zirounding does not provide feasibility recovering */ for( i = 0; i < nslacks; ++i ) { SCIP_ROW* row; SCIP_Real lhs; SCIP_Real rhs; row = rows[i]; assert(row != NULL); lhs = SCIProwGetLhs(row); rhs = SCIProwGetRhs(row); /* get row activity */ activities[i] = SCIPgetRowActivity(scip, row); assert(SCIPisFeasLE(scip, lhs, activities[i]) && SCIPisFeasLE(scip, activities[i], rhs)); /* in special case if LHS or RHS is (-)infinity slacks have to be initialized as infinity */ if( SCIPisInfinity(scip, -lhs) ) downslacks[i] = SCIPinfinity(scip); else downslacks[i] = activities[i] - lhs; if( SCIPisInfinity(scip, rhs) ) upslacks[i] = SCIPinfinity(scip); else upslacks[i] = rhs - activities[i]; SCIPdebugMessage("lhs:%5.2f <= act:%5.2g <= rhs:%5.2g --> down: %5.2g, up:%5.2g\n", lhs, activities[i], rhs, downslacks[i], upslacks[i]); /* row is an equation. Try to find a slack variable in the row, i.e., * a continuous variable which occurs only in this row. If no such variable exists, * there is no hope for an IP-feasible solution in this round */ if( SCIPisFeasEQ(scip, lhs, rhs) && rowneedsslackvar[i] ) { /* @todo: This is only necessary for rows containing fractional variables. */ rowFindSlackVar(scip, row, &(slackvars[i]), &(slackvarcoeffs[i])); if( slackvars[i] == NULL ) { SCIPdebugMessage("No slack variable found for equation %s, terminating ZI Round heuristic\n", SCIProwGetName(row)); goto TERMINATE; } else { SCIP_Real ubslackvar; SCIP_Real lbslackvar; SCIP_Real solvalslackvar; SCIP_Real coeffslackvar; SCIP_Real ubgap; SCIP_Real lbgap; assert(SCIPvarGetType(slackvars[i]) == SCIP_VARTYPE_CONTINUOUS); solvalslackvar = SCIPgetSolVal(scip, sol, slackvars[i]); ubslackvar = SCIPvarGetUbGlobal(slackvars[i]); lbslackvar = SCIPvarGetLbGlobal(slackvars[i]); coeffslackvar = slackvarcoeffs[i]; assert(!SCIPisFeasZero(scip, coeffslackvar)); ubgap = ubslackvar - solvalslackvar; lbgap = solvalslackvar - lbslackvar; if( SCIPisFeasZero(scip, ubgap) ) ubgap = 0.0; if( SCIPisFeasZero(scip, lbgap) ) lbgap = 0.0; if( SCIPisFeasPositive(scip, coeffslackvar) ) { if( !SCIPisInfinity(scip, lbslackvar) ) upslacks[i] += coeffslackvar * lbgap; else upslacks[i] = SCIPinfinity(scip); if( !SCIPisInfinity(scip, ubslackvar) ) downslacks[i] += coeffslackvar * ubgap; else downslacks[i] = SCIPinfinity(scip); } else { if( !SCIPisInfinity(scip, ubslackvar) ) upslacks[i] -= coeffslackvar * ubgap; else upslacks[i] = SCIPinfinity(scip); if( !SCIPisInfinity(scip, lbslackvar) ) downslacks[i] -= coeffslackvar * lbgap; else downslacks[i] = SCIPinfinity(scip); } SCIPdebugMessage(" Slack variable for row %s at pos %d: %g <= %s = %g <= %g; Coeff %g, upslack = %g, downslack = %g \n", SCIProwGetName(row), SCIProwGetLPPos(row), lbslackvar, SCIPvarGetName(slackvars[i]), solvalslackvar, ubslackvar, coeffslackvar, upslacks[i], downslacks[i]); } } /* due to numerical inaccuracies, the rows might be feasible, even if the slacks are * significantly smaller than zero -> terminate */ if( SCIPisFeasLT(scip, upslacks[i], 0.0) || SCIPisFeasLT(scip, downslacks[i], 0.0) ) goto TERMINATE; } assert(nslacks == 0 || (upslacks != NULL && downslacks != NULL && activities != NULL)); /* initialize number of remaining variables and flag to enter the main loop */ currentlpcands = nlpcands; improvementfound = TRUE; /* iterate over variables as long as there are fractional variables left */ while( currentlpcands > 0 && improvementfound && (heurdata->maxroundingloops == -1 || nroundings < heurdata->maxroundingloops) ) { /*lint --e{850}*/ improvementfound = FALSE; nroundings++; SCIPdebugMessage("zirounding enters while loop for %d time with %d candidates left. \n", nroundings, currentlpcands); /* check for every remaining fractional variable if a shifting decreases ZI-value of the variable */ for( c = 0; c < currentlpcands; ++c ) { SCIP_VAR* var; SCIP_Real oldsolval; SCIP_Real upperbound; SCIP_Real lowerbound; SCIP_Real up; SCIP_Real down; SCIP_Real ziup; SCIP_Real zidown; SCIP_Real zicurrent; SCIP_Real shiftval; DIRECTION direction; /* get values from local data */ oldsolval = solarray[c]; var = zilpcands[c]; assert(!SCIPisFeasIntegral(scip, oldsolval)); assert(SCIPvarGetStatus(var) == SCIP_VARSTATUS_COLUMN); /* calculate bounds for variable and make sure that there are no numerical inconsistencies */ upperbound = SCIPinfinity(scip); lowerbound = SCIPinfinity(scip); calculateBounds(scip, var, oldsolval, &upperbound, &lowerbound, upslacks, downslacks, nslacks, &numericalerror); if( numericalerror ) goto TERMINATE; /* calculate the possible values after shifting */ up = oldsolval + upperbound; down = oldsolval - lowerbound; /* if the variable is integer or implicit binary, do not shift further than the nearest integer */ if( SCIPvarGetType(var) != SCIP_VARTYPE_BINARY) { SCIP_Real ceilx; SCIP_Real floorx; ceilx = SCIPfeasCeil(scip, oldsolval); floorx = SCIPfeasFloor(scip, oldsolval); up = MIN(up, ceilx); down = MAX(down, floorx); } /* calculate necessary values */ ziup = getZiValue(scip, up); zidown = getZiValue(scip, down); zicurrent = getZiValue(scip, oldsolval); /* calculate the shifting direction that reduces ZI-value the most, * if both directions improve ZI-value equally, take the direction which improves the objective */ if( SCIPisFeasLT(scip, zidown, zicurrent) || SCIPisFeasLT(scip, ziup, zicurrent) ) { if( SCIPisFeasEQ(scip,ziup, zidown) ) direction = SCIPisFeasGE(scip, SCIPvarGetObj(var), 0.0) ? DIRECTION_DOWN : DIRECTION_UP; else if( SCIPisFeasLT(scip, zidown, ziup) ) direction = DIRECTION_DOWN; else direction = DIRECTION_UP; /* once a possible shifting direction and value have been found, variable value is updated */ shiftval = (direction == DIRECTION_UP ? up - oldsolval : down - oldsolval); /* this improves numerical stability in some cases */ if( direction == DIRECTION_UP ) shiftval = MIN(shiftval, upperbound); else shiftval = MIN(shiftval, lowerbound); /* update the solution */ solarray[c] = direction == DIRECTION_UP ? up : down; SCIP_CALL( SCIPsetSolVal(scip, sol, var, solarray[c]) ); /* update the rows activities and slacks */ SCIP_CALL( updateSlacks(scip, sol, var, shiftval, upslacks, downslacks, activities, slackvars, slackvarcoeffs, nslacks) ); SCIPdebugMessage("zirounding update step : %d var index, oldsolval=%g, shiftval=%g\n", SCIPvarGetIndex(var), oldsolval, shiftval); /* since at least one improvement has been found, heuristic will enter main loop for another time because the improvement * might affect many LP rows and their current slacks and thus make further rounding steps possible */ improvementfound = TRUE; } /* if solution value of variable has become feasibly integral due to rounding step, * variable is put at the end of remaining candidates array so as not to be considered in future loops */ if( SCIPisFeasIntegral(scip, solarray[c]) ) { zilpcands[c] = zilpcands[currentlpcands - 1]; solarray[c] = solarray[currentlpcands - 1]; currentlpcands--; /* counter is decreased if end of candidates array has not been reached yet */ if( c < currentlpcands ) c--; } else if( nroundings == heurdata->maxroundingloops - 1 ) goto TERMINATE; } } /* in case that no candidate is left for rounding after the final main loop * the found solution has to be checked for feasibility in the original problem */ if( currentlpcands == 0 ) { SCIP_Bool stored; SCIP_CALL(SCIPtrySol(scip, sol, FALSE, FALSE, TRUE, FALSE, &stored)); if( stored ) { #ifdef SCIP_DEBUG SCIPdebugMessage("found feasible rounded solution:\n"); SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) ); #endif SCIPstatisticMessage(" ZI Round solution value: %g \n", SCIPgetSolOrigObj(scip, sol)); *result = SCIP_FOUNDSOL; } } /* free memory for all locally allocated data */ TERMINATE: SCIPfreeBufferArrayNull(scip, &activities); SCIPfreeBufferArrayNull(scip, &rowneedsslackvar); SCIPfreeBufferArrayNull(scip, &slackvarcoeffs); SCIPfreeBufferArrayNull(scip, &downslacks); SCIPfreeBufferArrayNull(scip, &upslacks); SCIPfreeBufferArrayNull(scip, &slackvars); SCIPfreeBufferArrayNull(scip, &zilpcands); SCIPfreeBufferArrayNull(scip, &solarray); return retcode; }
/** LP solution separation method of separator */ static SCIP_DECL_SEPAEXECLP(sepaExeclpGomory) { /*lint --e{715}*/ SCIP_SEPADATA* sepadata; SCIP_VAR** vars; SCIP_COL** cols; SCIP_ROW** rows; SCIP_Real* binvrow; SCIP_Real* cutcoefs; SCIP_Real maxscale; SCIP_Real minfrac; SCIP_Real maxfrac; SCIP_Longint maxdnom; SCIP_Bool cutoff; int* basisind; int naddedcuts; int nvars; int ncols; int nrows; int ncalls; int depth; int maxdepth; int maxsepacuts; int c; int i; assert(sepa != NULL); assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0); assert(scip != NULL); assert(result != NULL); *result = SCIP_DIDNOTRUN; sepadata = SCIPsepaGetData(sepa); assert(sepadata != NULL); depth = SCIPgetDepth(scip); ncalls = SCIPsepaGetNCallsAtNode(sepa); minfrac = sepadata->away; maxfrac = 1.0 - sepadata->away; /* only call separator, if we are not close to terminating */ if( SCIPisStopped(scip) ) return SCIP_OKAY; /* only call the gomory cut separator a given number of times at each node */ if( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot) || (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) ) return SCIP_OKAY; /* only call separator, if an optimal LP solution is at hand */ if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL ) return SCIP_OKAY; /* only call separator, if the LP solution is basic */ if( !SCIPisLPSolBasic(scip) ) return SCIP_OKAY; /* only call separator, if there are fractional variables */ if( SCIPgetNLPBranchCands(scip) == 0 ) return SCIP_OKAY; /* get variables data */ SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) ); /* get LP data */ SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) ); SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) ); if( ncols == 0 || nrows == 0 ) return SCIP_OKAY; #if 0 /* if too many columns, separator is usually very slow: delay it until no other cuts have been found */ if( ncols >= 50*nrows ) return SCIP_OKAY; if( ncols >= 5*nrows ) { int ncutsfound; ncutsfound = SCIPgetNCutsFound(scip); if( ncutsfound > sepadata->lastncutsfound || !SCIPsepaWasLPDelayed(sepa) ) { sepadata->lastncutsfound = ncutsfound; *result = SCIP_DELAYED; return SCIP_OKAY; } } #endif /* set the maximal denominator in rational representation of gomory cut and the maximal scale factor to * scale resulting cut to integral values to avoid numerical instabilities */ /**@todo find better but still stable gomory cut settings: look at dcmulti, gesa3, khb0525, misc06, p2756 */ maxdepth = SCIPgetMaxDepth(scip); if( depth == 0 ) { maxdnom = 1000; maxscale = 1000.0; } else if( depth <= maxdepth/4 ) { maxdnom = 1000; maxscale = 1000.0; } else if( depth <= maxdepth/2 ) { maxdnom = 100; maxscale = 100.0; } else { maxdnom = 10; maxscale = 10.0; } /* allocate temporary memory */ SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, nvars) ); SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) ); SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) ); /* get basis indices */ SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) ); /* get the maximal number of cuts allowed in a separation round */ if( depth == 0 ) maxsepacuts = sepadata->maxsepacutsroot; else maxsepacuts = sepadata->maxsepacuts; SCIPdebugMessage("searching gomory cuts: %d cols, %d rows, maxdnom=%"SCIP_LONGINT_FORMAT", maxscale=%g, maxcuts=%d\n", ncols, nrows, maxdnom, maxscale, maxsepacuts); cutoff = FALSE; naddedcuts = 0; /* for all basic columns belonging to integer variables, try to generate a gomory cut */ for( i = 0; i < nrows && naddedcuts < maxsepacuts && !SCIPisStopped(scip) && !cutoff; ++i ) { SCIP_Bool tryrow; tryrow = FALSE; c = basisind[i]; if( c >= 0 ) { SCIP_VAR* var; assert(c < ncols); var = SCIPcolGetVar(cols[c]); if( SCIPvarGetType(var) != SCIP_VARTYPE_CONTINUOUS ) { SCIP_Real primsol; primsol = SCIPcolGetPrimsol(cols[c]); assert(SCIPgetVarSol(scip, var) == primsol); /*lint !e777*/ if( SCIPfeasFrac(scip, primsol) >= minfrac ) { SCIPdebugMessage("trying gomory cut for col <%s> [%g]\n", SCIPvarGetName(var), primsol); tryrow = TRUE; } } } else if( sepadata->separaterows ) { SCIP_ROW* row; assert(0 <= -c-1 && -c-1 < nrows); row = rows[-c-1]; if( SCIProwIsIntegral(row) && !SCIProwIsModifiable(row) ) { SCIP_Real primsol; primsol = SCIPgetRowActivity(scip, row); if( SCIPfeasFrac(scip, primsol) >= minfrac ) { SCIPdebugMessage("trying gomory cut for row <%s> [%g]\n", SCIProwGetName(row), primsol); tryrow = TRUE; } } } if( tryrow ) { SCIP_Real cutrhs; SCIP_Real cutact; SCIP_Bool success; SCIP_Bool cutislocal; /* get the row of B^-1 for this basic integer variable with fractional solution value */ SCIP_CALL( SCIPgetLPBInvRow(scip, i, binvrow) ); cutact = 0.0; cutrhs = SCIPinfinity(scip); /* create a MIR cut out of the weighted LP rows using the B^-1 row as weights */ SCIP_CALL( SCIPcalcMIR(scip, NULL, BOUNDSWITCH, USEVBDS, ALLOWLOCAL, FIXINTEGRALRHS, NULL, NULL, (int) MAXAGGRLEN(nvars), sepadata->maxweightrange, minfrac, maxfrac, binvrow, 1.0, NULL, NULL, cutcoefs, &cutrhs, &cutact, &success, &cutislocal) ); assert(ALLOWLOCAL || !cutislocal); /* @todo Currently we are using the SCIPcalcMIR() function to compute the coefficients of the Gomory * cut. Alternatively, we could use the direct version (see thesis of Achterberg formula (8.4)) which * leads to cut a of the form \sum a_i x_i \geq 1. Rumor has it that these cuts are better. */ SCIPdebugMessage(" -> success=%u: %g <= %g\n", success, cutact, cutrhs); /* if successful, convert dense cut into sparse row, and add the row as a cut */ if( success && SCIPisFeasGT(scip, cutact, cutrhs) ) { SCIP_ROW* cut; char cutname[SCIP_MAXSTRLEN]; int v; /* construct cut name */ if( c >= 0 ) (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "gom%d_x%d", SCIPgetNLPs(scip), c); else (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "gom%d_s%d", SCIPgetNLPs(scip), -c-1); /* create empty cut */ SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &cut, sepa, cutname, -SCIPinfinity(scip), cutrhs, cutislocal, FALSE, sepadata->dynamiccuts) ); /* cache the row extension and only flush them if the cut gets added */ SCIP_CALL( SCIPcacheRowExtensions(scip, cut) ); /* collect all non-zero coefficients */ for( v = 0; v < nvars; ++v ) { if( !SCIPisZero(scip, cutcoefs[v]) ) { SCIP_CALL( SCIPaddVarToRow(scip, cut, vars[v], cutcoefs[v]) ); } } if( SCIProwGetNNonz(cut) == 0 ) { assert(SCIPisFeasNegative(scip, cutrhs)); SCIPdebugMessage(" -> gomory cut detected infeasibility with cut 0 <= %f\n", cutrhs); cutoff = TRUE; } else if( SCIProwGetNNonz(cut) == 1 ) { /* add the bound change as cut to avoid that the LP gets modified. that would mean the LP is not flushed * and the method SCIPgetLPBInvRow() fails; SCIP internally will apply that bound change automatically */ SCIP_CALL( SCIPaddCut(scip, NULL, cut, TRUE) ); naddedcuts++; } else { /* Only take efficacious cuts, except for cuts with one non-zero coefficients (= bound * changes); the latter cuts will be handeled internally in sepastore. */ if( SCIPisCutEfficacious(scip, NULL, cut) ) { assert(success == TRUE); SCIPdebugMessage(" -> gomory cut for <%s>: act=%f, rhs=%f, eff=%f\n", c >= 0 ? SCIPvarGetName(SCIPcolGetVar(cols[c])) : SCIProwGetName(rows[-c-1]), cutact, cutrhs, SCIPgetCutEfficacy(scip, NULL, cut)); if( sepadata->makeintegral ) { /* try to scale the cut to integral values */ SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip), maxdnom, maxscale, MAKECONTINTEGRAL, &success) ); if( sepadata->forcecuts ) success = TRUE; /* in case the left hand side in minus infinity and the right hand side is plus infinity the cut is * useless so we are not taking it at all */ if( (SCIPisInfinity(scip, -SCIProwGetLhs(cut)) && SCIPisInfinity(scip, SCIProwGetRhs(cut))) ) success = FALSE; /* @todo Trying to make the Gomory cut integral might fail. Due to numerical reasons/arguments we * currently ignore such cuts. If the cut, however, has small support (let's say smaller or equal to * 5), we might want to add that cut (even it does not have integral coefficients). To be able to * do that we need to add a rank to the data structure of a row. The rank of original rows are * zero and for aggregated rows it is the maximum over all used rows plus one. */ } if( success ) { SCIPdebugMessage(" -> found gomory cut <%s>: act=%f, rhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n", cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut), SCIPgetCutEfficacy(scip, NULL, cut), SCIPgetRowMinCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut)/SCIPgetRowMinCoef(scip, cut)); /* flush all changes before adding the cut */ SCIP_CALL( SCIPflushRowExtensions(scip, cut) ); /* add global cuts which are not implicit bound changes to the cut pool */ if( !cutislocal ) { if( sepadata->delayedcuts ) { SCIP_CALL( SCIPaddDelayedPoolCut(scip, cut) ); } else { SCIP_CALL( SCIPaddPoolCut(scip, cut) ); } } else { /* local cuts we add to the sepastore */ SCIP_CALL( SCIPaddCut(scip, NULL, cut, FALSE) ); } naddedcuts++; } } } /* release the row */ SCIP_CALL( SCIPreleaseRow(scip, &cut) ); } } } /* free temporary memory */ SCIPfreeBufferArray(scip, &binvrow); SCIPfreeBufferArray(scip, &basisind); SCIPfreeBufferArray(scip, &cutcoefs); SCIPdebugMessage("end searching gomory cuts: found %d cuts\n", naddedcuts); sepadata->lastncutsfound = SCIPgetNCutsFound(scip); /* evalute the result of the separation */ if( cutoff ) *result = SCIP_CUTOFF; else if ( naddedcuts > 0 ) *result = SCIP_SEPARATED; else *result = SCIP_DIDNOTFIND; return SCIP_OKAY; }
/** execution method of primal heuristic */ static SCIP_DECL_HEUREXEC(heurExecShifting) /*lint --e{715}*/ { /*lint --e{715}*/ SCIP_HEURDATA* heurdata; SCIP_SOL* sol; SCIP_VAR** lpcands; SCIP_Real* lpcandssol; SCIP_ROW** lprows; SCIP_Real* activities; SCIP_ROW** violrows; SCIP_Real* nincreases; SCIP_Real* ndecreases; int* violrowpos; int* nfracsinrow; SCIP_Real increaseweight; SCIP_Real obj; SCIP_Real bestshiftval; SCIP_Real minobj; int nlpcands; int nlprows; int nvars; int nfrac; int nviolrows; int nprevviolrows; int minnviolrows; int nnonimprovingshifts; int c; int r; SCIP_Longint nlps; SCIP_Longint ncalls; SCIP_Longint nsolsfound; SCIP_Longint nnodes; assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0); assert(scip != NULL); assert(result != NULL); assert(SCIPhasCurrentNodeLP(scip)); *result = SCIP_DIDNOTRUN; /* only call heuristic, if an optimal LP solution is at hand */ if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL ) return SCIP_OKAY; /* only call heuristic, if the LP objective value is smaller than the cutoff bound */ if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) ) return SCIP_OKAY; /* get heuristic data */ heurdata = SCIPheurGetData(heur); assert(heurdata != NULL); /* don't call heuristic, if we have already processed the current LP solution */ nlps = SCIPgetNLPs(scip); if( nlps == heurdata->lastlp ) return SCIP_OKAY; heurdata->lastlp = nlps; /* don't call heuristic, if it was not successful enough in the past */ ncalls = SCIPheurGetNCalls(heur); nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + SCIPheurGetNSolsFound(heur); nnodes = SCIPgetNNodes(scip); if( nnodes % ((ncalls/100)/(nsolsfound+1)+1) != 0 ) return SCIP_OKAY; /* get fractional variables, that should be integral */ /* todo check if heuristic should include implicit integer variables for its calculations */ SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, NULL) ); nfrac = nlpcands; /* only call heuristic, if LP solution is fractional */ if( nfrac == 0 ) return SCIP_OKAY; *result = SCIP_DIDNOTFIND; /* get LP rows */ SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) ); SCIPdebugMessage("executing shifting heuristic: %d LP rows, %d fractionals\n", nlprows, nfrac); /* get memory for activities, violated rows, and row violation positions */ nvars = SCIPgetNVars(scip); SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) ); SCIP_CALL( SCIPallocBufferArray(scip, &violrows, nlprows) ); SCIP_CALL( SCIPallocBufferArray(scip, &violrowpos, nlprows) ); SCIP_CALL( SCIPallocBufferArray(scip, &nfracsinrow, nlprows) ); SCIP_CALL( SCIPallocBufferArray(scip, &nincreases, nvars) ); SCIP_CALL( SCIPallocBufferArray(scip, &ndecreases, nvars) ); BMSclearMemoryArray(nfracsinrow, nlprows); BMSclearMemoryArray(nincreases, nvars); BMSclearMemoryArray(ndecreases, nvars); /* get the activities for all globally valid rows; * the rows should be feasible, but due to numerical inaccuracies in the LP solver, they can be violated */ nviolrows = 0; for( r = 0; r < nlprows; ++r ) { SCIP_ROW* row; row = lprows[r]; assert(SCIProwGetLPPos(row) == r); if( !SCIProwIsLocal(row) ) { activities[r] = SCIPgetRowActivity(scip, row); if( SCIPisFeasLT(scip, activities[r], SCIProwGetLhs(row)) || SCIPisFeasGT(scip, activities[r], SCIProwGetRhs(row)) ) { violrows[nviolrows] = row; violrowpos[r] = nviolrows; nviolrows++; } else violrowpos[r] = -1; } } /* calc the current number of fractional variables in rows */ for( c = 0; c < nlpcands; ++c ) addFracCounter(nfracsinrow, nlprows, lpcands[c], +1); /* get the working solution from heuristic's local data */ sol = heurdata->sol; assert(sol != NULL); /* copy the current LP solution to the working solution */ SCIP_CALL( SCIPlinkLPSol(scip, sol) ); /* calculate the minimal objective value possible after rounding fractional variables */ minobj = SCIPgetSolTransObj(scip, sol); assert(minobj < SCIPgetCutoffbound(scip)); for( c = 0; c < nlpcands; ++c ) { obj = SCIPvarGetObj(lpcands[c]); bestshiftval = obj > 0.0 ? SCIPfeasFloor(scip, lpcandssol[c]) : SCIPfeasCeil(scip, lpcandssol[c]); minobj += obj * (bestshiftval - lpcandssol[c]); } /* try to shift remaining variables in order to become/stay feasible */ nnonimprovingshifts = 0; minnviolrows = INT_MAX; increaseweight = 1.0; while( (nfrac > 0 || nviolrows > 0) && nnonimprovingshifts < MAXSHIFTINGS ) { SCIP_VAR* shiftvar; SCIP_Real oldsolval; SCIP_Real newsolval; SCIP_Bool oldsolvalisfrac; int probindex; SCIPdebugMessage("shifting heuristic: nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g), cutoff=%g\n", nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj), SCIPretransformObj(scip, SCIPgetCutoffbound(scip))); nprevviolrows = nviolrows; /* choose next variable to process: * - if a violated row exists, shift a variable decreasing the violation, that has least impact on other rows * - otherwise, shift a variable, that has strongest devastating impact on rows in opposite direction */ shiftvar = NULL; oldsolval = 0.0; newsolval = 0.0; if( nviolrows > 0 && (nfrac == 0 || nnonimprovingshifts < MAXSHIFTINGS-1) ) { SCIP_ROW* row; int rowidx; int rowpos; int direction; rowidx = -1; rowpos = -1; row = NULL; if( nfrac > 0 ) { for( rowidx = nviolrows-1; rowidx >= 0; --rowidx ) { row = violrows[rowidx]; rowpos = SCIProwGetLPPos(row); assert(violrowpos[rowpos] == rowidx); if( nfracsinrow[rowpos] > 0 ) break; } } if( rowidx == -1 ) { rowidx = SCIPgetRandomInt(0, nviolrows-1, &heurdata->randseed); row = violrows[rowidx]; rowpos = SCIProwGetLPPos(row); assert(0 <= rowpos && rowpos < nlprows); assert(violrowpos[rowpos] == rowidx); assert(nfracsinrow[rowpos] == 0); } assert(violrowpos[rowpos] == rowidx); SCIPdebugMessage("shifting heuristic: try to fix violated row <%s>: %g <= %g <= %g\n", SCIProwGetName(row), SCIProwGetLhs(row), activities[rowpos], SCIProwGetRhs(row)); SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) ); /* get direction in which activity must be shifted */ assert(SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row)) || SCIPisFeasGT(scip, activities[rowpos], SCIProwGetRhs(row))); direction = SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row)) ? +1 : -1; /* search a variable that can shift the activity in the necessary direction */ SCIP_CALL( selectShifting(scip, sol, row, activities[rowpos], direction, nincreases, ndecreases, increaseweight, &shiftvar, &oldsolval, &newsolval) ); } if( shiftvar == NULL && nfrac > 0 ) { SCIPdebugMessage("shifting heuristic: search rounding variable and try to stay feasible\n"); SCIP_CALL( selectEssentialRounding(scip, sol, minobj, lpcands, nlpcands, &shiftvar, &oldsolval, &newsolval) ); } /* check, whether shifting was possible */ if( shiftvar == NULL || SCIPisEQ(scip, oldsolval, newsolval) ) { SCIPdebugMessage("shifting heuristic: -> didn't find a shifting variable\n"); break; } SCIPdebugMessage("shifting heuristic: -> shift var <%s>[%g,%g], type=%d, oldval=%g, newval=%g, obj=%g\n", SCIPvarGetName(shiftvar), SCIPvarGetLbGlobal(shiftvar), SCIPvarGetUbGlobal(shiftvar), SCIPvarGetType(shiftvar), oldsolval, newsolval, SCIPvarGetObj(shiftvar)); /* update row activities of globally valid rows */ SCIP_CALL( updateActivities(scip, activities, violrows, violrowpos, &nviolrows, nlprows, shiftvar, oldsolval, newsolval) ); if( nviolrows >= nprevviolrows ) nnonimprovingshifts++; else if( nviolrows < minnviolrows ) { minnviolrows = nviolrows; nnonimprovingshifts = 0; } /* store new solution value and decrease fractionality counter */ SCIP_CALL( SCIPsetSolVal(scip, sol, shiftvar, newsolval) ); /* update fractionality counter and minimal objective value possible after shifting remaining variables */ oldsolvalisfrac = !SCIPisFeasIntegral(scip, oldsolval) && (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER); obj = SCIPvarGetObj(shiftvar); if( (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER) && oldsolvalisfrac ) { assert(SCIPisFeasIntegral(scip, newsolval)); nfrac--; nnonimprovingshifts = 0; minnviolrows = INT_MAX; addFracCounter(nfracsinrow, nlprows, shiftvar, -1); /* the rounding was already calculated into the minobj -> update only if rounding in "wrong" direction */ if( obj > 0.0 && newsolval > oldsolval ) minobj += obj; else if( obj < 0.0 && newsolval < oldsolval ) minobj -= obj; } else { /* update minimal possible objective value */ minobj += obj * (newsolval - oldsolval); } /* update increase/decrease arrays */ if( !oldsolvalisfrac ) { probindex = SCIPvarGetProbindex(shiftvar); assert(0 <= probindex && probindex < nvars); increaseweight *= WEIGHTFACTOR; if( newsolval < oldsolval ) ndecreases[probindex] += increaseweight; else nincreases[probindex] += increaseweight; if( increaseweight >= 1e+09 ) { int i; for( i = 0; i < nvars; ++i ) { nincreases[i] /= increaseweight; ndecreases[i] /= increaseweight; } increaseweight = 1.0; } } SCIPdebugMessage("shifting heuristic: -> nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n", nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj)); } /* check, if the new solution is feasible */ if( nfrac == 0 && nviolrows == 0 ) { SCIP_Bool stored; /* check solution for feasibility, and add it to solution store if possible * neither integrality nor feasibility of LP rows has to be checked, because this is already * done in the shifting heuristic itself; however, we better check feasibility of LP rows, * because of numerical problems with activity updating */ SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, FALSE, TRUE, &stored) ); if( stored ) { SCIPdebugMessage("found feasible shifted solution:\n"); SCIPdebug( SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) ) ); *result = SCIP_FOUNDSOL; } } /* free memory buffers */ SCIPfreeBufferArray(scip, &ndecreases); SCIPfreeBufferArray(scip, &nincreases); SCIPfreeBufferArray(scip, &nfracsinrow); SCIPfreeBufferArray(scip, &violrowpos); SCIPfreeBufferArray(scip, &violrows); SCIPfreeBufferArray(scip, &activities); return SCIP_OKAY; }
/** LP solution separation method of separator */ static SCIP_DECL_SEPAEXECLP(sepaExeclpStrongcg) { /*lint --e{715}*/ SCIP_SEPADATA* sepadata; SCIP_VAR** vars; SCIP_COL** cols; SCIP_ROW** rows; SCIP_Real* varsolvals; SCIP_Real* binvrow; SCIP_Real* cutcoefs; SCIP_Real cutrhs; SCIP_Real cutact; SCIP_Real maxscale; SCIP_Longint maxdnom; int* basisind; int* inds; int ninds; int nvars; int ncols; int nrows; int ncalls; int depth; int maxdepth; int maxsepacuts; int ncuts; int c; int i; int cutrank; SCIP_Bool success; SCIP_Bool cutislocal; char normtype; assert(sepa != NULL); assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0); assert(scip != NULL); assert(result != NULL); *result = SCIP_DIDNOTRUN; sepadata = SCIPsepaGetData(sepa); assert(sepadata != NULL); depth = SCIPgetDepth(scip); ncalls = SCIPsepaGetNCallsAtNode(sepa); /* only call separator, if we are not close to terminating */ if( SCIPisStopped(scip) ) return SCIP_OKAY; /* only call the strong CG cut separator a given number of times at each node */ if( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot) || (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) ) return SCIP_OKAY; /* only call separator, if an optimal LP solution is at hand */ if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL ) return SCIP_OKAY; /* only call separator, if the LP solution is basic */ if( !SCIPisLPSolBasic(scip) ) return SCIP_OKAY; /* only call separator, if there are fractional variables */ if( SCIPgetNLPBranchCands(scip) == 0 ) return SCIP_OKAY; /* get variables data */ SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) ); /* get LP data */ SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) ); SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) ); if( ncols == 0 || nrows == 0 ) return SCIP_OKAY; #if 0 /* if too many columns, separator is usually very slow: delay it until no other cuts have been found */ if( ncols >= 50*nrows ) return SCIP_OKAY; if( ncols >= 5*nrows ) { int ncutsfound; ncutsfound = SCIPgetNCutsFound(scip); if( ncutsfound > sepadata->lastncutsfound || !SCIPsepaWasLPDelayed(sepa) ) { sepadata->lastncutsfound = ncutsfound; *result = SCIP_DELAYED; return SCIP_OKAY; } } #endif /* get the type of norm to use for efficacy calculations */ SCIP_CALL( SCIPgetCharParam(scip, "separating/efficacynorm", &normtype) ); /* set the maximal denominator in rational representation of strong CG cut and the maximal scale factor to * scale resulting cut to integral values to avoid numerical instabilities */ /**@todo find better but still stable strong CG cut settings: look at dcmulti, gesa3, khb0525, misc06, p2756 */ maxdepth = SCIPgetMaxDepth(scip); if( depth == 0 ) { maxdnom = 1000; maxscale = 1000.0; } else if( depth <= maxdepth/4 ) { maxdnom = 1000; maxscale = 1000.0; } else if( depth <= maxdepth/2 ) { maxdnom = 100; maxscale = 100.0; } else { maxdnom = 10; maxscale = 10.0; } *result = SCIP_DIDNOTFIND; /* allocate temporary memory */ SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, nvars) ); SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) ); SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) ); SCIP_CALL( SCIPallocBufferArray(scip, &inds, nrows) ); varsolvals = NULL; /* allocate this later, if needed */ /* get basis indices */ SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) ); /* get the maximal number of cuts allowed in a separation round */ if( depth == 0 ) maxsepacuts = sepadata->maxsepacutsroot; else maxsepacuts = sepadata->maxsepacuts; SCIPdebugMessage("searching strong CG cuts: %d cols, %d rows, maxdnom=%" SCIP_LONGINT_FORMAT ", maxscale=%g, maxcuts=%d\n", ncols, nrows, maxdnom, maxscale, maxsepacuts); /* for all basic columns belonging to integer variables, try to generate a strong CG cut */ ncuts = 0; for( i = 0; i < nrows && ncuts < maxsepacuts && !SCIPisStopped(scip) && *result != SCIP_CUTOFF; ++i ) { SCIP_Bool tryrow; tryrow = FALSE; c = basisind[i]; if( c >= 0 ) { SCIP_VAR* var; assert(c < ncols); var = SCIPcolGetVar(cols[c]); if( SCIPvarGetType(var) != SCIP_VARTYPE_CONTINUOUS ) { SCIP_Real primsol; primsol = SCIPcolGetPrimsol(cols[c]); assert(SCIPgetVarSol(scip, var) == primsol); /*lint !e777*/ if( SCIPfeasFrac(scip, primsol) >= MINFRAC ) { SCIPdebugMessage("trying strong CG cut for col <%s> [%g]\n", SCIPvarGetName(var), primsol); tryrow = TRUE; } } } #ifdef SEPARATEROWS else { SCIP_ROW* row; assert(0 <= -c-1 && -c-1 < nrows); row = rows[-c-1]; if( SCIProwIsIntegral(row) && !SCIProwIsModifiable(row) ) { SCIP_Real primsol; primsol = SCIPgetRowActivity(scip, row); if( SCIPfeasFrac(scip, primsol) >= MINFRAC ) { SCIPdebugMessage("trying strong CG cut for row <%s> [%g]\n", SCIProwGetName(row), primsol); tryrow = TRUE; } } } #endif if( tryrow ) { /* get the row of B^-1 for this basic integer variable with fractional solution value */ SCIP_CALL( SCIPgetLPBInvRow(scip, i, binvrow, inds, &ninds) ); #ifdef SCIP_DEBUG /* initialize variables, that might not have been initialized in SCIPcalcMIR if success == FALSE */ cutact = 0.0; cutrhs = SCIPinfinity(scip); #endif /* create a strong CG cut out of the weighted LP rows using the B^-1 row as weights */ SCIP_CALL( SCIPcalcStrongCG(scip, BOUNDSWITCH, USEVBDS, ALLOWLOCAL, (int) MAXAGGRLEN(nvars), sepadata->maxweightrange, MINFRAC, MAXFRAC, binvrow, inds, ninds, 1.0, cutcoefs, &cutrhs, &cutact, &success, &cutislocal, &cutrank) ); assert(ALLOWLOCAL || !cutislocal); SCIPdebugMessage(" -> success=%u: %g <= %g\n", success, cutact, cutrhs); /* if successful, convert dense cut into sparse row, and add the row as a cut */ if( success && SCIPisFeasGT(scip, cutact, cutrhs) ) { SCIP_VAR** cutvars; SCIP_Real* cutvals; SCIP_Real cutnorm; int cutlen; /* if this is the first successful cut, get the LP solution for all COLUMN variables */ if( varsolvals == NULL ) { int v; SCIP_CALL( SCIPallocBufferArray(scip, &varsolvals, nvars) ); for( v = 0; v < nvars; ++v ) { if( SCIPvarGetStatus(vars[v]) == SCIP_VARSTATUS_COLUMN ) varsolvals[v] = SCIPvarGetLPSol(vars[v]); } } assert(varsolvals != NULL); /* get temporary memory for storing the cut as sparse row */ SCIP_CALL( SCIPallocBufferArray(scip, &cutvars, nvars) ); SCIP_CALL( SCIPallocBufferArray(scip, &cutvals, nvars) ); /* store the cut as sparse row, calculate activity and norm of cut */ SCIP_CALL( storeCutInArrays(scip, nvars, vars, cutcoefs, varsolvals, normtype, cutvars, cutvals, &cutlen, &cutact, &cutnorm) ); SCIPdebugMessage(" -> strong CG cut for <%s>: act=%f, rhs=%f, norm=%f, eff=%f, rank=%d\n", c >= 0 ? SCIPvarGetName(SCIPcolGetVar(cols[c])) : SCIProwGetName(rows[-c-1]), cutact, cutrhs, cutnorm, (cutact - cutrhs)/cutnorm, cutrank); if( SCIPisPositive(scip, cutnorm) && SCIPisEfficacious(scip, (cutact - cutrhs)/cutnorm) ) { SCIP_ROW* cut; char cutname[SCIP_MAXSTRLEN]; /* create the cut */ if( c >= 0 ) (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "scg%d_x%d", SCIPgetNLPs(scip), c); else (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "scg%d_s%d", SCIPgetNLPs(scip), -c-1); SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &cut, sepa, cutname, -SCIPinfinity(scip), cutrhs, cutislocal, FALSE, sepadata->dynamiccuts) ); SCIP_CALL( SCIPaddVarsToRow(scip, cut, cutlen, cutvars, cutvals) ); /*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/ SCIProwChgRank(cut, cutrank); assert(success); #ifdef MAKECUTINTEGRAL /* try to scale the cut to integral values */ SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip), maxdnom, maxscale, MAKECONTINTEGRAL, &success) ); #else #ifdef MAKEINTCUTINTEGRAL /* try to scale the cut to integral values if there are no continuous variables * -> leads to an integral slack variable that can later be used for other cuts */ { int k = 0; while ( k < cutlen && SCIPvarIsIntegral(cutvars[k]) ) ++k; if( k == cutlen ) { SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip), maxdnom, maxscale, MAKECONTINTEGRAL, &success) ); } } #endif #endif #ifndef FORCECUTINTEGRAL success = TRUE; #endif if( success ) { if( !SCIPisCutEfficacious(scip, NULL, cut) ) { SCIPdebugMessage(" -> strong CG cut <%s> no longer efficacious: act=%f, rhs=%f, norm=%f, eff=%f\n", cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut), SCIPgetCutEfficacy(scip, NULL, cut)); /*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/ success = FALSE; } else { SCIP_Bool infeasible; SCIPdebugMessage(" -> found strong CG cut <%s>: act=%f, rhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n", cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut), SCIPgetCutEfficacy(scip, NULL, cut), SCIPgetRowMinCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut)/SCIPgetRowMinCoef(scip, cut)); /*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/ SCIP_CALL( SCIPaddCut(scip, NULL, cut, FALSE, &infeasible) ); if ( infeasible ) *result = SCIP_CUTOFF; else { if( !cutislocal ) { SCIP_CALL( SCIPaddPoolCut(scip, cut) ); } *result = SCIP_SEPARATED; } ncuts++; } } else { SCIPdebugMessage(" -> strong CG cut <%s> couldn't be scaled to integral coefficients: act=%f, rhs=%f, norm=%f, eff=%f\n", cutname, cutact, cutrhs, cutnorm, SCIPgetCutEfficacy(scip, NULL, cut)); } /* release the row */ SCIP_CALL( SCIPreleaseRow(scip, &cut) ); } /* free temporary memory */ SCIPfreeBufferArray(scip, &cutvals); SCIPfreeBufferArray(scip, &cutvars); } } } /* free temporary memory */ SCIPfreeBufferArrayNull(scip, &varsolvals); SCIPfreeBufferArray(scip, &inds); SCIPfreeBufferArray(scip, &binvrow); SCIPfreeBufferArray(scip, &basisind); SCIPfreeBufferArray(scip, &cutcoefs); SCIPdebugMessage("end searching strong CG cuts: found %d cuts\n", ncuts); sepadata->lastncutsfound = SCIPgetNCutsFound(scip); return SCIP_OKAY; }
/** execution method of primal heuristic */ static SCIP_DECL_HEUREXEC(heurExecRounding) /*lint --e{715}*/ { /*lint --e{715}*/ SCIP_HEURDATA* heurdata; SCIP_SOL* sol; SCIP_VAR** lpcands; SCIP_Real* lpcandssol; SCIP_ROW** lprows; SCIP_Real* activities; SCIP_ROW** violrows; int* violrowpos; SCIP_Real obj; SCIP_Real bestroundval; SCIP_Real minobj; int nlpcands; int nlprows; int nfrac; int nviolrows; int c; int r; SCIP_Longint nlps; SCIP_Longint ncalls; SCIP_Longint nsolsfound; SCIP_Longint nnodes; assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0); assert(scip != NULL); assert(result != NULL); assert(SCIPhasCurrentNodeLP(scip)); *result = SCIP_DIDNOTRUN; /* only call heuristic, if an optimal LP solution is at hand */ if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL ) return SCIP_OKAY; /* only call heuristic, if the LP objective value is smaller than the cutoff bound */ if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) ) return SCIP_OKAY; /* get heuristic data */ heurdata = SCIPheurGetData(heur); assert(heurdata != NULL); /* don't call heuristic, if we have already processed the current LP solution */ nlps = SCIPgetNLPs(scip); if( nlps == heurdata->lastlp ) return SCIP_OKAY; heurdata->lastlp = nlps; /* don't call heuristic, if it was not successful enough in the past */ ncalls = SCIPheurGetNCalls(heur); nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + SCIPheurGetNSolsFound(heur); nnodes = SCIPgetNNodes(scip); if( nnodes % ((ncalls/heurdata->successfactor)/(nsolsfound+1)+1) != 0 ) return SCIP_OKAY; /* get fractional variables, that should be integral */ SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, NULL) ); nfrac = nlpcands; /* only call heuristic, if LP solution is fractional */ if( nfrac == 0 ) return SCIP_OKAY; *result = SCIP_DIDNOTFIND; /* get LP rows */ SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) ); SCIPdebugMessage("executing rounding heuristic: %d LP rows, %d fractionals\n", nlprows, nfrac); /* get memory for activities, violated rows, and row violation positions */ SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) ); SCIP_CALL( SCIPallocBufferArray(scip, &violrows, nlprows) ); SCIP_CALL( SCIPallocBufferArray(scip, &violrowpos, nlprows) ); /* get the activities for all globally valid rows; * the rows should be feasible, but due to numerical inaccuracies in the LP solver, they can be violated */ nviolrows = 0; for( r = 0; r < nlprows; ++r ) { SCIP_ROW* row; row = lprows[r]; assert(SCIProwGetLPPos(row) == r); if( !SCIProwIsLocal(row) ) { activities[r] = SCIPgetRowActivity(scip, row); if( SCIPisFeasLT(scip, activities[r], SCIProwGetLhs(row)) || SCIPisFeasGT(scip, activities[r], SCIProwGetRhs(row)) ) { violrows[nviolrows] = row; violrowpos[r] = nviolrows; nviolrows++; } else violrowpos[r] = -1; } } /* get the working solution from heuristic's local data */ sol = heurdata->sol; assert(sol != NULL); /* copy the current LP solution to the working solution */ SCIP_CALL( SCIPlinkLPSol(scip, sol) ); /* calculate the minimal objective value possible after rounding fractional variables */ minobj = SCIPgetSolTransObj(scip, sol); assert(minobj < SCIPgetCutoffbound(scip)); for( c = 0; c < nlpcands; ++c ) { obj = SCIPvarGetObj(lpcands[c]); bestroundval = obj > 0.0 ? SCIPfeasFloor(scip, lpcandssol[c]) : SCIPfeasCeil(scip, lpcandssol[c]); minobj += obj * (bestroundval - lpcandssol[c]); } /* try to round remaining variables in order to become/stay feasible */ while( nfrac > 0 ) { SCIP_VAR* roundvar; SCIP_Real oldsolval; SCIP_Real newsolval; SCIPdebugMessage("rounding heuristic: nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n", nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj)); /* minobj < SCIPgetCutoffbound(scip) should be true, otherwise the rounding variable selection * should have returned NULL. Due to possible cancellation we use SCIPisLE. */ assert( SCIPisLE(scip, minobj, SCIPgetCutoffbound(scip)) ); /* choose next variable to process: * - if a violated row exists, round a variable decreasing the violation, that has least impact on other rows * - otherwise, round a variable, that has strongest devastating impact on rows in opposite direction */ if( nviolrows > 0 ) { SCIP_ROW* row; int rowpos; row = violrows[nviolrows-1]; rowpos = SCIProwGetLPPos(row); assert(0 <= rowpos && rowpos < nlprows); assert(violrowpos[rowpos] == nviolrows-1); SCIPdebugMessage("rounding heuristic: try to fix violated row <%s>: %g <= %g <= %g\n", SCIProwGetName(row), SCIProwGetLhs(row), activities[rowpos], SCIProwGetRhs(row)); if( SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row)) ) { /* lhs is violated: select a variable rounding, that increases the activity */ SCIP_CALL( selectIncreaseRounding(scip, sol, minobj, row, &roundvar, &oldsolval, &newsolval) ); } else { assert(SCIPisFeasGT(scip, activities[rowpos], SCIProwGetRhs(row))); /* rhs is violated: select a variable rounding, that decreases the activity */ SCIP_CALL( selectDecreaseRounding(scip, sol, minobj, row, &roundvar, &oldsolval, &newsolval) ); } } else { SCIPdebugMessage("rounding heuristic: search rounding variable and try to stay feasible\n"); SCIP_CALL( selectEssentialRounding(scip, sol, minobj, lpcands, nlpcands, &roundvar, &oldsolval, &newsolval) ); } /* check, whether rounding was possible */ if( roundvar == NULL ) { SCIPdebugMessage("rounding heuristic: -> didn't find a rounding variable\n"); break; } SCIPdebugMessage("rounding heuristic: -> round var <%s>, oldval=%g, newval=%g, obj=%g\n", SCIPvarGetName(roundvar), oldsolval, newsolval, SCIPvarGetObj(roundvar)); /* update row activities of globally valid rows */ SCIP_CALL( updateActivities(scip, activities, violrows, violrowpos, &nviolrows, nlprows, roundvar, oldsolval, newsolval) ); /* store new solution value and decrease fractionality counter */ SCIP_CALL( SCIPsetSolVal(scip, sol, roundvar, newsolval) ); nfrac--; /* update minimal objective value possible after rounding remaining variables */ obj = SCIPvarGetObj(roundvar); if( obj > 0.0 && newsolval > oldsolval ) minobj += obj; else if( obj < 0.0 && newsolval < oldsolval ) minobj -= obj; SCIPdebugMessage("rounding heuristic: -> nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n", nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj)); } /* check, if the new solution is feasible */ if( nfrac == 0 && nviolrows == 0 ) { SCIP_Bool stored; /* check solution for feasibility, and add it to solution store if possible * neither integrality nor feasibility of LP rows has to be checked, because this is already * done in the rounding heuristic itself; however, be better check feasibility of LP rows, * because of numerical problems with activity updating */ SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, FALSE, TRUE, &stored) ); if( stored ) { #ifdef SCIP_DEBUG SCIPdebugMessage("found feasible rounded solution:\n"); SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) ); #endif *result = SCIP_FOUNDSOL; } } /* free memory buffers */ SCIPfreeBufferArray(scip, &violrowpos); SCIPfreeBufferArray(scip, &violrows); SCIPfreeBufferArray(scip, &activities); return SCIP_OKAY; }