/** output method of display column to output file stream 'file' */ static SCIP_DECL_DISPOUTPUT(SCIPdispOutputMaxdepth) { /*lint --e{715}*/ assert(disp != NULL); assert(strcmp(SCIPdispGetName(disp), DISP_NAME_MAXDEPTH) == 0); assert(scip != NULL); SCIPdispInt(SCIPgetMessagehdlr(scip), file, SCIPgetMaxDepth(scip), DISP_WIDT_MAXDEPTH); return SCIP_OKAY; }
/** execution method of primal heuristic */ static SCIP_DECL_HEUREXEC(heurExecIntdiving) /*lint --e{715}*/ { /*lint --e{715}*/ SCIP_HEURDATA* heurdata; SCIP_LPSOLSTAT lpsolstat; SCIP_VAR** pseudocands; SCIP_VAR** fixcands; SCIP_Real* fixcandscores; SCIP_Real searchubbound; SCIP_Real searchavgbound; SCIP_Real searchbound; SCIP_Real objval; SCIP_Bool lperror; SCIP_Bool cutoff; SCIP_Bool backtracked; SCIP_Longint ncalls; SCIP_Longint nsolsfound; SCIP_Longint nlpiterations; SCIP_Longint maxnlpiterations; int nfixcands; int nbinfixcands; int depth; int maxdepth; int maxdivedepth; int divedepth; int nextcand; int c; assert(heur != NULL); assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0); assert(scip != NULL); assert(result != NULL); assert(SCIPhasCurrentNodeLP(scip)); *result = SCIP_DELAYED; /* 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; /* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */ if( !SCIPisLPSolBasic(scip) ) return SCIP_OKAY; /* don't dive two times at the same node */ if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 ) return SCIP_OKAY; *result = SCIP_DIDNOTRUN; /* get heuristic's data */ heurdata = SCIPheurGetData(heur); assert(heurdata != NULL); /* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */ depth = SCIPgetDepth(scip); maxdepth = SCIPgetMaxDepth(scip); maxdepth = MAX(maxdepth, 100); if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth ) return SCIP_OKAY; /* calculate the maximal number of LP iterations until heuristic is aborted */ nlpiterations = SCIPgetNNodeLPIterations(scip); ncalls = SCIPheurGetNCalls(heur); nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess; maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations); maxnlpiterations += heurdata->maxlpiterofs; /* don't try to dive, if we took too many LP iterations during diving */ if( heurdata->nlpiterations >= maxnlpiterations ) return SCIP_OKAY; /* allow at least a certain number of LP iterations in this dive */ maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER); /* get unfixed integer variables */ SCIP_CALL( SCIPgetPseudoBranchCands(scip, &pseudocands, &nfixcands, NULL) ); /* don't try to dive, if there are no fractional variables */ if( nfixcands == 0 ) return SCIP_OKAY; /* calculate the objective search bound */ if( SCIPgetNSolsFound(scip) == 0 ) { if( heurdata->maxdiveubquotnosol > 0.0 ) searchubbound = SCIPgetLowerbound(scip) + heurdata->maxdiveubquotnosol * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip)); else searchubbound = SCIPinfinity(scip); if( heurdata->maxdiveavgquotnosol > 0.0 ) searchavgbound = SCIPgetLowerbound(scip) + heurdata->maxdiveavgquotnosol * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip)); else searchavgbound = SCIPinfinity(scip); } else { if( heurdata->maxdiveubquot > 0.0 ) searchubbound = SCIPgetLowerbound(scip) + heurdata->maxdiveubquot * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip)); else searchubbound = SCIPinfinity(scip); if( heurdata->maxdiveavgquot > 0.0 ) searchavgbound = SCIPgetLowerbound(scip) + heurdata->maxdiveavgquot * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip)); else searchavgbound = SCIPinfinity(scip); } searchbound = MIN(searchubbound, searchavgbound); if( SCIPisObjIntegral(scip) ) searchbound = SCIPceil(scip, searchbound); /* calculate the maximal diving depth: 10 * min{number of integer variables, max depth} */ maxdivedepth = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip); maxdivedepth = MIN(maxdivedepth, maxdepth); maxdivedepth *= 10; *result = SCIP_DIDNOTFIND; /* start diving */ SCIP_CALL( SCIPstartProbing(scip) ); /* enables collection of variable statistics during probing */ SCIPenableVarHistory(scip); SCIPdebugMessage("(node %" SCIP_LONGINT_FORMAT ") executing intdiving heuristic: depth=%d, %d non-fixed, dualbound=%g, searchbound=%g\n", SCIPgetNNodes(scip), SCIPgetDepth(scip), nfixcands, SCIPgetDualbound(scip), SCIPretransformObj(scip, searchbound)); /* copy the pseudo candidates into own array, because we want to reorder them */ SCIP_CALL( SCIPduplicateBufferArray(scip, &fixcands, pseudocands, nfixcands) ); /* sort non-fixed variables by non-increasing inference score, but prefer binaries over integers in any case */ SCIP_CALL( SCIPallocBufferArray(scip, &fixcandscores, nfixcands) ); nbinfixcands = 0; for( c = 0; c < nfixcands; ++c ) { SCIP_VAR* var; SCIP_Real score; int colveclen; int left; int right; int i; assert(c >= nbinfixcands); var = fixcands[c]; assert(SCIPvarIsIntegral(var)); colveclen = (SCIPvarGetStatus(var) == SCIP_VARSTATUS_COLUMN ? SCIPcolGetNNonz(SCIPvarGetCol(var)) : 0); if( SCIPvarIsBinary(var) ) { score = 500.0 * SCIPvarGetNCliques(var, TRUE) + 100.0 * SCIPvarGetNImpls(var, TRUE) + SCIPgetVarAvgInferenceScore(scip, var) + (SCIP_Real)colveclen/100.0; /* shift the non-binary variables one slot to the right */ for( i = c; i > nbinfixcands; --i ) { fixcands[i] = fixcands[i-1]; fixcandscores[i] = fixcandscores[i-1]; } /* put the new candidate into the first nbinfixcands slot */ left = 0; right = nbinfixcands; nbinfixcands++; } else { score = 5.0 * (SCIPvarGetNCliques(var, FALSE) + SCIPvarGetNCliques(var, TRUE)) + SCIPvarGetNImpls(var, FALSE) + SCIPvarGetNImpls(var, TRUE) + SCIPgetVarAvgInferenceScore(scip, var) + (SCIP_Real)colveclen/10000.0; /* put the new candidate in the slots after the binary candidates */ left = nbinfixcands; right = c; } for( i = right; i > left && score > fixcandscores[i-1]; --i ) { fixcands[i] = fixcands[i-1]; fixcandscores[i] = fixcandscores[i-1]; } fixcands[i] = var; fixcandscores[i] = score; SCIPdebugMessage(" <%s>: ncliques=%d/%d, nimpls=%d/%d, inferencescore=%g, colveclen=%d -> score=%g\n", SCIPvarGetName(var), SCIPvarGetNCliques(var, FALSE), SCIPvarGetNCliques(var, TRUE), SCIPvarGetNImpls(var, FALSE), SCIPvarGetNImpls(var, TRUE), SCIPgetVarAvgInferenceScore(scip, var), colveclen, score); } SCIPfreeBufferArray(scip, &fixcandscores); /* get LP objective value */ lpsolstat = SCIP_LPSOLSTAT_OPTIMAL; objval = SCIPgetLPObjval(scip); /* dive as long we are in the given objective, depth and iteration limits, but if possible, we dive at least with * the depth 10 */ lperror = FALSE; cutoff = FALSE; divedepth = 0; nextcand = 0; while( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL && (divedepth < 10 || (divedepth < maxdivedepth && heurdata->nlpiterations < maxnlpiterations && objval < searchbound)) && !SCIPisStopped(scip) ) { SCIP_VAR* var; SCIP_Real bestsolval; SCIP_Real bestfixval; int bestcand; SCIP_Longint nnewlpiterations; SCIP_Longint nnewdomreds; /* open a new probing node if this will not exceed the maximal tree depth, otherwise stop here */ if( SCIPgetDepth(scip) < SCIPgetDepthLimit(scip) ) { SCIP_CALL( SCIPnewProbingNode(scip) ); divedepth++; } else break; nnewlpiterations = 0; nnewdomreds = 0; /* fix binary variable that is closest to 1 in the LP solution to 1; * if all binary variables are fixed, fix integer variable with least fractionality in LP solution */ bestcand = -1; bestsolval = -1.0; bestfixval = 1.0; /* look in the binary variables for fixing candidates */ for( c = nextcand; c < nbinfixcands; ++c ) { SCIP_Real solval; var = fixcands[c]; /* ignore already fixed variables */ if( var == NULL ) continue; if( SCIPvarGetLbLocal(var) > 0.5 || SCIPvarGetUbLocal(var) < 0.5 ) { fixcands[c] = NULL; continue; } /* get the LP solution value */ solval = SCIPvarGetLPSol(var); if( solval > bestsolval ) { bestcand = c; bestfixval = 1.0; bestsolval = solval; if( SCIPisGE(scip, bestsolval, 1.0) ) { /* we found an unfixed binary variable with LP solution value of 1.0 - there cannot be a better candidate */ break; } else if( SCIPisLE(scip, bestsolval, 0.0) ) { /* the variable is currently at 0.0 - this is the only situation where we want to fix it to 0.0 */ bestfixval = 0.0; } } } /* if all binary variables are fixed, look in the integer variables for a fixing candidate */ if( bestcand == -1 ) { SCIP_Real bestfrac; bestfrac = SCIP_INVALID; for( c = MAX(nextcand, nbinfixcands); c < nfixcands; ++c ) { SCIP_Real solval; SCIP_Real frac; var = fixcands[c]; /* ignore already fixed variables */ if( var == NULL ) continue; if( SCIPvarGetUbLocal(var) - SCIPvarGetLbLocal(var) < 0.5 ) { fixcands[c] = NULL; continue; } /* get the LP solution value */ solval = SCIPvarGetLPSol(var); frac = SCIPfrac(scip, solval); /* ignore integer variables that are currently integral */ if( SCIPisFeasFracIntegral(scip, frac) ) continue; if( frac < bestfrac ) { bestcand = c; bestsolval = solval; bestfrac = frac; bestfixval = SCIPfloor(scip, bestsolval + 0.5); if( SCIPisZero(scip, bestfrac) ) { /* we found an unfixed integer variable with integral LP solution value */ break; } } } } assert(-1 <= bestcand && bestcand < nfixcands); /* if there is no unfixed candidate left, we are done */ if( bestcand == -1 ) break; var = fixcands[bestcand]; assert(var != NULL); assert(SCIPvarIsIntegral(var)); assert(SCIPvarGetUbLocal(var) - SCIPvarGetLbLocal(var) > 0.5); assert(SCIPisGE(scip, bestfixval, SCIPvarGetLbLocal(var))); assert(SCIPisLE(scip, bestfixval, SCIPvarGetUbLocal(var))); backtracked = FALSE; do { /* if the variable is already fixed or if the solution value is outside the domain, numerical troubles may have * occured or variable was fixed by propagation while backtracking => Abort diving! */ if( SCIPvarGetLbLocal(var) >= SCIPvarGetUbLocal(var) - 0.5 ) { SCIPdebugMessage("Selected variable <%s> already fixed to [%g,%g], diving aborted \n", SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var)); cutoff = TRUE; break; } if( SCIPisFeasLT(scip, bestfixval, SCIPvarGetLbLocal(var)) || SCIPisFeasGT(scip, bestfixval, SCIPvarGetUbLocal(var)) ) { SCIPdebugMessage("selected variable's <%s> solution value is outside the domain [%g,%g] (solval: %.9f), diving aborted\n", SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), bestfixval); assert(backtracked); break; } /* apply fixing of best candidate */ SCIPdebugMessage(" dive %d/%d, LP iter %" SCIP_LONGINT_FORMAT "/%" SCIP_LONGINT_FORMAT ", %d unfixed: var <%s>, sol=%g, oldbounds=[%g,%g], fixed to %g\n", divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations, SCIPgetNPseudoBranchCands(scip), SCIPvarGetName(var), bestsolval, SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), bestfixval); SCIP_CALL( SCIPfixVarProbing(scip, var, bestfixval) ); /* apply domain propagation */ SCIP_CALL( SCIPpropagateProbing(scip, 0, &cutoff, &nnewdomreds) ); if( !cutoff ) { /* if the best candidate was just fixed to its LP value and no domain reduction was found, the LP solution * stays valid, and the LP does not need to be resolved */ if( nnewdomreds > 0 || !SCIPisEQ(scip, bestsolval, bestfixval) ) { /* resolve the diving LP */ /* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic. * Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop. */ #ifdef NDEBUG SCIP_RETCODE retstat; nlpiterations = SCIPgetNLPIterations(scip); retstat = SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff); if( retstat != SCIP_OKAY ) { SCIPwarningMessage(scip, "Error while solving LP in Intdiving heuristic; LP solve terminated with code <%d>\n",retstat); } #else nlpiterations = SCIPgetNLPIterations(scip); SCIP_CALL( SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff) ); #endif if( lperror ) break; /* update iteration count */ nnewlpiterations = SCIPgetNLPIterations(scip) - nlpiterations; heurdata->nlpiterations += nnewlpiterations; /* get LP solution status */ lpsolstat = SCIPgetLPSolstat(scip); assert(cutoff || (lpsolstat != SCIP_LPSOLSTAT_OBJLIMIT && lpsolstat != SCIP_LPSOLSTAT_INFEASIBLE && (lpsolstat != SCIP_LPSOLSTAT_OPTIMAL || SCIPisLT(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip))))); } } /* perform backtracking if a cutoff was detected */ if( cutoff && !backtracked && heurdata->backtrack ) { SCIPdebugMessage(" *** cutoff detected at level %d - backtracking\n", SCIPgetProbingDepth(scip)); SCIP_CALL( SCIPbacktrackProbing(scip, SCIPgetProbingDepth(scip)-1) ); /* after backtracking there has to be at least one open node without exceeding the maximal tree depth */ assert(SCIPgetDepthLimit(scip) > SCIPgetDepth(scip)); SCIP_CALL( SCIPnewProbingNode(scip) ); bestfixval = SCIPvarIsBinary(var) ? 1.0 - bestfixval : (SCIPisGT(scip, bestsolval, bestfixval) && SCIPisFeasLE(scip, bestfixval + 1, SCIPvarGetUbLocal(var)) ? bestfixval + 1 : bestfixval - 1); backtracked = TRUE; } else backtracked = FALSE; } while( backtracked ); if( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL ) { SCIP_Bool success; /* get new objective value */ objval = SCIPgetLPObjval(scip); if( nnewlpiterations > 0 || !SCIPisEQ(scip, bestsolval, bestfixval) ) { /* we must start again with the first candidate, since the LP solution changed */ nextcand = 0; /* create solution from diving LP and try to round it */ SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) ); SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) ); if( success ) { SCIPdebugMessage("intdiving found roundable primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol)); /* try to add solution to SCIP */ SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) ); /* check, if solution was feasible and good enough */ if( success ) { SCIPdebugMessage(" -> solution was feasible and good enough\n"); *result = SCIP_FOUNDSOL; } } } else nextcand = bestcand+1; /* continue with the next candidate in the following loop */ } SCIPdebugMessage(" -> lpsolstat=%d, objval=%g/%g\n", lpsolstat, objval, searchbound); } /* free temporary memory */ SCIPfreeBufferArray(scip, &fixcands); /* end diving */ SCIP_CALL( SCIPendProbing(scip) ); if( *result == SCIP_FOUNDSOL ) heurdata->nsuccess++; SCIPdebugMessage("intdiving heuristic finished\n"); return SCIP_OKAY; }
/** node selection method of node selector */ static SCIP_DECL_NODESELSELECT(nodeselSelectBfs) { /*lint --e{715}*/ SCIP_NODESELDATA* nodeseldata; int minplungedepth; int maxplungedepth; int plungedepth; SCIP_Real maxplungequot; assert(nodesel != NULL); assert(strcmp(SCIPnodeselGetName(nodesel), NODESEL_NAME) == 0); assert(scip != NULL); assert(selnode != NULL); *selnode = NULL; /* get node selector user data */ nodeseldata = SCIPnodeselGetData(nodesel); assert(nodeseldata != NULL); /* calculate minimal and maximal plunging depth */ minplungedepth = nodeseldata->minplungedepth; maxplungedepth = nodeseldata->maxplungedepth; maxplungequot = nodeseldata->maxplungequot; if( minplungedepth == -1 ) { minplungedepth = SCIPgetMaxDepth(scip)/10; if( SCIPgetNStrongbranchLPIterations(scip) > 2*SCIPgetNNodeLPIterations(scip) ) minplungedepth += 10; if( maxplungedepth >= 0 ) minplungedepth = MIN(minplungedepth, maxplungedepth); } if( maxplungedepth == -1 ) maxplungedepth = SCIPgetMaxDepth(scip)/2; maxplungedepth = MAX(maxplungedepth, minplungedepth); /* check, if we exceeded the maximal plunging depth */ plungedepth = SCIPgetPlungeDepth(scip); if( plungedepth > maxplungedepth ) { /* we don't want to plunge again: select best node from the tree */ SCIPdebugMessage("plungedepth: [%d,%d], cur: %d -> abort plunging\n", minplungedepth, maxplungedepth, plungedepth); *selnode = SCIPgetBestNode(scip); SCIPdebugMessage(" -> best node : lower=%g\n", *selnode != NULL ? SCIPnodeGetLowerbound(*selnode) : SCIPinfinity(scip)); } else { SCIP_NODE* node; SCIP_Real maxbound; /* check, if plunging is forced at the current depth */ if( plungedepth < minplungedepth ) { maxbound = SCIPinfinity(scip); SCIPdebugMessage("plungedepth: [%d,%d], cur: %d => maxbound: infinity\n", minplungedepth, maxplungedepth, plungedepth); } else { SCIP_Real lowerbound; SCIP_Real cutoffbound; /* get global lower and cutoff bound */ lowerbound = SCIPgetLowerbound(scip); cutoffbound = SCIPgetCutoffbound(scip); /* if we didn't find a solution yet, the cutoff bound is usually very bad: * use only 20% of the gap as cutoff bound */ if( SCIPgetNSolsFound(scip) == 0 ) cutoffbound = lowerbound + 0.2 * (cutoffbound - lowerbound); /* calculate maximal plunging bound */ maxbound = lowerbound + maxplungequot * (cutoffbound - lowerbound); SCIPdebugMessage("plungedepth: [%d,%d], cur: %d, bounds: [%g,%g], maxbound: %g\n", minplungedepth, maxplungedepth, plungedepth, lowerbound, cutoffbound, maxbound); } /* we want to plunge again: prefer children over siblings, and siblings over leaves, * but only select a child or sibling, if its dual bound is small enough; * prefer using nodes with higher node selection priority assigned by the branching rule */ node = SCIPgetPrioChild(scip); if( node != NULL && SCIPnodeGetLowerbound(node) < maxbound ) { *selnode = node; SCIPdebugMessage(" -> selected prio child: lower=%g\n", SCIPnodeGetLowerbound(*selnode)); } else { node = SCIPgetBestChild(scip); if( node != NULL && SCIPnodeGetLowerbound(node) < maxbound ) { *selnode = node; SCIPdebugMessage(" -> selected best child: lower=%g\n", SCIPnodeGetLowerbound(*selnode)); } else { node = SCIPgetPrioSibling(scip); if( node != NULL && SCIPnodeGetLowerbound(node) < maxbound ) { *selnode = node; SCIPdebugMessage(" -> selected prio sibling: lower=%g\n", SCIPnodeGetLowerbound(*selnode)); } else { node = SCIPgetBestSibling(scip); if( node != NULL && SCIPnodeGetLowerbound(node) < maxbound ) { *selnode = node; SCIPdebugMessage(" -> selected best sibling: lower=%g\n", SCIPnodeGetLowerbound(*selnode)); } else { *selnode = SCIPgetBestNode(scip); SCIPdebugMessage(" -> selected best leaf: lower=%g\n", *selnode != NULL ? SCIPnodeGetLowerbound(*selnode) : SCIPinfinity(scip)); } } } } } return SCIP_OKAY; }
/** execution method of primal heuristic */ static SCIP_DECL_HEUREXEC(heurExecActconsdiving) /*lint --e{715}*/ { /*lint --e{715}*/ SCIP_HEURDATA* heurdata; SCIP_LPSOLSTAT lpsolstat; SCIP_VAR* var; SCIP_VAR** lpcands; SCIP_Real* lpcandssol; SCIP_Real* lpcandsfrac; SCIP_Real searchubbound; SCIP_Real searchavgbound; SCIP_Real searchbound; SCIP_Real objval; SCIP_Real oldobjval; SCIP_Real frac; SCIP_Real bestfrac; SCIP_Bool bestcandmayrounddown; SCIP_Bool bestcandmayroundup; SCIP_Bool bestcandroundup; SCIP_Bool mayrounddown; SCIP_Bool mayroundup; SCIP_Bool roundup; SCIP_Bool lperror; SCIP_Bool cutoff; SCIP_Bool backtracked; SCIP_Longint ncalls; SCIP_Longint nsolsfound; SCIP_Longint nlpiterations; SCIP_Longint maxnlpiterations; int nlpcands; int startnlpcands; int depth; int maxdepth; int maxdivedepth; int divedepth; SCIP_Real actscore; SCIP_Real downscore; SCIP_Real upscore; SCIP_Real bestactscore; int bestcand; int c; assert(heur != NULL); assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0); assert(scip != NULL); assert(result != NULL); assert(SCIPhasCurrentNodeLP(scip)); *result = SCIP_DELAYED; /* 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; /* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */ if( !SCIPisLPSolBasic(scip) ) return SCIP_OKAY; /* don't dive two times at the same node */ if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 ) return SCIP_OKAY; *result = SCIP_DIDNOTRUN; /* get heuristic's data */ heurdata = SCIPheurGetData(heur); assert(heurdata != NULL); /* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */ depth = SCIPgetDepth(scip); maxdepth = SCIPgetMaxDepth(scip); maxdepth = MAX(maxdepth, 30); if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth ) return SCIP_OKAY; /* calculate the maximal number of LP iterations until heuristic is aborted */ nlpiterations = SCIPgetNNodeLPIterations(scip); ncalls = SCIPheurGetNCalls(heur); nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess; maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations); maxnlpiterations += heurdata->maxlpiterofs; /* don't try to dive, if we took too many LP iterations during diving */ if( heurdata->nlpiterations >= maxnlpiterations ) return SCIP_OKAY; /* allow at least a certain number of LP iterations in this dive */ maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER); /* get fractional variables that should be integral */ SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) ); /* don't try to dive, if there are no fractional variables */ if( nlpcands == 0 ) return SCIP_OKAY; /* calculate the objective search bound */ if( SCIPgetNSolsFound(scip) == 0 ) { if( heurdata->maxdiveubquotnosol > 0.0 ) searchubbound = SCIPgetLowerbound(scip) + heurdata->maxdiveubquotnosol * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip)); else searchubbound = SCIPinfinity(scip); if( heurdata->maxdiveavgquotnosol > 0.0 ) searchavgbound = SCIPgetLowerbound(scip) + heurdata->maxdiveavgquotnosol * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip)); else searchavgbound = SCIPinfinity(scip); } else { if( heurdata->maxdiveubquot > 0.0 ) searchubbound = SCIPgetLowerbound(scip) + heurdata->maxdiveubquot * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip)); else searchubbound = SCIPinfinity(scip); if( heurdata->maxdiveavgquot > 0.0 ) searchavgbound = SCIPgetLowerbound(scip) + heurdata->maxdiveavgquot * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip)); else searchavgbound = SCIPinfinity(scip); } searchbound = MIN(searchubbound, searchavgbound); if( SCIPisObjIntegral(scip) ) searchbound = SCIPceil(scip, searchbound); /* calculate the maximal diving depth: 10 * min{number of integer variables, max depth} */ maxdivedepth = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip); maxdivedepth = MIN(maxdivedepth, maxdepth); maxdivedepth *= 10; *result = SCIP_DIDNOTFIND; /* start diving */ SCIP_CALL( SCIPstartProbing(scip) ); /* enables collection of variable statistics during probing */ SCIPenableVarHistory(scip); /* get LP objective value */ lpsolstat = SCIP_LPSOLSTAT_OPTIMAL; objval = SCIPgetLPObjval(scip); SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") executing actconsdiving heuristic: depth=%d, %d fractionals, dualbound=%g, avgbound=%g, cutoffbound=%g, searchbound=%g\n", SCIPgetNNodes(scip), SCIPgetDepth(scip), nlpcands, SCIPgetDualbound(scip), SCIPgetAvgDualbound(scip), SCIPretransformObj(scip, SCIPgetCutoffbound(scip)), SCIPretransformObj(scip, searchbound)); /* dive as long we are in the given objective, depth and iteration limits and fractional variables exist, but * - if possible, we dive at least with the depth 10 * - if the number of fractional variables decreased at least with 1 variable per 2 dive depths, we continue diving */ lperror = FALSE; cutoff = FALSE; divedepth = 0; bestcandmayrounddown = FALSE; bestcandmayroundup = FALSE; startnlpcands = nlpcands; while( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL && nlpcands > 0 && (divedepth < 10 || nlpcands <= startnlpcands - divedepth/2 || (divedepth < maxdivedepth && heurdata->nlpiterations < maxnlpiterations && objval < searchbound)) && !SCIPisStopped(scip) ) { divedepth++; SCIP_CALL( SCIPnewProbingNode(scip) ); /* choose variable fixing: * - prefer variables that may not be rounded without destroying LP feasibility: * - of these variables, round variable with least number of locks in corresponding direction * - if all remaining fractional variables may be rounded without destroying LP feasibility: * - round variable with least number of locks in opposite of its feasible rounding direction */ bestcand = -1; bestactscore = -1.0; bestfrac = SCIP_INVALID; bestcandmayrounddown = TRUE; bestcandmayroundup = TRUE; bestcandroundup = FALSE; for( c = 0; c < nlpcands; ++c ) { var = lpcands[c]; mayrounddown = SCIPvarMayRoundDown(var); mayroundup = SCIPvarMayRoundUp(var); frac = lpcandsfrac[c]; if( mayrounddown || mayroundup ) { /* the candidate may be rounded: choose this candidate only, if the best candidate may also be rounded */ if( bestcandmayrounddown || bestcandmayroundup ) { /* choose rounding direction: * - if variable may be rounded in both directions, round corresponding to the fractionality * - otherwise, round in the infeasible direction, because feasible direction is tried by rounding * the current fractional solution */ if( mayrounddown && mayroundup ) roundup = (frac > 0.5); else roundup = mayrounddown; if( roundup ) frac = 1.0 - frac; actscore = getNActiveConsScore(scip, var, &downscore, &upscore); /* penalize too small fractions */ if( frac < 0.01 ) actscore *= 0.01; /* prefer decisions on binary variables */ if( !SCIPvarIsBinary(var) ) actscore *= 0.01; /* check, if candidate is new best candidate */ assert(0.0 < frac && frac < 1.0); if( SCIPisGT(scip, actscore, bestactscore) || (SCIPisGE(scip, actscore, bestactscore) && frac < bestfrac) ) { bestcand = c; bestactscore = actscore; bestfrac = frac; bestcandmayrounddown = mayrounddown; bestcandmayroundup = mayroundup; bestcandroundup = roundup; } } } else { /* the candidate may not be rounded */ actscore = getNActiveConsScore(scip, var, &downscore, &upscore); roundup = (downscore < upscore); if( roundup ) frac = 1.0 - frac; /* penalize too small fractions */ if( frac < 0.01 ) actscore *= 0.01; /* prefer decisions on binary variables */ if( !SCIPvarIsBinary(var) ) actscore *= 0.01; /* check, if candidate is new best candidate: prefer unroundable candidates in any case */ assert(0.0 < frac && frac < 1.0); if( bestcandmayrounddown || bestcandmayroundup || SCIPisGT(scip, actscore, bestactscore) || (SCIPisGE(scip, actscore, bestactscore) && frac < bestfrac) ) { bestcand = c; bestactscore = actscore; bestfrac = frac; bestcandmayrounddown = FALSE; bestcandmayroundup = FALSE; bestcandroundup = roundup; } assert(bestfrac < SCIP_INVALID); } } assert(bestcand != -1); /* if all candidates are roundable, try to round the solution */ if( bestcandmayrounddown || bestcandmayroundup ) { SCIP_Bool success; /* create solution from diving LP and try to round it */ SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) ); SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) ); if( success ) { SCIPdebugMessage("actconsdiving found roundable primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol)); /* try to add solution to SCIP */ SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) ); /* check, if solution was feasible and good enough */ if( success ) { SCIPdebugMessage(" -> solution was feasible and good enough\n"); *result = SCIP_FOUNDSOL; } } } assert(bestcand != -1); var = lpcands[bestcand]; backtracked = FALSE; do { /* if the variable is already fixed or if the solution value is outside the domain, numerical troubles may have * occured or variable was fixed by propagation while backtracking => Abort diving! */ if( SCIPvarGetLbLocal(var) >= SCIPvarGetUbLocal(var) - 0.5 ) { SCIPdebugMessage("Selected variable <%s> already fixed to [%g,%g] (solval: %.9f), diving aborted \n", SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), lpcandssol[bestcand]); cutoff = TRUE; break; } if( SCIPisFeasLT(scip, lpcandssol[bestcand], SCIPvarGetLbLocal(var)) || SCIPisFeasGT(scip, lpcandssol[bestcand], SCIPvarGetUbLocal(var)) ) { SCIPdebugMessage("selected variable's <%s> solution value is outside the domain [%g,%g] (solval: %.9f), diving aborted\n", SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), lpcandssol[bestcand]); assert(backtracked); break; } /* apply rounding of best candidate */ if( bestcandroundup == !backtracked ) { /* round variable up */ SCIPdebugMessage(" dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT": var <%s>, round=%u/%u, sol=%g, oldbounds=[%g,%g], newbounds=[%g,%g]\n", divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations, SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup, lpcandssol[bestcand], SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), SCIPfeasCeil(scip, lpcandssol[bestcand]), SCIPvarGetUbLocal(var)); SCIP_CALL( SCIPchgVarLbProbing(scip, var, SCIPfeasCeil(scip, lpcandssol[bestcand])) ); } else { /* round variable down */ SCIPdebugMessage(" dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT": var <%s>, round=%u/%u, sol=%g, oldbounds=[%g,%g], newbounds=[%g,%g]\n", divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations, SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup, lpcandssol[bestcand], SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), SCIPvarGetLbLocal(var), SCIPfeasFloor(scip, lpcandssol[bestcand])); SCIP_CALL( SCIPchgVarUbProbing(scip, lpcands[bestcand], SCIPfeasFloor(scip, lpcandssol[bestcand])) ); } /* apply domain propagation */ SCIP_CALL( SCIPpropagateProbing(scip, 0, &cutoff, NULL) ); if( !cutoff ) { /* resolve the diving LP */ /* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic. * Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop. */ #ifdef NDEBUG SCIP_RETCODE retstat; nlpiterations = SCIPgetNLPIterations(scip); retstat = SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff); if( retstat != SCIP_OKAY ) { SCIPwarningMessage(scip, "Error while solving LP in Actconsdiving heuristic; LP solve terminated with code <%d>\n",retstat); } #else nlpiterations = SCIPgetNLPIterations(scip); SCIP_CALL( SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff) ); #endif if( lperror ) break; /* update iteration count */ heurdata->nlpiterations += SCIPgetNLPIterations(scip) - nlpiterations; /* get LP solution status, objective value, and fractional variables, that should be integral */ lpsolstat = SCIPgetLPSolstat(scip); assert(cutoff || (lpsolstat != SCIP_LPSOLSTAT_OBJLIMIT && lpsolstat != SCIP_LPSOLSTAT_INFEASIBLE && (lpsolstat != SCIP_LPSOLSTAT_OPTIMAL || SCIPisLT(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip))))); } /* perform backtracking if a cutoff was detected */ if( cutoff && !backtracked && heurdata->backtrack ) { SCIPdebugMessage(" *** cutoff detected at level %d - backtracking\n", SCIPgetProbingDepth(scip)); SCIP_CALL( SCIPbacktrackProbing(scip, SCIPgetProbingDepth(scip)-1) ); SCIP_CALL( SCIPnewProbingNode(scip) ); backtracked = TRUE; } else backtracked = FALSE; } while( backtracked ); if( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL ) { /* get new objective value */ oldobjval = objval; objval = SCIPgetLPObjval(scip); /* update pseudo cost values */ if( SCIPisGT(scip, objval, oldobjval) ) { if( bestcandroundup ) { SCIP_CALL( SCIPupdateVarPseudocost(scip, lpcands[bestcand], 1.0-lpcandsfrac[bestcand], objval - oldobjval, 1.0) ); } else { SCIP_CALL( SCIPupdateVarPseudocost(scip, lpcands[bestcand], 0.0-lpcandsfrac[bestcand], objval - oldobjval, 1.0) ); } } /* get new fractional variables */ SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) ); } SCIPdebugMessage(" -> lpsolstat=%d, objval=%g/%g, nfrac=%d\n", lpsolstat, objval, searchbound, nlpcands); } /* check if a solution has been found */ if( nlpcands == 0 && !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL ) { SCIP_Bool success; /* create solution from diving LP */ SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) ); SCIPdebugMessage("actconsdiving found primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol)); /* try to add solution to SCIP */ SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) ); /* check, if solution was feasible and good enough */ if( success ) { SCIPdebugMessage(" -> solution was feasible and good enough\n"); *result = SCIP_FOUNDSOL; } } /* end diving */ SCIP_CALL( SCIPendProbing(scip) ); if( *result == SCIP_FOUNDSOL ) heurdata->nsuccess++; SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") finished actconsdiving heuristic: %d fractionals, dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT", objval=%g/%g, lpsolstat=%d, cutoff=%u\n", SCIPgetNNodes(scip), nlpcands, divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations, SCIPretransformObj(scip, objval), SCIPretransformObj(scip, searchbound), lpsolstat, cutoff); return SCIP_OKAY; }
/** execution method of primal heuristic */ static SCIP_DECL_HEUREXEC(heurExecObjpscostdiving) /*lint --e{715}*/ { /*lint --e{715}*/ SCIP_HEURDATA* heurdata; SCIP_LPSOLSTAT lpsolstat; SCIP_VAR* var; SCIP_VAR** lpcands; SCIP_Real* lpcandssol; SCIP_Real* lpcandsfrac; SCIP_Real primsol; SCIP_Real frac; SCIP_Real pscostquot; SCIP_Real bestpscostquot; SCIP_Real oldobj; SCIP_Real newobj; SCIP_Real objscale; SCIP_Bool bestcandmayrounddown; SCIP_Bool bestcandmayroundup; SCIP_Bool bestcandroundup; SCIP_Bool mayrounddown; SCIP_Bool mayroundup; SCIP_Bool roundup; SCIP_Bool lperror; SCIP_Longint ncalls; SCIP_Longint nsolsfound; SCIP_Longint nlpiterations; SCIP_Longint maxnlpiterations; int* roundings; int nvars; int varidx; int nlpcands; int startnlpcands; int depth; int maxdepth; int maxdivedepth; int divedepth; int bestcand; int c; assert(heur != NULL); assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0); assert(scip != NULL); assert(result != NULL); assert(SCIPhasCurrentNodeLP(scip)); *result = SCIP_DELAYED; /* 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; /* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */ if( !SCIPisLPSolBasic(scip) ) return SCIP_OKAY; /* don't dive two times at the same node */ if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 ) return SCIP_OKAY; *result = SCIP_DIDNOTRUN; /* get heuristic's data */ heurdata = SCIPheurGetData(heur); assert(heurdata != NULL); /* only apply heuristic, if only a few solutions have been found */ if( heurdata->maxsols >= 0 && SCIPgetNSolsFound(scip) >= heurdata->maxsols ) return SCIP_OKAY; /* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */ depth = SCIPgetDepth(scip); maxdepth = SCIPgetMaxDepth(scip); maxdepth = MAX(maxdepth, 30); if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth ) return SCIP_OKAY; /* calculate the maximal number of LP iterations until heuristic is aborted */ nlpiterations = SCIPgetNNodeLPIterations(scip); ncalls = SCIPheurGetNCalls(heur); nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess; maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations); maxnlpiterations += heurdata->maxlpiterofs; /* don't try to dive, if we took too many LP iterations during diving */ if( heurdata->nlpiterations >= maxnlpiterations ) return SCIP_OKAY; /* allow at least a certain number of LP iterations in this dive */ maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER); /* get fractional variables that should be integral */ SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) ); /* don't try to dive, if there are no fractional variables */ if( nlpcands == 0 ) return SCIP_OKAY; /* calculate the maximal diving depth */ nvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip); if( SCIPgetNSolsFound(scip) == 0 ) maxdivedepth = (int)(heurdata->depthfacnosol * nvars); else maxdivedepth = (int)(heurdata->depthfac * nvars); maxdivedepth = MIN(maxdivedepth, 10*maxdepth); *result = SCIP_DIDNOTFIND; /* get temporary memory for remembering the current soft roundings */ SCIP_CALL( SCIPallocBufferArray(scip, &roundings, nvars) ); BMSclearMemoryArray(roundings, nvars); /* start diving */ SCIP_CALL( SCIPstartDive(scip) ); SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") executing objpscostdiving heuristic: depth=%d, %d fractionals, dualbound=%g, maxnlpiterations=%"SCIP_LONGINT_FORMAT", maxdivedepth=%d\n", SCIPgetNNodes(scip), SCIPgetDepth(scip), nlpcands, SCIPgetDualbound(scip), maxnlpiterations, maxdivedepth); /* dive as long we are in the given diving depth and iteration limits and fractional variables exist, but * - if the last objective change was in a direction, that corresponds to a feasible rounding, we continue in any case * - if possible, we dive at least with the depth 10 * - if the number of fractional variables decreased at least with 1 variable per 2 dive depths, we continue diving */ lperror = FALSE; lpsolstat = SCIP_LPSOLSTAT_OPTIMAL; divedepth = 0; bestcandmayrounddown = FALSE; bestcandmayroundup = FALSE; startnlpcands = nlpcands; while( !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL && nlpcands > 0 && (divedepth < 10 || nlpcands <= startnlpcands - divedepth/2 || (divedepth < maxdivedepth && nlpcands <= startnlpcands - divedepth/10 && heurdata->nlpiterations < maxnlpiterations)) && !SCIPisStopped(scip) ) { SCIP_RETCODE retcode; divedepth++; /* choose variable for objective change: * - prefer variables that may not be rounded without destroying LP feasibility: * - of these variables, change objective value of variable with largest rel. difference of pseudo cost values * - if all remaining fractional variables may be rounded without destroying LP feasibility: * - change objective value of variable with largest rel. difference of pseudo cost values */ bestcand = -1; bestpscostquot = -1.0; bestcandmayrounddown = TRUE; bestcandmayroundup = TRUE; bestcandroundup = FALSE; for( c = 0; c < nlpcands; ++c ) { var = lpcands[c]; mayrounddown = SCIPvarMayRoundDown(var); mayroundup = SCIPvarMayRoundUp(var); primsol = lpcandssol[c]; frac = lpcandsfrac[c]; if( mayrounddown || mayroundup ) { /* the candidate may be rounded: choose this candidate only, if the best candidate may also be rounded */ if( bestcandmayrounddown || bestcandmayroundup ) { /* choose rounding direction: * - if variable may be rounded in both directions, round corresponding to the pseudo cost values * - otherwise, round in the infeasible direction, because feasible direction is tried by rounding * the current fractional solution */ roundup = FALSE; if( mayrounddown && mayroundup ) calcPscostQuot(scip, var, primsol, frac, 0, &pscostquot, &roundup); else if( mayrounddown ) calcPscostQuot(scip, var, primsol, frac, +1, &pscostquot, &roundup); else calcPscostQuot(scip, var, primsol, frac, -1, &pscostquot, &roundup); /* prefer variables, that have already been soft rounded but failed to get integral */ varidx = SCIPvarGetProbindex(var); assert(0 <= varidx && varidx < nvars); if( roundings[varidx] != 0 ) pscostquot *= 1000.0; /* check, if candidate is new best candidate */ if( pscostquot > bestpscostquot ) { bestcand = c; bestpscostquot = pscostquot; bestcandmayrounddown = mayrounddown; bestcandmayroundup = mayroundup; bestcandroundup = roundup; } } } else { /* the candidate may not be rounded: calculate pseudo cost quotient and preferred direction */ calcPscostQuot(scip, var, primsol, frac, 0, &pscostquot, &roundup); /* prefer variables, that have already been soft rounded but failed to get integral */ varidx = SCIPvarGetProbindex(var); assert(0 <= varidx && varidx < nvars); if( roundings[varidx] != 0 ) pscostquot *= 1000.0; /* check, if candidate is new best candidate: prefer unroundable candidates in any case */ if( bestcandmayrounddown || bestcandmayroundup || pscostquot > bestpscostquot ) { bestcand = c; bestpscostquot = pscostquot; bestcandmayrounddown = FALSE; bestcandmayroundup = FALSE; bestcandroundup = roundup; } } } assert(bestcand != -1); /* if all candidates are roundable, try to round the solution */ if( bestcandmayrounddown || bestcandmayroundup ) { SCIP_Bool success; /* create solution from diving LP and try to round it */ SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) ); SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) ); if( success ) { SCIPdebugMessage("objpscostdiving found roundable primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol)); /* try to add solution to SCIP */ SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) ); /* check, if solution was feasible and good enough */ if( success ) { SCIPdebugMessage(" -> solution was feasible and good enough\n"); *result = SCIP_FOUNDSOL; } } } var = lpcands[bestcand]; /* check, if the best candidate was already subject to soft rounding */ varidx = SCIPvarGetProbindex(var); assert(0 <= varidx && varidx < nvars); if( roundings[varidx] == +1 ) { /* variable was already soft rounded upwards: hard round it downwards */ SCIP_CALL( SCIPchgVarUbDive(scip, var, SCIPfeasFloor(scip, lpcandssol[bestcand])) ); SCIPdebugMessage(" dive %d/%d: var <%s>, round=%u/%u, sol=%g, was already soft rounded upwards -> bounds=[%g,%g]\n", divedepth, maxdivedepth, SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup, lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var)); } else if( roundings[varidx] == -1 ) { /* variable was already soft rounded downwards: hard round it upwards */ SCIP_CALL( SCIPchgVarLbDive(scip, var, SCIPfeasCeil(scip, lpcandssol[bestcand])) ); SCIPdebugMessage(" dive %d/%d: var <%s>, round=%u/%u, sol=%g, was already soft rounded downwards -> bounds=[%g,%g]\n", divedepth, maxdivedepth, SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup, lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var)); } else { assert(roundings[varidx] == 0); /* apply soft rounding of best candidate via a change in the objective value */ objscale = divedepth * 1000.0; oldobj = SCIPgetVarObjDive(scip, var); if( bestcandroundup ) { /* soft round variable up: make objective value (more) negative */ if( oldobj < 0.0 ) newobj = objscale * oldobj; else newobj = -objscale * oldobj; newobj = MIN(newobj, -objscale); /* remember, that this variable was soft rounded upwards */ roundings[varidx] = +1; } else { /* soft round variable down: make objective value (more) positive */ if( oldobj > 0.0 ) newobj = objscale * oldobj; else newobj = -objscale * oldobj; newobj = MAX(newobj, objscale); /* remember, that this variable was soft rounded downwards */ roundings[varidx] = -1; } SCIP_CALL( SCIPchgVarObjDive(scip, var, newobj) ); SCIPdebugMessage(" dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT": var <%s>, round=%u/%u, sol=%g, bounds=[%g,%g], obj=%g, newobj=%g\n", divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations, SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup, lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var), oldobj, newobj); } /* resolve the diving LP */ nlpiterations = SCIPgetNLPIterations(scip); retcode = SCIPsolveDiveLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, NULL); lpsolstat = SCIPgetLPSolstat(scip); /* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic. * Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop. */ if( retcode != SCIP_OKAY ) { #ifndef NDEBUG if( lpsolstat != SCIP_LPSOLSTAT_UNBOUNDEDRAY ) { SCIP_CALL( retcode ); } #endif SCIPwarningMessage(scip, "Error while solving LP in Objpscostdiving heuristic; LP solve terminated with code <%d>\n", retcode); SCIPwarningMessage(scip, "This does not affect the remaining solution procedure --> continue\n"); } if( lperror ) break; /* update iteration count */ heurdata->nlpiterations += SCIPgetNLPIterations(scip) - nlpiterations; /* get LP solution status and fractional variables, that should be integral */ if( lpsolstat == SCIP_LPSOLSTAT_OPTIMAL ) { /* get new fractional variables */ SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) ); } SCIPdebugMessage(" -> lpsolstat=%d, nfrac=%d\n", lpsolstat, nlpcands); } /* check if a solution has been found */ if( nlpcands == 0 && !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL ) { SCIP_Bool success; /* create solution from diving LP */ SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) ); SCIPdebugMessage("objpscostdiving found primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol)); /* try to add solution to SCIP */ SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) ); /* check, if solution was feasible and good enough */ if( success ) { SCIPdebugMessage(" -> solution was feasible and good enough\n"); *result = SCIP_FOUNDSOL; } } /* end diving */ SCIP_CALL( SCIPendDive(scip) ); if( *result == SCIP_FOUNDSOL ) heurdata->nsuccess++; /* free temporary memory for remembering the current soft roundings */ SCIPfreeBufferArray(scip, &roundings); SCIPdebugMessage("objpscostdiving heuristic finished\n"); return SCIP_OKAY; }
/** 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; }
/** computes a disjunctive cut inequality based on two simplex taubleau rows */ static SCIP_RETCODE generateDisjCutSOS1( SCIP* scip, /**< SCIP pointer */ SCIP_SEPA* sepa, /**< separator */ SCIP_ROW** rows, /**< LP rows */ int nrows, /**< number of LP rows */ SCIP_COL** cols, /**< LP columns */ int ncols, /**< number of LP columns */ int ndisjcuts, /**< number of disjunctive cuts found so far */ SCIP_Bool scale, /**< should cut be scaled */ SCIP_Bool strengthen, /**< should cut be strengthened if integer variables are present */ SCIP_Real cutlhs1, /**< left hand side of the first simplex row */ SCIP_Real cutlhs2, /**< left hand side of the second simplex row */ SCIP_Real bound1, /**< bound of first simplex row */ SCIP_Real bound2, /**< bound of second simplex row */ SCIP_Real* simplexcoefs1, /**< simplex coefficients of first row */ SCIP_Real* simplexcoefs2, /**< simplex coefficients of second row */ SCIP_Real* cutcoefs, /**< pointer to store cut coefficients (length: nscipvars) */ SCIP_ROW** row, /**< pointer to store disjunctive cut inequality */ SCIP_Bool* madeintegral /**< pointer to store whether cut has been scaled to integral values */ ) { char cutname[SCIP_MAXSTRLEN]; SCIP_COL** rowcols; SCIP_COL* col; SCIP_Real* rowvals; SCIP_Real lhsrow; SCIP_Real rhsrow; SCIP_Real cutlhs; SCIP_Real sgn; SCIP_Real lb; SCIP_Real ub; int nonbasicnumber = 0; int rownnonz; int ind; int r; int c; assert( scip != NULL ); assert( row != NULL ); assert( rows != NULL ); assert( cols != NULL ); assert( simplexcoefs1 != NULL ); assert( simplexcoefs2 != NULL ); assert( cutcoefs != NULL ); assert( sepa != NULL ); assert( madeintegral != NULL ); *madeintegral = FALSE; /* check signs */ if ( SCIPisFeasPositive(scip, cutlhs1) == SCIPisFeasPositive(scip, cutlhs2) ) sgn = 1.0; else sgn = -1.0; /* check bounds */ if ( SCIPisInfinity(scip, REALABS(bound1)) || SCIPisInfinity(scip, REALABS(bound2)) ) strengthen = FALSE; /* compute left hand side of row (a later update is possible, see below) */ cutlhs = sgn * cutlhs1 * cutlhs2; /* add cut-coefficients of the non-basic non-slack variables */ for (c = 0; c < ncols; ++c) { col = cols[c]; assert( col != NULL ); ind = SCIPcolGetLPPos(col); assert( ind >= 0 ); if ( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_LOWER ) { lb = SCIPcolGetLb(col); /* for integer variables we may obtain stronger coefficients */ if ( strengthen && SCIPcolIsIntegral(col) ) { SCIP_Real mval; SCIP_Real mvalfloor; SCIP_Real mvalceil; mval = (cutlhs2 * simplexcoefs1[nonbasicnumber] - cutlhs1 * simplexcoefs2[nonbasicnumber]) / (cutlhs2 * bound1 + cutlhs1 * bound2); mvalfloor = SCIPfloor(scip, mval); mvalceil = SCIPceil(scip, mval); cutcoefs[ind] = MIN(sgn * cutlhs2 * (simplexcoefs1[nonbasicnumber] - mvalfloor * bound1), sgn * cutlhs1 * (simplexcoefs2[nonbasicnumber] + mvalceil * bound2)); assert( SCIPisFeasLE(scip, cutcoefs[ind], MAX(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber])) ); } else cutcoefs[ind] = MAX(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber]); cutlhs += cutcoefs[ind] * lb; ++nonbasicnumber; } else if ( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_UPPER ) { ub = SCIPcolGetUb(col); /* for integer variables we may obtain stronger coefficients */ if ( strengthen && SCIPcolIsIntegral(col) ) { SCIP_Real mval; SCIP_Real mvalfloor; SCIP_Real mvalceil; mval = (cutlhs2 * simplexcoefs1[nonbasicnumber] - cutlhs1 * simplexcoefs2[nonbasicnumber]) / (cutlhs2 * bound1 + cutlhs1 * bound2); mvalfloor = SCIPfloor(scip, -mval); mvalceil = SCIPceil(scip, -mval); cutcoefs[ind] = MAX(sgn * cutlhs2 * (simplexcoefs1[nonbasicnumber] + mvalfloor * bound1), sgn * cutlhs1 * (simplexcoefs2[nonbasicnumber] - mvalceil * bound2)); assert( SCIPisFeasLE(scip, -cutcoefs[ind], -MIN(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber])) ); } else cutcoefs[ind] = MIN(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber]); cutlhs += cutcoefs[ind] * ub; ++nonbasicnumber; } else { assert( SCIPcolGetBasisStatus(col) != SCIP_BASESTAT_ZERO ); cutcoefs[ind] = 0.0; } } /* add cut-coefficients of the non-basic slack variables */ for (r = 0; r < nrows; ++r) { rhsrow = SCIProwGetRhs(rows[r]) - SCIProwGetConstant(rows[r]); lhsrow = SCIProwGetLhs(rows[r]) - SCIProwGetConstant(rows[r]); assert( SCIProwGetBasisStatus(rows[r]) != SCIP_BASESTAT_ZERO ); assert( SCIPisFeasZero(scip, lhsrow - rhsrow) || SCIPisNegative(scip, lhsrow - rhsrow) ); assert( SCIProwIsInLP(rows[r]) ); if ( SCIProwGetBasisStatus(rows[r]) != SCIP_BASESTAT_BASIC ) { SCIP_Real cutcoef; if ( SCIProwGetBasisStatus(rows[r]) == SCIP_BASESTAT_UPPER ) { assert( SCIPisFeasZero(scip, SCIPgetRowLPActivity(scip, rows[r]) - SCIProwGetRhs(rows[r])) ); cutcoef = MAX(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber]); cutlhs -= cutcoef * rhsrow; ++nonbasicnumber; } else /* SCIProwGetBasisStatus(rows[r]) == SCIP_BASESTAT_LOWER */ { assert( SCIProwGetBasisStatus(rows[r]) == SCIP_BASESTAT_LOWER ); assert( SCIPisFeasZero(scip, SCIPgetRowLPActivity(scip, rows[r]) - SCIProwGetLhs(rows[r])) ); cutcoef = MIN(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber]); cutlhs -= cutcoef * lhsrow; ++nonbasicnumber; } rownnonz = SCIProwGetNNonz(rows[r]); rowvals = SCIProwGetVals(rows[r]); rowcols = SCIProwGetCols(rows[r]); for (c = 0; c < rownnonz; ++c) { ind = SCIPcolGetLPPos(rowcols[c]); /* if column is not in LP, then return without generating cut */ if ( ind < 0 ) { *row = NULL; return SCIP_OKAY; } cutcoefs[ind] -= cutcoef * rowvals[c]; } } } /* create cut */ (void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "%s_%d_%d", SCIPsepaGetName(sepa), SCIPgetNLPs(scip), ndisjcuts); if ( SCIPgetDepth(scip) == 0 ) SCIP_CALL( SCIPcreateEmptyRowSepa(scip, row, sepa, cutname, cutlhs, SCIPinfinity(scip), FALSE, FALSE, TRUE) ); else SCIP_CALL( SCIPcreateEmptyRowSepa(scip, row, sepa, cutname, cutlhs, SCIPinfinity(scip), TRUE, FALSE, TRUE) ); SCIP_CALL( SCIPcacheRowExtensions(scip, *row) ); for (c = 0; c < ncols; ++c) { ind = SCIPcolGetLPPos(cols[c]); assert( ind >= 0 ); if ( ! SCIPisFeasZero(scip, cutcoefs[ind]) ) { SCIP_CALL( SCIPaddVarToRow(scip, *row, SCIPcolGetVar(cols[c]), cutcoefs[ind] ) ); } } SCIP_CALL( SCIPflushRowExtensions(scip, *row) ); /* try to scale the cut to integral values * @todo find better but still stable disjunctive cut settings */ if ( scale ) { int maxdepth; int depth; SCIP_Longint maxdnom; SCIP_Real maxscale; depth = SCIPgetDepth(scip); assert( depth >= 0 ); 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; } SCIP_CALL( SCIPmakeRowIntegral(scip, *row, -SCIPepsilon(scip), SCIPsumepsilon(scip), maxdnom, maxscale, TRUE, madeintegral) ); } 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(heurExecRootsoldiving) /*lint --e{715}*/ { /*lint --e{715}*/ SCIP_HEURDATA* heurdata; SCIP_VAR** vars; SCIP_Real* rootsol; SCIP_Real* objchgvals; int* softroundings; int* intvalrounds; int nvars; int nbinvars; int nintvars; int nlpcands; SCIP_LPSOLSTAT lpsolstat; SCIP_Real absstartobjval; SCIP_Real objstep; SCIP_Real alpha; SCIP_Real oldobj; SCIP_Real newobj; SCIP_Bool lperror; SCIP_Bool lpsolchanged; SCIP_Longint nsolsfound; SCIP_Longint ncalls; SCIP_Longint nlpiterations; SCIP_Longint maxnlpiterations; int depth; int maxdepth; int maxdivedepth; int divedepth; int startnlpcands; int ncycles; int i; assert(heur != NULL); assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0); assert(scip != NULL); assert(result != NULL); assert(SCIPhasCurrentNodeLP(scip)); *result = SCIP_DELAYED; /* 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 solution is basic (which allows fast resolve in diving) */ if( !SCIPisLPSolBasic(scip) ) return SCIP_OKAY; /* don't dive two times at the same node */ if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 ) return SCIP_OKAY; *result = SCIP_DIDNOTRUN; /* get heuristic's data */ heurdata = SCIPheurGetData(heur); assert(heurdata != NULL); /* only apply heuristic, if only a few solutions have been found */ if( heurdata->maxsols >= 0 && SCIPgetNSolsFound(scip) >= heurdata->maxsols ) return SCIP_OKAY; /* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */ depth = SCIPgetDepth(scip); maxdepth = SCIPgetMaxDepth(scip); maxdepth = MAX(maxdepth, 30); if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth ) return SCIP_OKAY; /* calculate the maximal number of LP iterations until heuristic is aborted */ nlpiterations = SCIPgetNNodeLPIterations(scip); ncalls = SCIPheurGetNCalls(heur); nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess; maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations); maxnlpiterations += heurdata->maxlpiterofs; /* don't try to dive, if we took too many LP iterations during diving */ if( heurdata->nlpiterations >= maxnlpiterations ) return SCIP_OKAY; /* allow at least a certain number of LP iterations in this dive */ maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER); /* get number of fractional variables, that should be integral */ nlpcands = SCIPgetNLPBranchCands(scip); /* don't try to dive, if there are no fractional variables */ if( nlpcands == 0 ) return SCIP_OKAY; /* calculate the maximal diving depth */ nvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip); if( SCIPgetNSolsFound(scip) == 0 ) maxdivedepth = (int)(heurdata->depthfacnosol * nvars); else maxdivedepth = (int)(heurdata->depthfac * nvars); maxdivedepth = MAX(maxdivedepth, 10); *result = SCIP_DIDNOTFIND; /* get all variables of LP */ SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) ); /* get root solution value of all binary and integer variables */ SCIP_CALL( SCIPallocBufferArray(scip, &rootsol, nbinvars + nintvars) ); for( i = 0; i < nbinvars + nintvars; i++ ) rootsol[i] = SCIPvarGetRootSol(vars[i]); /* get current LP objective value, and calculate length of a single step in an objective coefficient */ absstartobjval = SCIPgetLPObjval(scip); absstartobjval = ABS(absstartobjval); absstartobjval = MAX(absstartobjval, 1.0); objstep = absstartobjval / 10.0; /* initialize array storing the preferred soft rounding directions and counting the integral value rounds */ SCIP_CALL( SCIPallocBufferArray(scip, &softroundings, nbinvars + nintvars) ); BMSclearMemoryArray(softroundings, nbinvars + nintvars); SCIP_CALL( SCIPallocBufferArray(scip, &intvalrounds, nbinvars + nintvars) ); BMSclearMemoryArray(intvalrounds, nbinvars + nintvars); /* allocate temporary memory for buffering objective changes */ SCIP_CALL( SCIPallocBufferArray(scip, &objchgvals, nbinvars + nintvars) ); /* start diving */ SCIP_CALL( SCIPstartDive(scip) ); SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") executing rootsoldiving heuristic: depth=%d, %d fractionals, dualbound=%g, maxnlpiterations=%"SCIP_LONGINT_FORMAT", maxdivedepth=%d, LPobj=%g, objstep=%g\n", SCIPgetNNodes(scip), SCIPgetDepth(scip), nlpcands, SCIPgetDualbound(scip), maxnlpiterations, maxdivedepth, SCIPgetLPObjval(scip), objstep); lperror = FALSE; divedepth = 0; lpsolstat = SCIP_LPSOLSTAT_OPTIMAL; alpha = heurdata->alpha; ncycles = 0; lpsolchanged = TRUE; startnlpcands = nlpcands; while( !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL && nlpcands > 0 && ncycles < 10 && (divedepth < 10 || nlpcands <= startnlpcands - divedepth/2 || (divedepth < maxdivedepth && heurdata->nlpiterations < maxnlpiterations)) && !SCIPisStopped(scip) ) { SCIP_Bool success; int hardroundingidx; int hardroundingdir; SCIP_Real hardroundingoldbd; SCIP_Real hardroundingnewbd; SCIP_Bool boundschanged; SCIP_RETCODE retcode; /* create solution from diving LP and try to round it */ SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) ); SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) ); if( success ) { SCIPdebugMessage("rootsoldiving found roundable primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol)); /* try to add solution to SCIP */ SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) ); /* check, if solution was feasible and good enough */ if( success ) { SCIPdebugMessage(" -> solution was feasible and good enough\n"); *result = SCIP_FOUNDSOL; } } divedepth++; hardroundingidx = -1; hardroundingdir = 0; hardroundingoldbd = 0.0; hardroundingnewbd = 0.0; boundschanged = FALSE; SCIPdebugMessage("dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT":\n", divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations); /* round solution x* from diving LP: * - x~_j = down(x*_j) if x*_j is integer or binary variable and x*_j <= root solution_j * - x~_j = up(x*_j) if x*_j is integer or binary variable and x*_j > root solution_j * - x~_j = x*_j if x*_j is continuous variable * change objective function in diving LP: * - if x*_j is integral, or j is a continuous variable, set obj'_j = alpha * obj_j * - otherwise, set obj'_j = alpha * obj_j + sign(x*_j - x~_j) */ for( i = 0; i < nbinvars + nintvars; i++ ) { SCIP_VAR* var; SCIP_Real solval; var = vars[i]; oldobj = SCIPgetVarObjDive(scip, var); newobj = oldobj; solval = SCIPvarGetLPSol(var); if( SCIPisFeasIntegral(scip, solval) ) { /* if the variable became integral after a soft rounding, count the rounds; after a while, fix it to its * current integral value; * otherwise, fade out the objective value */ if( softroundings[i] != 0 && lpsolchanged ) { intvalrounds[i]++; if( intvalrounds[i] == 5 && SCIPgetVarLbDive(scip, var) < SCIPgetVarUbDive(scip, var) - 0.5 ) { /* use exact integral value, if the variable is only integral within numerical tolerances */ solval = SCIPfloor(scip, solval+0.5); SCIPdebugMessage(" -> fixing <%s> = %g\n", SCIPvarGetName(var), solval); SCIP_CALL( SCIPchgVarLbDive(scip, var, solval) ); SCIP_CALL( SCIPchgVarUbDive(scip, var, solval) ); boundschanged = TRUE; } } else newobj = alpha * oldobj; } else if( solval <= rootsol[i] ) { /* if the variable was soft rounded most of the time downwards, round it downwards by changing the bounds; * otherwise, apply soft rounding by changing the objective value */ softroundings[i]--; if( softroundings[i] <= -10 && hardroundingidx == -1 ) { SCIPdebugMessage(" -> hard rounding <%s>[%g] <= %g\n", SCIPvarGetName(var), solval, SCIPfeasFloor(scip, solval)); hardroundingidx = i; hardroundingdir = -1; hardroundingoldbd = SCIPgetVarUbDive(scip, var); hardroundingnewbd = SCIPfeasFloor(scip, solval); SCIP_CALL( SCIPchgVarUbDive(scip, var, hardroundingnewbd) ); boundschanged = TRUE; } else newobj = alpha * oldobj + objstep; } else { /* if the variable was soft rounded most of the time upwards, round it upwards by changing the bounds; * otherwise, apply soft rounding by changing the objective value */ softroundings[i]++; if( softroundings[i] >= +10 && hardroundingidx == -1 ) { SCIPdebugMessage(" -> hard rounding <%s>[%g] >= %g\n", SCIPvarGetName(var), solval, SCIPfeasCeil(scip, solval)); hardroundingidx = i; hardroundingdir = +1; hardroundingoldbd = SCIPgetVarLbDive(scip, var); hardroundingnewbd = SCIPfeasCeil(scip, solval); SCIP_CALL( SCIPchgVarLbDive(scip, var, hardroundingnewbd) ); boundschanged = TRUE; } else newobj = alpha * oldobj - objstep; } /* remember the objective change */ objchgvals[i] = newobj; } /* apply objective changes if there was no bound change */ if( !boundschanged ) { /* apply cached changes on integer variables */ for( i = 0; i < nbinvars + nintvars; ++i ) { SCIP_VAR* var; var = vars[i]; SCIPdebugMessage(" -> i=%d var <%s>, solval=%g, rootsol=%g, oldobj=%g, newobj=%g\n", i, SCIPvarGetName(var), SCIPvarGetLPSol(var), rootsol[i], SCIPgetVarObjDive(scip, var), objchgvals[i]); SCIP_CALL( SCIPchgVarObjDive(scip, var, objchgvals[i]) ); } /* fade out the objective values of the continuous variables */ for( i = nbinvars + nintvars; i < nvars; i++ ) { SCIP_VAR* var; var = vars[i]; oldobj = SCIPgetVarObjDive(scip, var); newobj = alpha * oldobj; SCIPdebugMessage(" -> i=%d var <%s>, solval=%g, oldobj=%g, newobj=%g\n", i, SCIPvarGetName(var), SCIPvarGetLPSol(var), oldobj, newobj); SCIP_CALL( SCIPchgVarObjDive(scip, var, newobj) ); } } SOLVEAGAIN: /* resolve the diving LP */ nlpiterations = SCIPgetNLPIterations(scip); retcode = SCIPsolveDiveLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror); lpsolstat = SCIPgetLPSolstat(scip); /* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic. * Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop. */ if( retcode != SCIP_OKAY ) { #ifndef NDEBUG if( lpsolstat != SCIP_LPSOLSTAT_UNBOUNDEDRAY ) { SCIP_CALL( retcode ); } #endif SCIPwarningMessage(scip, "Error while solving LP in Rootsoldiving heuristic; LP solve terminated with code <%d>\n", retcode); SCIPwarningMessage(scip, "This does not affect the remaining solution procedure --> continue\n"); } if( lperror ) break; /* update iteration count */ heurdata->nlpiterations += SCIPgetNLPIterations(scip) - nlpiterations; /* if no LP iterations were performed, we stayed at the same solution -> count this cycling */ lpsolchanged = (SCIPgetNLPIterations(scip) != nlpiterations); if( lpsolchanged ) ncycles = 0; else if( !boundschanged ) /* do not count if integral variables have been fixed */ ncycles++; /* get LP solution status and number of fractional variables, that should be integral */ if( lpsolstat == SCIP_LPSOLSTAT_INFEASIBLE && hardroundingidx != -1 ) { SCIP_VAR* var; var = vars[hardroundingidx]; /* round the hard rounded variable to the opposite direction and resolve the LP */ if( hardroundingdir == -1 ) { SCIPdebugMessage(" -> opposite hard rounding <%s> >= %g\n", SCIPvarGetName(var), hardroundingnewbd + 1.0); SCIP_CALL( SCIPchgVarUbDive(scip, var, hardroundingoldbd) ); SCIP_CALL( SCIPchgVarLbDive(scip, var, hardroundingnewbd + 1.0) ); } else { SCIPdebugMessage(" -> opposite hard rounding <%s> <= %g\n", SCIPvarGetName(var), hardroundingnewbd - 1.0); SCIP_CALL( SCIPchgVarLbDive(scip, var, hardroundingoldbd) ); SCIP_CALL( SCIPchgVarUbDive(scip, var, hardroundingnewbd - 1.0) ); } hardroundingidx = -1; goto SOLVEAGAIN; } if( lpsolstat == SCIP_LPSOLSTAT_OPTIMAL ) nlpcands = SCIPgetNLPBranchCands(scip); SCIPdebugMessage(" -> lpsolstat=%d, nfrac=%d\n", lpsolstat, nlpcands); } SCIPdebugMessage("---> diving finished: lpsolstat = %d, depth %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT"\n", lpsolstat, divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations); /* check if a solution has been found */ if( nlpcands == 0 && !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL ) { SCIP_Bool success; /* create solution from diving LP */ SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) ); SCIPdebugMessage("rootsoldiving found primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol)); /* try to add solution to SCIP */ SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) ); /* check, if solution was feasible and good enough */ if( success ) { SCIPdebugMessage(" -> solution was feasible and good enough\n"); *result = SCIP_FOUNDSOL; } } /* end diving */ SCIP_CALL( SCIPendDive(scip) ); if( *result == SCIP_FOUNDSOL ) heurdata->nsuccess++; /* free temporary memory */ SCIPfreeBufferArray(scip, &objchgvals); SCIPfreeBufferArray(scip, &intvalrounds); SCIPfreeBufferArray(scip, &softroundings); SCIPfreeBufferArray(scip, &rootsol); SCIPdebugMessage("rootsoldiving heuristic finished\n"); return SCIP_OKAY; }