/** returns whether the debug solution is worse as the best known solution or if the debug solution was found */
static
SCIP_Bool debugSolIsAchieved(
SCIP_SET* set /**< global SCIP settings */
)
{
SCIP_SOL* bestsol;
SCIP* scip;
if( solisachieved )
return TRUE;
assert(set != NULL);
scip = set->scip;
assert(scip != NULL);
bestsol = SCIPgetBestSol(scip);
if( bestsol != NULL )
{
SCIP_Real solvalue;
/* don't check solution while in problem creation stage */
if( SCIPsetGetStage(set) == SCIP_STAGE_PROBLEM )
return TRUE;
solvalue = SCIPgetSolOrigObj(scip, bestsol);
/* make sure a debug solution has been read, so we do not compare against the initial debugsolval == 0 */
SCIP_CALL( readSolution(set) );
if( (SCIPgetObjsense(scip) == SCIP_OBJSENSE_MINIMIZE && SCIPsetIsLE(set, solvalue, debugsolval)) || (SCIPgetObjsense(scip) == SCIP_OBJSENSE_MAXIMIZE && SCIPsetIsGE(set, solvalue, debugsolval)) )
solisachieved = TRUE;
}
return solisachieved;
}
/** execution method of event handler */
static
SCIP_DECL_EVENTEXEC(eventExecBestsol)
{ /*lint --e{715}*/
SCIP_SOL* bestsol;
SCIP_Real solvalue;
assert(eventhdlr != NULL);
assert(strcmp(SCIPeventhdlrGetName(eventhdlr), EVENTHDLR_NAME) == 0);
assert(event != NULL);
assert(scip != NULL);
assert(SCIPeventGetType(event) == SCIP_EVENTTYPE_BESTSOLFOUND);
SCIPdebugMessage("exec method of event handler for best solution found\n");
bestsol = SCIPgetBestSol(scip);
assert(bestsol != NULL);
solvalue = SCIPgetSolOrigObj(scip, bestsol);
/* print best solution value */
SCIPinfoMessage(scip, NULL, "found new best solution with solution value <%g> in SCIP <%s>\n",
solvalue, SCIPgetProbName(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;
}
/** 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;
}
/** changes the color of the node to the color of nodes with a primal solution */
void SCIPvisualFoundSolution(
SCIP_VISUAL* visual, /**< visualization information */
SCIP_SET* set, /**< global SCIP settings */
SCIP_STAT* stat, /**< problem statistics */
SCIP_NODE* node, /**< node where the solution was found, or NULL */
SCIP_Bool bettersol, /**< the solution was better than the previous ones */
SCIP_SOL* sol /**< solution that has been found */
)
{
if ( visual->vbcfile != NULL )
{
if ( node != NULL && set->visual_dispsols )
{
if ( SCIPnodeGetType(node) != SCIP_NODETYPE_PROBINGNODE )
vbcSetColor(visual, stat, node, SCIP_VBCCOLOR_SOLUTION);
}
}
if ( visual->bakfile != NULL && bettersol )
{
SCIP_Real obj;
if ( set->visual_objextern )
obj = SCIPgetSolOrigObj(set->scip, sol);
else
obj = SCIPgetSolTransObj(set->scip, sol);
if ( SCIPsolGetHeur(sol) == NULL && node != NULL )
{
/* if LP solution was feasible ... */
SCIP_VAR* branchvar;
SCIP_BOUNDTYPE branchtype;
SCIP_Real branchbound;
SCIP_NODE *pnode;
size_t parentnodenum;
size_t nodenum;
char t = 'M';
/* find first parent that is not a probing node */
pnode = node;
while ( pnode != NULL && SCIPnodeGetType(pnode) == SCIP_NODETYPE_PROBINGNODE )
pnode = pnode->parent;
if ( pnode != NULL )
{
/* get node num from hash map */
nodenum = (size_t)SCIPhashmapGetImage(visual->nodenum, pnode);
/* get nodenum of parent node from hash map */
parentnodenum = (pnode->parent != NULL ? (size_t)SCIPhashmapGetImage(visual->nodenum, pnode->parent) : 0);
assert( pnode->parent == NULL || parentnodenum > 0 );
/* get branching information */
getBranchInfo(pnode, &branchvar, &branchtype, &branchbound);
/* determine branching type */
if ( branchvar != NULL )
t = (branchtype == SCIP_BOUNDTYPE_LOWER ? 'R' : 'L');
printTime(visual, stat, FALSE);
SCIPmessageFPrintInfo(visual->messagehdlr, visual->bakfile, "integer %d %d %c %f\n", (int)nodenum, (int)parentnodenum, t, obj);
}
}
else
{
printTime(visual, stat, FALSE);
SCIPmessageFPrintInfo(visual->messagehdlr, visual->bakfile, "heuristic %f\n", obj);
}
}
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecIndicator)
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
int nfoundsols = 0;
assert( heur != NULL );
assert( scip != NULL );
assert( result != NULL );
*result = SCIP_DIDNOTRUN;
if ( SCIPgetSubscipDepth(scip) > 0 )
return SCIP_OKAY;
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert( heurdata != NULL );
/* call heuristic, if solution candidate is available */
if ( heurdata->solcand != NULL )
{
assert( heurdata->nindconss > 0 );
assert( heurdata->indconss != NULL );
/* The heuristic will only be successful if there are no integral variables and no binary variables except the
* indicator variables. */
if ( SCIPgetNIntVars(scip) > 0 || heurdata->nindconss < SCIPgetNBinVars(scip) )
return SCIP_OKAY;
SCIP_CALL( trySolCandidate(scip, heur, heurdata, heurdata->nindconss, heurdata->indconss, heurdata->solcand, &nfoundsols) );
if ( nfoundsols > 0 )
*result = SCIP_FOUNDSOL;
else
*result = SCIP_DIDNOTFIND;
/* free memory */
SCIPfreeBlockMemoryArray(scip, &(heurdata->solcand), heurdata->nindconss);
SCIPfreeBlockMemoryArray(scip, &(heurdata->indconss), heurdata->nindconss);
}
else
{
SCIP_CONS** indconss;
SCIP_Bool* solcand;
SCIP_SOL* bestsol;
int nindconss;
int i;
if ( heurdata->indicatorconshdlr == NULL )
return SCIP_OKAY;
/* check whether a new best solution has been found */
bestsol = SCIPgetBestSol(scip);
if ( bestsol == heurdata->lastsol )
return SCIP_OKAY;
heurdata->lastsol = bestsol;
/* avoid solutions produced by this heuristic */
if ( SCIPsolGetHeur(bestsol) == heur )
return SCIP_OKAY;
/* The heuristic will only be successful if there are no integral variables and no binary variables except the
* indicator variables. */
if ( SCIPgetNIntVars(scip) > 0 || SCIPconshdlrGetNConss(heurdata->indicatorconshdlr) < SCIPgetNBinVars(scip) )
return SCIP_OKAY;
nindconss = SCIPconshdlrGetNConss(heurdata->indicatorconshdlr);
if ( nindconss == 0 )
return SCIP_OKAY;
indconss = SCIPconshdlrGetConss(heurdata->indicatorconshdlr);
assert( indconss != NULL );
/* fill solutin candidate */
SCIP_CALL( SCIPallocBufferArray(scip, &solcand, nindconss) );
for (i = 0; i < nindconss; ++i)
{
SCIP_VAR* binvar;
SCIP_Real val;
solcand[i] = FALSE;
if ( SCIPconsIsActive(indconss[i]) )
{
binvar = SCIPgetBinaryVarIndicator(indconss[i]);
assert( binvar != NULL );
val = SCIPgetSolVal(scip, bestsol, binvar);
assert( SCIPisFeasIntegral(scip, val) );
if ( val > 0.5 )
solcand[i] = TRUE;
}
}
SCIPdebugMessage("Trying to improve best solution of value %f.\n", SCIPgetSolOrigObj(scip, bestsol) );
/* try one-opt heuristic */
SCIP_CALL( tryOneOpt(scip, heur, heurdata, nindconss, indconss, solcand, &nfoundsols) );
if ( nfoundsols > 0 )
*result = SCIP_FOUNDSOL;
else
*result = SCIP_DIDNOTFIND;
SCIPfreeBufferArray(scip, &solcand);
}
return SCIP_OKAY;
}
/** searches and adds integral objective cuts that separate the given primal solution */
static
SCIP_RETCODE separateCuts(
SCIP* scip, /**< SCIP data structure */
SCIP_SEPA* sepa, /**< the intobj separator */
SCIP_SOL* sol, /**< the solution that should be separated, or NULL for LP solution */
SCIP_RESULT* result /**< pointer to store the result */
)
{
SCIP_SEPADATA* sepadata;
SCIP_Real objval;
SCIP_Real intbound;
SCIP_Bool infeasible;
SCIP_Bool tightened;
assert(result != NULL);
assert(*result == SCIP_DIDNOTRUN);
/* if the objective value may be fractional, we cannot do anything */
if( !SCIPisObjIntegral(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
/* if the current objective value is integral, there is no integral objective value cut */
if( sol == NULL )
objval = SCIPretransformObj(scip, SCIPgetLPObjval(scip));
else
objval = SCIPgetSolOrigObj(scip, sol);
if( SCIPisFeasIntegral(scip, objval) )
return SCIP_OKAY;
sepadata = SCIPsepaGetData(sepa);
assert(sepadata != NULL);
/* the objective value is fractional: create the objective value inequality, if not yet existing */
SCIP_CALL( createObjRow(scip, sepa, sepadata) );
/* adjust the bounds of the objective value variable */
if( SCIPgetObjsense(scip) == SCIP_OBJSENSE_MINIMIZE )
{
intbound = SCIPceil(scip, objval) - sepadata->setoff;
SCIP_CALL( SCIPtightenVarLb(scip, sepadata->objvar, intbound, FALSE, &infeasible, &tightened) );
SCIPdebugMessage("new objective variable lower bound: <%s>[%g,%g]\n",
SCIPvarGetName(sepadata->objvar), SCIPvarGetLbLocal(sepadata->objvar), SCIPvarGetUbLocal(sepadata->objvar));
}
else
{
intbound = SCIPfloor(scip, objval) - sepadata->setoff;
SCIP_CALL( SCIPtightenVarUb(scip, sepadata->objvar, intbound, FALSE, &infeasible, &tightened) );
SCIPdebugMessage("new objective variable upper bound: <%s>[%g,%g]\n",
SCIPvarGetName(sepadata->objvar), SCIPvarGetLbLocal(sepadata->objvar), SCIPvarGetUbLocal(sepadata->objvar));
}
/* add the objective value inequality as a cut to the LP */
if( infeasible )
*result = SCIP_CUTOFF;
else
{
if( !SCIProwIsInLP(sepadata->objrow) )
{
SCIP_CALL( SCIPaddCut(scip, sol, sepadata->objrow, FALSE, &infeasible) );
}
if ( infeasible )
*result = SCIP_CUTOFF;
else if ( tightened )
*result = SCIP_REDUCEDDOM;
else
*result = SCIP_SEPARATED;
}
return SCIP_OKAY;
}
SCIP_RETCODE SCIPconshdlrBenders::sepaBenders(
SCIP * scip,
SCIP_CONSHDLR * conshdlr,
SCIP_SOL * sol,
whereFrom where,
SCIP_RESULT * result)
{
OsiCuts cs; /**< Benders cut placeholder */
SCIP_Real * vals = NULL; /**< current solution */
#if 1
if (scip_checkpriority_ < 0)
{
/** consider incumbent solutions only */
double primObj = SCIPgetPrimalbound(scip);
double currObj = SCIPgetSolOrigObj(scip, sol);
if (SCIPisLT(scip, primObj, currObj))
{
DSPdebugMessage(" -> primObj %e currObj %e\n", primObj, currObj);
return SCIP_OKAY;
}
}
#endif
/** allocate memory */
SCIP_CALL(SCIPallocMemoryArray(scip, &vals, nvars_));
/** get current solution */
SCIP_CALL(SCIPgetSolVals(scip, sol, nvars_, vars_, vals));
/** TODO The following filter does not work, meaning that it provides suboptimal solution.
* I do not know the reason. */
#if 0
double maxviol = 1.e-10;
for (int j = 0; j < nvars_ - naux_; ++j)
{
SCIP_VARTYPE vartype = SCIPvarGetType(vars_[j]);
if (vartype == SCIP_VARTYPE_CONTINUOUS) continue;
double viol = 0.5 - fabs(vals[j] - floor(vals[j]) - 0.5);
if (viol > maxviol)
maxviol = viol;
}
DSPdebugMessage("maximum violation %e\n", maxviol);
if (where != from_scip_check &&
where != from_scip_enfolp &&
where != from_scip_enfops &&
maxviol > 1.e-7)
{
printf("where %d maxviol %e\n", where, maxviol);
/** free memory */
SCIPfreeMemoryArray(scip, &vals);
return SCIP_OKAY;
}
#endif
#ifdef DSP_DEBUG2
double minvals = COIN_DBL_MAX;
double maxvals = -COIN_DBL_MAX;
double sumvals = 0.;
double ssvals = 0.;
//printf("nvars_ %d naux_ %d nAuxvars_ %d\n", nvars_, naux_, tss_->nAuxvars_);
for (int j = 0; j < nvars_ - naux_; ++j)
{
// if (vals[j] < 0 || vals[j] > 1)
// printf("solution %d has value %e.\n", j, vals[j]);
sumvals += vals[j];
ssvals += vals[j] * vals[j];
minvals = minvals > vals[j] ? vals[j] : minvals;
maxvals = maxvals < vals[j] ? vals[j] : maxvals;
}
DSPdebugMessage("solution: min %e max %e avg %e sum %e two-norm %e\n",
minvals, maxvals, sumvals / nvars_, sumvals, sqrt(ssvals));
#endif
#define SCAN_GLOBAL_CUT_POOL
#ifdef SCAN_GLOBAL_CUT_POOL
if (SCIPgetStage(scip) == SCIP_STAGE_SOLVING ||
SCIPgetStage(scip) == SCIP_STAGE_SOLVED ||
SCIPgetStage(scip) == SCIP_STAGE_EXITSOLVE)
{
bool addedPoolCut = false;
int numPoolCuts = SCIPgetNPoolCuts(scip);
int numCutsToScan = 100;
SCIP_CUT ** poolcuts = SCIPgetPoolCuts(scip);
for (int i = numPoolCuts - 1; i >= 0; --i)
{
if (i < 0) break;
if (numCutsToScan == 0) break;
/** retrieve row */
SCIP_ROW * poolcutrow = SCIPcutGetRow(poolcuts[i]);
/** benders? */
if (strcmp(SCIProwGetName(poolcutrow), "benders") != 0)
continue;
/** counter */
numCutsToScan--;
if (SCIPgetCutEfficacy(scip, sol, poolcutrow) > 1.e-6)
{
if (where == from_scip_sepalp ||
where == from_scip_sepasol ||
where == from_scip_enfolp)
{
/** add cut */
SCIP_Bool infeasible;
SCIP_CALL(SCIPaddCut(scip, sol, poolcutrow,
FALSE, /**< force cut */
&infeasible));
if (infeasible)
*result = SCIP_CUTOFF;
else //if (*result != SCIP_CUTOFF)
*result = SCIP_SEPARATED;
}
else
*result = SCIP_INFEASIBLE;
addedPoolCut = true;
break;
}
}
if (addedPoolCut)
{
DSPdebugMessage("Added pool cut\n");
/** free memory */
SCIPfreeMemoryArray(scip, &vals);
return SCIP_OKAY;
}
}
#endif
/** generate Benders cuts */
assert(tss_);
tss_->generateCuts(nvars_, vals, &cs);
/** If found Benders cuts */
for (int i = 0; i < cs.sizeCuts(); ++i)
{
/** get cut pointer */
OsiRowCut * rc = cs.rowCutPtr(i);
if (!rc) continue;
const CoinPackedVector cutrow = rc->row();
if (cutrow.getNumElements() == 0) continue;
/** is optimality cut? */
bool isOptimalityCut = false;
for (int j = nvars_ - naux_; j < nvars_; ++j)
{
if (cutrow.getMaxIndex() == j)
{
isOptimalityCut = true;
break;
}
}
double efficacy = rc->violated(vals) / cutrow.twoNorm();
SCIP_Bool isEfficacious = efficacy > 1.e-6;
#define KK_TEST
#ifdef KK_TEST
if (SCIPgetStage(scip) == SCIP_STAGE_INITSOLVE ||
SCIPgetStage(scip) == SCIP_STAGE_SOLVING)
{
/** create empty row */
SCIP_ROW * row = NULL;
SCIP_CALL(SCIPcreateEmptyRowCons(scip, &row, conshdlr, "benders", rc->lb(), SCIPinfinity(scip),
FALSE, /**< is row local? */
FALSE, /**< is row modifiable? */
FALSE /**< is row removable? can this be TRUE? */));
/** cache the row extension and only flush them if the cut gets added */
SCIP_CALL(SCIPcacheRowExtensions(scip, row));
/** collect all non-zero coefficients */
for (int j = 0; j < cutrow.getNumElements(); ++j)
SCIP_CALL(SCIPaddVarToRow(scip, row, vars_[cutrow.getIndices()[j]], cutrow.getElements()[j]));
DSPdebugMessage("found Benders (%s) cut: act=%f, lhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n",
isOptimalityCut ? "opti" : "feas",
SCIPgetRowLPActivity(scip, row), SCIProwGetLhs(row), SCIProwGetNorm(row),
SCIPgetCutEfficacy(scip, sol, row),
SCIPgetRowMinCoef(scip, row), SCIPgetRowMaxCoef(scip, row),
SCIPgetRowMaxCoef(scip, row)/SCIPgetRowMinCoef(scip, row));
/** flush all changes before adding cut */
SCIP_CALL(SCIPflushRowExtensions(scip, row));
DSPdebugMessage("efficacy %e isEfficatious %d\n", efficacy, isEfficacious);
if (isEfficacious)
{
if (where == from_scip_sepalp ||
where == from_scip_sepasol ||
where == from_scip_enfolp)
{
/** add cut */
SCIP_Bool infeasible;
SCIP_CALL(SCIPaddCut(scip, sol, row,
FALSE, /**< force cut */
&infeasible));
if (infeasible)
*result = SCIP_CUTOFF;
else //if (*result != SCIP_CUTOFF)
*result = SCIP_SEPARATED;
}
else
*result = SCIP_INFEASIBLE;
}
/** add cut to global pool */
SCIP_CALL(SCIPaddPoolCut(scip, row));
DSPdebugMessage("number of cuts in global cut pool: %d\n", SCIPgetNPoolCuts(scip));
/** release the row */
SCIP_CALL(SCIPreleaseRow(scip, &row));
}
else if (isEfficacious &&
where != from_scip_sepalp &&
where != from_scip_sepasol &&
where != from_scip_enfolp)
*result = SCIP_INFEASIBLE;
#else
if (where == from_scip_sepalp ||
where == from_scip_sepasol ||
where == from_scip_enfolp)
{
/** create empty row */
SCIP_ROW * row = NULL;
SCIP_CALL(SCIPcreateEmptyRowCons(scip, &row, conshdlr, "benders", rc->lb(), SCIPinfinity(scip),
FALSE, /**< is row local? */
FALSE, /**< is row modifiable? */
FALSE /**< is row removable? can this be TRUE? */));
/** cache the row extension and only flush them if the cut gets added */
SCIP_CALL(SCIPcacheRowExtensions(scip, row));
/** collect all non-zero coefficients */
for (int j = 0; j < cutrow.getNumElements(); ++j)
SCIP_CALL(SCIPaddVarToRow(scip, row, vars_[cutrow.getIndices()[j]], cutrow.getElements()[j]));
DSPdebugMessage("found Benders (%s) cut: act=%f, lhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n",
isOptimalityCut ? "opti" : "feas",
SCIPgetRowLPActivity(scip, row), SCIProwGetLhs(row), SCIProwGetNorm(row),
SCIPgetCutEfficacy(scip, NULL, row),
SCIPgetRowMinCoef(scip, row), SCIPgetRowMaxCoef(scip, row),
SCIPgetRowMaxCoef(scip, row)/SCIPgetRowMinCoef(scip, row));
/** flush all changes before adding cut */
SCIP_CALL(SCIPflushRowExtensions(scip, row));
/** is cut efficacious? */
if (isOptimalityCut)
{
efficacy = SCIPgetCutEfficacy(scip, sol, row);
isEfficacious = SCIPisCutEfficacious(scip, sol, row);
}
else
{
efficacy = rc->violated(vals);
isEfficacious = efficacy > 1.e-6;
}
if (isEfficacious)
{
/** add cut */
SCIP_Bool infeasible;
SCIP_CALL(SCIPaddCut(scip, sol, row,
FALSE, /**< force cut */
&infeasible));
if (infeasible)
*result = SCIP_CUTOFF;
else if (*result != SCIP_CUTOFF)
*result = SCIP_SEPARATED;
}
/** add cut to global pool */
SCIP_CALL(SCIPaddPoolCut(scip, row));
/** release the row */
SCIP_CALL(SCIPreleaseRow(scip, &row));
}
else
{
if (isOptimalityCut)
{
efficacy = rc->violated(vals) / cutrow.twoNorm();
isEfficacious = efficacy > 0.05;
}
else
{
efficacy = rc->violated(vals);
isEfficacious = efficacy > 1.e-6;
}
DSPdebugMessage("%s efficacy %e\n", isOptimalityCut ? "Opti" : "Feas", efficacy);
if (isEfficacious == TRUE)
*result = SCIP_INFEASIBLE;
}
#endif
}
/** free memory */
SCIPfreeMemoryArray(scip, &vals);
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecForward)
{ /*lint --e{715}*/
SCIP_PROBDATA* probdata;
int n;
int p;
int ndep;
/* "_" means the matrix for blas */
SCIP_Real* y; /* [n] */
SCIP_Real* orig_X_; /* [n*p] */
SCIP_Real* orig_Q_; /* [p*p] <- (X^t) X */
SCIP_Real* orig_q; /* [p] <- (X^t) y */
SCIP_Real r;
int* Mdep; /* [ndep] */
int* groupX; /* [ndep*p] */
/* for forward selection */
int dim;
int* list; /* [p] */
SCIP_Real* a; /* [dim] */
SCIP_Real* a_old; /* [dim-1] */
SCIP_Real* a_new; /* [dim] */
SCIP_Real RSS; /* residual sum of square */
SCIP_Real RSS_new;
SCIP_Real AIC;
SCIP_Real AIC_new;
int ublb;
int *Branchz; /* [3*p] */
/*
* X: sub matrix of orig_X_
* Y: (X^t X)^-1
* X_new = (X, x_i);
* Z: (X_new ^t X_new)^-1
* = ( V v
v^t u )
*/
SCIP_Real* Xy; /* sub vector of orig_q */
SCIP_Real* X_;
SCIP_Real* Y_; /* [(dim-1)*(dim-1)] */
SCIP_Real* Z_; /* [dim*dim] */
SCIP_Real* W_; /* [dim*dim] */
SCIP_Real* V_; /* [(dim-1)*(dim-1)] */
SCIP_Real* v; /* [dim-1] */
SCIP_Real u;
SCIP_Real* b; /* [dim-1] */
SCIP_Real* c; /* [dim-1] */
SCIP_Real* d; /* [n] */
/* variables */
SCIP_VAR** var_a; /* [p] continuous variables */
SCIP_VAR** var_z; /* [p] 01 variables */
SCIP_VAR** var_ep; /* [n] continuous variables */
SCIP_VAR* var_rss; /* continuous variable, residual sum of squares */
SCIP_VAR* var_log; /* continuous variable, log(rss) */
/* set solution */
SCIP_Real *ep;
int nsols;
int store;
SCIP_SOL** sols;
SCIP_Real objval;
SCIP_SOL* sol;
SCIP_Real* solvals;
SCIP_Bool success;
int nvars = SCIPgetNVars(scip);
SCIP_VAR** vars;
int i,j,t,ct;
int memo;
assert(heur != NULL);
assert(scip != NULL);
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
assert(result != NULL);
#if MYPARA_LOG
printf("forward selection!\n");
#endif
/* get heuristic data */
/*
SCIP_HEURDATA* heurdata;
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
assert(lastsolindices != NULL);
*/
/* get values from probdata */
probdata = SCIPgetProbData(scip);
assert(probdata != NULL);
n = SCIPprobdataGetNdatas(probdata);
p = SCIPprobdataGetNexvars(probdata);
ndep = SCIPprobdataGetNdep(probdata);
y = SCIPprobdataGety(probdata);
orig_X_ = SCIPprobdataGetX(probdata);
orig_Q_ = SCIPprobdataGetQ(probdata);
orig_q = SCIPprobdataGetq(probdata);
r = SCIPprobdataGetr(probdata);
if( ndep ){
Mdep = SCIPprobdataGetMdep(probdata);
groupX = SCIPprobdataGetgroupX(probdata);
}else{
Mdep = NULL;
groupX = NULL;
}
/* variables */
var_a = SCIPprobdataGetVars_a(probdata);
var_z = SCIPprobdataGetVars_z(probdata);
var_ep = SCIPprobdataGetVars_ep(probdata);
var_rss = SCIPprobdataGetVar_rss(probdata);
var_log = SCIPprobdataGetVar_log(probdata);
/* get branching info */
/* alloc */
SCIP_CALL( SCIPallocBufferArray(scip, &Branchz, 3*p));
GenerateZeroVecInt( 3*p, Branchz);
for(i=0; i<p; ++i){
ublb = SCIPround(scip, SCIPcomputeVarUbLocal(scip, var_z[i])
+ SCIPcomputeVarLbLocal(scip, var_z[i]));
*(Branchz+(ublb*p)+i) = 1;
}
#if MYPARA_LOG
for(i=0; i<3; i++){
for(j=0; j<p; j++){
printf("%d, ", *(Branchz+(i*p)+j));
}
newline();
}
#endif
if( ndep ){
for(i=0; i<ndep; i++){
memo = -1;
for(j=0; j<p; j++){
if( *(groupX+(i*p)+j)==1 ){
if( *(Branchz+j)==1 ) break;
if( *(Branchz+p+j)==1 ) memo=j;
if( j==Mdep[i] ){
if( memo==-1 ){
printf("error in heur_backward.c\n");
stop();
}
*(Branchz+p+memo) = 0;
*(Branchz+memo) = 1;
break;
}
}
}
}
}
#if MYPARA_LOG
printf("linear dependent\n");
if( ndep ){
for(i=0; i<3; i++){
for(j=0; j<p; j++){
printf("%d, ", *(Branchz+(i*p)+j));
}
newline();
}
}
#endif
/* alloc */
SCIP_CALL( SCIPallocBufferArray(scip, &X_, n*p));
SCIP_CALL( SCIPallocBufferArray(scip, &Xy, p));
SCIP_CALL( SCIPallocBufferArray(scip, &d, n));
SCIP_CALL( SCIPallocBufferArray(scip, &list, p));
/* initialize from Branchz */
#if MYPARA_LOG
printf("initialization\n");
#endif
GenerateZeroVecInt( p, list);
dim = 0;
memo = -1;
AIC = 1e+06;
SCIP_CALL( SCIPallocBufferArray(scip, &a_old, dim+1));
for(i=0; i<p; i++){
if( Branchz[i]==1 ){ /* if z_i is fixed to 0 */
list[i] = -1;
}else if( Branchz[p+i]==1 ){ /* if z_i is unfixed */
list[i] = 0;
}else if( Branchz[2*p+i]==1 ){ /* if z_i is fixed 1 */
dim++;
list[i] = dim;
if( dim == 1 ){
a_old[0] = orig_q[i] / mat_( orig_Q_, p, i, i);
RSS = RSSvalue( 1, a_old, &orig_q[i], r);
AIC = AICvalue( n, dim, RSS);
/* update X_ and Xy */
mydcopy_( &orig_X_[n * i], &X_[n * (dim-1)], n);
Xy[dim-1] = orig_q[i];
/* generate Y ( dim = 1 ) */
SCIP_CALL( SCIPallocBufferArray( scip, &Y_, dim*dim));
Y_[0] = 1 / mat_( orig_Q_, p, i, i);
}else{
/* alloc */
SCIPfreeBufferArray(scip, &a_old);
SCIP_CALL( SCIPallocBufferArray( scip, &a_old, dim));
SCIP_CALL( SCIPallocBufferArray( scip, &b, dim-1));
SCIP_CALL( SCIPallocBufferArray( scip, &c, dim-1));
SCIP_CALL( SCIPallocBufferArray( scip, &v, dim-1));
SCIP_CALL( SCIPallocBufferArray( scip, &V_, (dim-1)*(dim-1)));
SCIP_CALL( SCIPallocBufferArray( scip, &Z_, (dim)*(dim)));
/* 1. b <- X^t x_i */
dgemv_t( X_, n, dim-1, &orig_X_[n * i], b);
//printv( dim-1, b);
/* 2. c <- Y b */
dgemv_2( Y_, dim-1, dim-1, b, c);
//printv( dim-1, c);
/* 3. d <- - X c + x_i */
dgemv_1( X_, n, dim-1, c, &orig_X_[n * i], -1.0, 1.0, d);
//printv( n, d);
/* 4. u <- 1/<x_i, d> */
u = 1.0 / myddot_( &orig_X_[n * i], d, n);
//prints(u);
/* 5. v <- - u c */
mydscal_( c, dim-1, -u, v);
//printv( dim-1, v);
/* 6. V <- Y + u c c^t */
dger_1( Y_, c, c, dim-1, dim-1, u, V_);
//printM_( V_, dim-1, dim-1);
/* 7. Z */
/* V */
for(j=0; j<(dim-1); j++){
for(t=0; t<(dim-1); t++){
*(Z_ + j + (t*dim) ) = mat_( V_, dim-1, j, t);
}
}
/* v */
for(j=0; j<(dim-1); j++){
*(Z_ + dim-1 + (j*dim) ) = v[j];
*(Z_ + j + ((dim-1)*dim)) = v[j];
}
/* u */
*(Z_ + dim-1 + ((dim-1)*dim)) = u;
//printM_( Z_, dim, dim);
/* 8. a_old <- Z (Xy) */
Xy[dim-1] = orig_q[i];
dgemv_2( Z_, dim, dim, Xy, a_old);
//printv( dim, a_old);
RSS = RSSvalue( dim, a_old, Xy, r);
AIC = AICvalue( n, dim, RSS);
/* copy */
SCIPfreeBufferArray(scip, &Y_);
SCIP_CALL( SCIPallocBufferArray(scip, &Y_, dim*dim));
mydcopy_( Z_, Y_, dim*dim);
/* update X_ and Xy */
mydcopy_( &orig_X_[n * i], &X_[n * (dim-1)], n);
Xy[dim-1] = orig_q[i];
/* free */
SCIPfreeBufferArray(scip, &b);
SCIPfreeBufferArray(scip, &c);
SCIPfreeBufferArray(scip, &v);
SCIPfreeBufferArray(scip, &V_);
SCIPfreeBufferArray(scip, &Z_);
}
#if MYPARA_LOG
printf("---> %dth variable, AIC:%f\n", i, AIC);
#endif
}else{
printf("error:heur_forward.c\n");
stop();
}
}
if( dim == 0 ){
#if MYPARA_LOG
printf("[dim:0]\n");
#endif
dim++;
RSS = 1e+06;
for(i=0; i<p; i++){
if( list[i] == 0 ){
a_old[0] = orig_q[i] / mat_( orig_Q_, p, i, i);
RSS_new = RSSvalue( 1, a_old, &orig_q[i], r);
if( RSS_new < RSS ){
RSS = RSS_new;
memo = i;
}
#if MYPARA_LOG
printf("%d: RSS = %f\n", i, RSS_new);
#endif
}
}
if( memo < 0 || memo >= p ){
printf("error in heur_forward.c\n");
stop();
}
AIC = AICvalue( n, dim, RSS);
list[memo] = dim;
/* update X_ and Xy */
mydcopy_( &orig_X_[n * memo], &X_[n * (dim-1)], n);
Xy[dim-1] = orig_q[memo];
/* generate Y ( dim = 1 ) */
SCIP_CALL( SCIPallocBufferArray( scip, &Y_, dim*dim));
Y_[0] = 1 / mat_( orig_Q_, p, memo, memo);
#if MYPARA_LOG
printf("---> %dth variable, AIC:%f\n", memo, AIC);
#endif
} /* if ( dim==0 ) */
while(1){
dim++;
memo = -1;
RSS = 1e+06;
#if MYPARA_LOG
printf("(dim=%d) ", dim);
Longline();
#endif
/* alloc */
SCIP_CALL( SCIPallocBufferArray( scip, &a_new, dim));
SCIP_CALL( SCIPallocBufferArray( scip, &a, dim));
SCIP_CALL( SCIPallocBufferArray( scip, &b, dim-1));
SCIP_CALL( SCIPallocBufferArray( scip, &c, dim-1));
SCIP_CALL( SCIPallocBufferArray( scip, &v, dim-1));
SCIP_CALL( SCIPallocBufferArray( scip, &V_, (dim-1)*(dim-1)));
SCIP_CALL( SCIPallocBufferArray( scip, &Z_, (dim)*(dim)));
SCIP_CALL( SCIPallocBufferArray( scip, &W_, (dim)*(dim)));
for(i=0; i<p; i++){
/*
* 1. b <- X^t x_i
* 2. c <- Y b
* 3. d <- - X c + x_i
* 4. u <- 1 / <x_i, d>
* 5. v <- - u c
* 6. V <- Y + u c c^t
* 7. Z <- ( V v
v^t u )
* 8. a_new <- Z (Xy)
*/
if( list[i]==0 ){
/* 1. b <- X^t x_i */
dgemv_t( X_, n, dim-1, &orig_X_[n * i], b);
//printv( dim-1, b);
/* 2. c <- Y b */
dgemv_2( Y_, dim-1, dim-1, b, c);
//printv( dim-1, c);
/* 3. d <- - X c + x_i */
dgemv_1( X_, n, dim-1, c, &orig_X_[n * i], -1.0, 1.0, d);
//printv( n, d);
/* 4. u <- 1/<x_i, d> */
u = 1.0 / myddot_( &orig_X_[n * i], d, n);
//prints(u);
/* 5. v <- - u c */
mydscal_( c, dim-1, -u, v);
//printv( dim-1, v);
/* 6. V <- Y + u c c^t */
dger_1( Y_, c, c, dim-1, dim-1, u, V_);
//printM_( V_, dim-1, dim-1);
/* 7. Z */
/* V */
for(j=0; j<(dim-1); j++){
for(t=0; t<(dim-1); t++){
*(Z_ + j + (t*dim) ) = mat_( V_, dim-1, j, t);
}
}
/* v */
for(j=0; j<(dim-1); j++){
*(Z_ + dim-1 + (j*dim) ) = v[j];
*(Z_ + j + ((dim-1)*dim)) = v[j];
}
/* u */
*(Z_ + dim-1 + ((dim-1)*dim)) = u;
//printM_( Z_, dim, dim);
/* 8. a_new <- Z (Xy) */
Xy[dim-1] = orig_q[i];
dgemv_2( Z_, dim, dim, Xy, a_new);
//printv( dim, a_new);
/* test */
RSS_new = RSSvalue( dim, a_new, Xy, r);
if( RSS_new < RSS ){
RSS = RSS_new;
memo = i;
mydcopy_( Z_, W_, dim*dim);
mydcopy_( a_new, a, dim);
}
#if MYPARA_LOG
printf("%d: RSS = %f\n", i, RSS_new);
#endif
}
}
if( memo < 0 || memo >= p ){
if( memo == -1 ){
for(i=0; i<p; i++){
if( list[i] == 0 ){
memo = i;
break;
}
}
if( memo != -1 ){
printf("error in heur_forward.c\n");
stop();
}
}else{
printf("error in heur_forward.c\n");
stop();
}
}
AIC_new = AICvalue( n, dim, RSS);
if( AIC_new < AIC ){
AIC = AIC_new;
list[memo] = dim;
#if MYPARA_LOG
printf("---> %dth variable, AIC:%f\n", memo, AIC);
#endif
/* copy and free */
SCIPfreeBufferArray(scip, &Y_);
SCIP_CALL( SCIPallocBufferArray(scip, &Y_, dim*dim));
mydcopy_( W_, Y_, dim*dim);
SCIPfreeBufferArray(scip, &a_old);
SCIP_CALL( SCIPallocBufferArray(scip, &a_old, dim));
mydcopy_( a, a_old, dim);
/* update X_ and Xy */
mydcopy_( &orig_X_[n * memo], &X_[n * (dim-1)], n);
Xy[dim-1] = orig_q[memo];
}else{
memo = -1;
SCIPfreeBufferArray(scip, Y_);
#if MYPARA_LOG
printf("--> no selection, (AIC:%f)\n", AIC_new);
#endif
}
/* free */
SCIPfreeBufferArray(scip, &a_new);
SCIPfreeBufferArray(scip, &a);
SCIPfreeBufferArray(scip, &b);
SCIPfreeBufferArray(scip, &c);
SCIPfreeBufferArray(scip, &v);
SCIPfreeBufferArray(scip, &V_);
SCIPfreeBufferArray(scip, &Z_);
SCIPfreeBufferArray(scip, &W_);
if( memo == -1 ){
dim--;
break;
}
}
nsols = SCIPgetNSols(scip);
if( nsols < MP_NUM_SOL ){
store = 1;
}else{
sols = SCIPgetSols(scip);
objval = AIC;
nsols = MP_NUM_SOL;
if( objval < SCIPgetSolOrigObj(scip,sols[nsols-1]) ){
store = 1;
}else{
store = 0;
}
}
if( store ){
/* generate solution */
/* alloc */
SCIP_CALL( SCIPallocBufferArray(scip, &ep, n));
dgemv_1( X_, n, dim, a_old, y, -1.0, 1.0, ep);
/* set solution */
/* alloc */
SCIP_CALL( SCIPallocBufferArray(scip, &solvals, nvars));
SCIP_CALL( SCIPallocBufferArray(scip, &vars, nvars));
ct=0;
/* a */
for(i=0; i<p; ++i){
vars[ct] = var_a[i];
if( list[i] > 0 ){
solvals[ct] = a_old[list[i]-1];
}else{
solvals[ct] = 0.0;
}
ct++;
}
/* z */
for(i=0; i<p; i++){
vars[ct] = var_z[i];
if( list[i] > 0 ){
solvals[ct] = 1.0;
}else{
solvals[ct] = 0.0;
}
ct++;
}
/* ep */
for(i=0; i<n; ++i){
vars[ct] = var_ep[i];
solvals[ct] = ep[i];
ct++;
}
vars[ct] = var_rss;
solvals[ct] = myddot_( ep, ep, n);
ct++;
vars[ct] = var_log;
solvals[ct] = log(myddot_( ep, ep, n));
ct++;
if( ct!=nvars ){
SCIPerrorMessage("It is unexpected error in set sol,");
printf("( ct, nvars) = ( %d, %d)", ct, nvars);
stop();
}
SCIP_CALL( SCIPcreateSol(scip, &sol, heur));
SCIP_CALL( SCIPsetSolVals(scip, sol, nvars, vars, solvals));
SCIP_CALL( SCIPtrySolFree(scip, &sol, TRUE, FALSE, TRUE, TRUE, &success));
/* free */
SCIPfreeBufferArray(scip, &ep);
SCIPfreeBufferArray(scip, &solvals);
SCIPfreeBufferArray(scip, &vars);
}
/* free */
SCIPfreeBufferArray(scip, &d);
SCIPfreeBufferArray(scip, &X_);
SCIPfreeBufferArray(scip, &Xy);
SCIPfreeBufferArray(scip, &a_old);
SCIPfreeBufferArray(scip, &list);
SCIPfreeBufferArray(scip, &Branchz);
*result = SCIP_FOUNDSOL;
return SCIP_OKAY;
}
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpRapidlearning)
{/*lint --e{715}*/
SCIP* subscip; /* the subproblem created by rapid learning */
SCIP_SEPADATA* sepadata; /* separator's private data */
SCIP_VAR** vars; /* original problem's variables */
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_HASHMAP* varmapbw; /* mapping of sub-SCIP variables to SCIP variables */
SCIP_CONSHDLR** conshdlrs; /* array of constraint handler's that might that might obtain conflicts */
int* oldnconss; /* number of constraints without rapid learning conflicts */
SCIP_Longint nodelimit; /* node limit for the subproblem */
SCIP_Real timelimit; /* time limit for the subproblem */
SCIP_Real memorylimit; /* memory limit for the subproblem */
int nconshdlrs; /* size of conshdlr and oldnconss array */
int nfixedvars; /* number of variables that could be fixed by rapid learning */
int nvars; /* number of variables */
int restartnum; /* maximal number of conflicts that should be created */
int i; /* counter */
SCIP_Bool success; /* was problem creation / copying constraint successful? */
SCIP_RETCODE retcode; /* used for catching sub-SCIP errors in debug mode */
int nconflicts; /* statistic: number of conflicts applied */
int nbdchgs; /* statistic: number of bound changes applied */
int n1startinfers; /* statistic: number of one side infer values */
int n2startinfers; /* statistic: number of both side infer values */
SCIP_Bool soladded; /* statistic: was a new incumbent found? */
SCIP_Bool dualboundchg; /* statistic: was a new dual bound found? */
SCIP_Bool disabledualreductions; /* TRUE, if dual reductions in sub-SCIP are not valid for original SCIP,
* e.g., because a constraint could not be copied or a primal solution
* could not be copied back
*/
int ndiscvars;
soladded = FALSE;
assert(sepa != NULL);
assert(scip != NULL);
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
ndiscvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip)+SCIPgetNImplVars(scip);
/* only run when still not fixed binary variables exists */
if( ndiscvars == 0 )
return SCIP_OKAY;
/* get separator's data */
sepadata = SCIPsepaGetData(sepa);
assert(sepadata != NULL);
/* only run for integer programs */
if( !sepadata->contvars && ndiscvars != SCIPgetNVars(scip) )
return SCIP_OKAY;
/* only run if there are few enough continuous variables */
if( sepadata->contvars && SCIPgetNContVars(scip) > sepadata->contvarsquot * SCIPgetNVars(scip) )
return SCIP_OKAY;
/* do not run if pricers are present */
if( SCIPgetNActivePricers(scip) > 0 )
return SCIP_OKAY;
/* if the separator should be exclusive to the root node, this prevents multiple calls due to restarts */
if( SCIPsepaGetFreq(sepa) == 0 && SCIPsepaGetNCalls(sepa) > 0)
return SCIP_OKAY;
/* call separator at most once per node */
if( SCIPsepaGetNCallsAtNode(sepa) > 0 )
return SCIP_OKAY;
/* do not call rapid learning, if the problem is too big */
if( SCIPgetNVars(scip) > sepadata->maxnvars || SCIPgetNConss(scip) > sepadata->maxnconss )
return SCIP_OKAY;
if( SCIPisStopped(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* initializing the subproblem */
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
SCIP_CALL( SCIPcreate(&subscip) );
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
success = FALSE;
/* copy the subproblem */
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "rapid", FALSE, FALSE, &success) );
if( sepadata->copycuts )
{
/** copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, FALSE) );
}
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) (size_t) SCIPhashmapGetImage(varmapfw, vars[i]);
SCIPhashmapFree(&varmapfw);
/* this avoids dual presolving */
if( !success )
{
for( i = 0; i < nvars; i++ )
{
SCIP_CALL( SCIPaddVarLocks(subscip, subvars[i], 1, 1 ) );
}
}
SCIPdebugMessage("Copying SCIP was%s successful.\n", success ? "" : " not");
/* mimic an FD solver: DFS, no LP solving, 1-FUIP instead of all-FUIP */
SCIP_CALL( SCIPsetIntParam(subscip, "lp/solvefreq", -1) );
SCIP_CALL( SCIPsetIntParam(subscip, "conflict/fuiplevels", 1) );
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/dfs/stdpriority", INT_MAX/4) );
SCIP_CALL( SCIPsetBoolParam(subscip, "constraints/disableenfops", TRUE) );
SCIP_CALL( SCIPsetIntParam(subscip, "propagating/pseudoobj/freq", -1) );
/* use inference branching */
SCIP_CALL( SCIPsetBoolParam(subscip, "branching/inference/useweightedsum", FALSE) );
/* only create short conflicts */
SCIP_CALL( SCIPsetRealParam(subscip, "conflict/maxvarsfac", 0.05) );
/* set limits for the subproblem */
nodelimit = SCIPgetNLPIterations(scip);
nodelimit = MAX(sepadata->minnodes, nodelimit);
nodelimit = MIN(sepadata->maxnodes, nodelimit);
restartnum = 1000;
/* check whether there is enough time and memory left */
SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
if( !SCIPisInfinity(scip, timelimit) )
timelimit -= SCIPgetSolvingTime(scip);
SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
if( !SCIPisInfinity(scip, memorylimit) )
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
if( timelimit <= 0.0 || memorylimit <= 0.0 )
goto TERMINATE;
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nodelimit/5) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
SCIP_CALL( SCIPsetIntParam(subscip, "limits/restarts", 0) );
SCIP_CALL( SCIPsetIntParam(subscip, "conflict/restartnum", restartnum) );
/* forbid recursive call of heuristics and separators solving subMIPs */
SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
/* disable cutting plane separation */
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
/* disable expensive presolving */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );
/* do not abort subproblem on CTRL-C */
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
#ifndef SCIP_DEBUG
/* disable output to console */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
#endif
/* add an objective cutoff */
SCIP_CALL( SCIPsetObjlimit(subscip, SCIPgetUpperbound(scip)) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapbw, SCIPblkmem(scip), SCIPcalcHashtableSize(5 * nvars)) );
/* store reversing mapping of variables */
SCIP_CALL( SCIPtransformProb(subscip) );
for( i = 0; i < nvars; ++i)
{
SCIP_CALL( SCIPhashmapInsert(varmapbw, SCIPvarGetTransVar(subvars[i]), vars[i]) );
}
/** allocate memory for constraints storage. Each constraint that will be created from now on will be a conflict.
* Therefore, we need to remember oldnconss to get the conflicts from the FD search.
*/
nconshdlrs = 4;
SCIP_CALL( SCIPallocBufferArray(scip, &conshdlrs, nconshdlrs) );
SCIP_CALL( SCIPallocBufferArray(scip, &oldnconss, nconshdlrs) );
/* store number of constraints before rapid learning search */
conshdlrs[0] = SCIPfindConshdlr(subscip, "bounddisjunction");
conshdlrs[1] = SCIPfindConshdlr(subscip, "setppc");
conshdlrs[2] = SCIPfindConshdlr(subscip, "linear");
conshdlrs[3] = SCIPfindConshdlr(subscip, "logicor");
/* redundant constraints might be eliminated in presolving */
SCIP_CALL( SCIPpresolve(subscip));
for( i = 0; i < nconshdlrs; ++i)
{
if( conshdlrs[i] != NULL )
oldnconss[i] = SCIPconshdlrGetNConss(conshdlrs[i]);
}
nfixedvars = SCIPgetNFixedVars(scip);
/* solve the subproblem */
retcode = SCIPsolve(subscip);
/* Errors in solving the subproblem should not kill the overall solving process
* Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage("Error while solving subproblem in rapid learning separator; sub-SCIP terminated with code <%d>\n",retcode);
}
/* abort solving, if limit of applied conflicts is reached */
if( SCIPgetNConflictConssApplied(subscip) >= restartnum )
{
SCIPdebugMessage("finish after %lld successful conflict calls.\n", SCIPgetNConflictConssApplied(subscip));
}
/* if the first 20% of the solution process were successful, proceed */
else if( (sepadata->applyprimalsol && SCIPgetNSols(subscip) > 0 && SCIPisFeasLT(scip, SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip) ) )
|| (sepadata->applybdchgs && SCIPgetNFixedVars(subscip) > nfixedvars)
|| (sepadata->applyconflicts && SCIPgetNConflictConssApplied(subscip) > 0) )
{
SCIPdebugMessage("proceed solving after the first 20%% of the solution process, since:\n");
if( SCIPgetNSols(subscip) > 0 && SCIPisFeasLE(scip, SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip) ) )
{
SCIPdebugMessage(" - there was a better solution (%f < %f)\n",SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip));
}
if( SCIPgetNFixedVars(subscip) > nfixedvars )
{
SCIPdebugMessage(" - there were %d variables fixed\n", SCIPgetNFixedVars(scip)-nfixedvars );
}
if( SCIPgetNConflictConssFound(subscip) > 0 )
{
SCIPdebugMessage(" - there were %lld conflict constraints created\n", SCIPgetNConflictConssApplied(subscip));
}
/* set node limit to 100% */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nodelimit) );
/* solve the subproblem */
retcode = SCIPsolve(subscip);
/* Errors in solving the subproblem should not kill the overall solving process
* Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage("Error while solving subproblem in rapid learning separator; sub-SCIP terminated with code <%d>\n",retcode);
}
}
else
{
SCIPdebugMessage("do not proceed solving after the first 20%% of the solution process.\n");
}
#ifdef SCIP_DEBUG
SCIP_CALL( SCIPprintStatistics(subscip, NULL) );
#endif
disabledualreductions = FALSE;
/* check, whether a solution was found */
if( sepadata->applyprimalsol && SCIPgetNSols(subscip) > 0 && SCIPfindHeur(scip, "trysol") != NULL )
{
SCIP_HEUR* heurtrysol;
SCIP_SOL** subsols;
int nsubsols;
/* check, whether a solution was found;
* due to numerics, it might happen that not all solutions are feasible -> try all solutions until was declared to be feasible
*/
nsubsols = SCIPgetNSols(subscip);
subsols = SCIPgetSols(subscip);
soladded = FALSE;
heurtrysol = SCIPfindHeur(scip, "trysol");
/* sequentially add solutions to trysol heuristic */
for( i = 0; i < nsubsols && !soladded; ++i )
{
SCIPdebugMessage("Try to create new solution by copying subscip solution.\n");
SCIP_CALL( createNewSol(scip, subscip, subvars, heurtrysol, subsols[i], &soladded) );
}
if( !soladded || !SCIPisEQ(scip, SCIPgetSolOrigObj(subscip, subsols[i-1]), SCIPgetSolOrigObj(subscip, subsols[0])) )
disabledualreductions = TRUE;
}
/* if the sub problem was solved completely, we update the dual bound */
dualboundchg = FALSE;
if( sepadata->applysolved && !disabledualreductions
&& (SCIPgetStatus(subscip) == SCIP_STATUS_OPTIMAL || SCIPgetStatus(subscip) == SCIP_STATUS_INFEASIBLE) )
{
/* we need to multiply the dualbound with the scaling factor and add the offset,
* because this information has been disregarded in the sub-SCIP */
SCIPdebugMessage("Update old dualbound %g to new dualbound %g.\n", SCIPgetDualbound(scip), SCIPgetTransObjscale(scip) * SCIPgetDualbound(subscip) + SCIPgetTransObjoffset(scip));
SCIP_CALL( SCIPupdateLocalDualbound(scip, SCIPgetDualbound(subscip) * SCIPgetTransObjscale(scip) + SCIPgetTransObjoffset(scip)) );
dualboundchg = TRUE;
}
/* check, whether conflicts were created */
nconflicts = 0;
if( sepadata->applyconflicts && !disabledualreductions && SCIPgetNConflictConssApplied(subscip) > 0 )
{
SCIP_HASHMAP* consmap;
int hashtablesize;
assert(SCIPgetNConflictConssApplied(subscip) < (SCIP_Longint) INT_MAX);
hashtablesize = (int) SCIPgetNConflictConssApplied(subscip);
assert(hashtablesize < INT_MAX/5);
hashtablesize *= 5;
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&consmap, SCIPblkmem(scip), SCIPcalcHashtableSize(hashtablesize)) );
/* loop over all constraint handlers that might contain conflict constraints */
for( i = 0; i < nconshdlrs; ++i)
{
/* copy constraints that have been created in FD run */
if( conshdlrs[i] != NULL && SCIPconshdlrGetNConss(conshdlrs[i]) > oldnconss[i] )
{
SCIP_CONS** conss;
int c;
int nconss;
nconss = SCIPconshdlrGetNConss(conshdlrs[i]);
conss = SCIPconshdlrGetConss(conshdlrs[i]);
/* loop over all constraints that have been added in sub-SCIP run, these are the conflicts */
for( c = oldnconss[i]; c < nconss; ++c)
{
SCIP_CONS* cons;
SCIP_CONS* conscopy;
cons = conss[c];
assert(cons != NULL);
success = FALSE;
SCIP_CALL( SCIPgetConsCopy(subscip, scip, cons, &conscopy, conshdlrs[i], varmapbw, consmap, NULL,
SCIPconsIsInitial(cons), SCIPconsIsSeparated(cons), SCIPconsIsEnforced(cons), SCIPconsIsChecked(cons),
SCIPconsIsPropagated(cons), TRUE, FALSE, SCIPconsIsDynamic(cons),
SCIPconsIsRemovable(cons), FALSE, TRUE, &success) );
if( success )
{
nconflicts++;
SCIP_CALL( SCIPaddCons(scip, conscopy) );
SCIP_CALL( SCIPreleaseCons(scip, &conscopy) );
}
else
{
SCIPdebugMessage("failed to copy conflict constraint %s back to original SCIP\n", SCIPconsGetName(cons));
}
}
}
}
SCIPhashmapFree(&consmap);
}
/* check, whether tighter global bounds were detected */
nbdchgs = 0;
if( sepadata->applybdchgs && !disabledualreductions )
for( i = 0; i < nvars; ++i )
{
SCIP_Bool infeasible;
SCIP_Bool tightened;
assert(SCIPisLE(scip, SCIPvarGetLbGlobal(vars[i]), SCIPvarGetLbGlobal(subvars[i])));
assert(SCIPisLE(scip, SCIPvarGetLbGlobal(subvars[i]), SCIPvarGetUbGlobal(subvars[i])));
assert(SCIPisLE(scip, SCIPvarGetUbGlobal(subvars[i]), SCIPvarGetUbGlobal(vars[i])));
/* update the bounds of the original SCIP, if a better bound was proven in the sub-SCIP */
SCIP_CALL( SCIPtightenVarUb(scip, vars[i], SCIPvarGetUbGlobal(subvars[i]), FALSE, &infeasible, &tightened) );
if( tightened )
nbdchgs++;
SCIP_CALL( SCIPtightenVarLb(scip, vars[i], SCIPvarGetLbGlobal(subvars[i]), FALSE, &infeasible, &tightened) );
if( tightened )
nbdchgs++;
}
n1startinfers = 0;
n2startinfers = 0;
/* install start values for inference branching */
if( sepadata->applyinfervals && (!sepadata->reducedinfer || soladded || nbdchgs+nconflicts > 0) )
{
for( i = 0; i < nvars; ++i )
{
SCIP_Real downinfer;
SCIP_Real upinfer;
SCIP_Real downvsids;
SCIP_Real upvsids;
SCIP_Real downconflen;
SCIP_Real upconflen;
/* copy downwards branching statistics */
downvsids = SCIPgetVarVSIDS(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);
downconflen = SCIPgetVarAvgConflictlength(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);
downinfer = SCIPgetVarAvgInferences(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);
/* copy upwards branching statistics */
upvsids = SCIPgetVarVSIDS(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);
upconflen = SCIPgetVarAvgConflictlength(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);
upinfer = SCIPgetVarAvgInferences(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);
/* memorize statistics */
if( downinfer+downconflen+downvsids > 0.0 || upinfer+upconflen+upvsids != 0 )
n1startinfers++;
if( downinfer+downconflen+downvsids > 0.0 && upinfer+upconflen+upvsids != 0 )
n2startinfers++;
SCIP_CALL( SCIPinitVarBranchStats(scip, vars[i], 0.0, 0.0, downvsids, upvsids, downconflen, upconflen, downinfer, upinfer, 0.0, 0.0) );
}
}
SCIPdebugPrintf("XXX Rapidlearning added %d conflicts, changed %d bounds, %s primal solution, %s dual bound improvement.\n", nconflicts, nbdchgs, soladded ? "found" : "no",
dualboundchg ? "found" : "no");
SCIPdebugPrintf("YYY Infervalues initialized on one side: %5.2f %% of variables, %5.2f %% on both sides\n",
100.0 * n1startinfers/(SCIP_Real)nvars, 100.0 * n2startinfers/(SCIP_Real)nvars);
/* change result pointer */
if( nconflicts > 0 || dualboundchg )
*result = SCIP_CONSADDED;
else if( nbdchgs > 0 )
*result = SCIP_REDUCEDDOM;
/* free local data */
SCIPfreeBufferArray(scip, &oldnconss);
SCIPfreeBufferArray(scip, &conshdlrs);
SCIPhashmapFree(&varmapbw);
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
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;
}
/** 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;
}
/** transforms given solution of the master problem into solution of the original problem
* @todo think about types of epsilons used in this method
*/
SCIP_RETCODE GCGrelaxTransformMastersolToOrigsol(
SCIP* scip, /**< SCIP data structure */
SCIP_SOL* mastersol, /**< solution of the master problem, or NULL for current LP solution */
SCIP_SOL** origsol /**< pointer to store the new created original problem's solution */
)
{
SCIP* masterprob;
int npricingprobs;
int* blocknrs;
SCIP_Real* blockvalue;
SCIP_Real increaseval;
SCIP_VAR** mastervars;
SCIP_Real* mastervals;
int nmastervars;
SCIP_VAR** vars;
int nvars;
SCIP_Real feastol;
int i;
int j;
assert(scip != NULL);
assert(origsol != NULL);
masterprob = GCGrelaxGetMasterprob(scip);
npricingprobs = GCGrelaxGetNPricingprobs(scip);
assert( !SCIPisInfinity(scip, SCIPgetSolOrigObj(masterprob, mastersol)) );
SCIP_CALL( SCIPcreateSol(scip, origsol, GCGrelaxGetProbingheur(scip)) );
SCIP_CALL( SCIPallocBufferArray(scip, &blockvalue, npricingprobs) );
SCIP_CALL( SCIPallocBufferArray(scip, &blocknrs, npricingprobs) );
/* get variables of the master problem and their solution values */
SCIP_CALL( SCIPgetVarsData(masterprob, &mastervars, &nmastervars, NULL, NULL, NULL, NULL) );
assert(mastervars != NULL);
assert(nmastervars >= 0);
SCIP_CALL( SCIPallocBufferArray(scip, &mastervals, nmastervars) );
SCIP_CALL( SCIPgetSolVals(masterprob, mastersol, nmastervars, mastervars, mastervals) );
/* initialize the block values for the pricing problems */
for( i = 0; i < npricingprobs; i++ )
{
blockvalue[i] = 0.0;
blocknrs[i] = 0;
}
/* loop over all given master variables */
for( i = 0; i < nmastervars; i++ )
{
SCIP_VAR** origvars;
int norigvars;
SCIP_Real* origvals;
SCIP_Bool isray;
int blocknr;
origvars = GCGmasterVarGetOrigvars(mastervars[i]);
norigvars = GCGmasterVarGetNOrigvars(mastervars[i]);
origvals = GCGmasterVarGetOrigvals(mastervars[i]);
blocknr = GCGvarGetBlock(mastervars[i]);
isray = GCGmasterVarIsRay(mastervars[i]);
assert(GCGvarIsMaster(mastervars[i]));
assert(!SCIPisFeasNegative(scip, mastervals[i]));
/** @todo handle infinite master solution values */
assert(!SCIPisInfinity(scip, mastervals[i]));
/* first of all, handle variables representing rays */
if( isray )
{
assert(blocknr >= 0);
/* we also want to take into account variables representing rays, that have a small value (between normal and feas eps),
* so we do no feas comparison here */
if( SCIPisPositive(scip, mastervals[i]) )
{
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
if( SCIPisZero(scip, origvals[j]) )
break;
assert(!SCIPisZero(scip, origvals[j]));
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done later) */
if( GCGvarIsLinking(origvars[j]) )
continue;
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[j]), origvals[j] * mastervals[i], SCIPvarGetName(mastervars[i]));
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[j], origvals[j] * mastervals[i]) );
}
}
mastervals[i] = 0.0;
continue;
}
/* handle the variables with value >= 1 to get integral values in original solution */
while( SCIPisFeasGE(scip, mastervals[i], 1.0) )
{
/* variable was directly transferred to the master problem (only in linking conss or linking variable) */
/** @todo this may be the wrong place for this case, handle it before the while loop
* and remove the similar case in the next while loop */
if( blocknr == -1 )
{
assert(norigvars == 1);
assert(origvals[0] == 1.0);
/* increase the corresponding value */
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[0]), origvals[0] * mastervals[i], SCIPvarGetName(mastervars[i]));
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[0], origvals[0] * mastervals[i]) );
mastervals[i] = 0.0;
}
else
{
assert(blocknr >= 0);
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
SCIP_VAR* pricingvar;
int norigpricingvars;
SCIP_VAR** origpricingvars;
if( SCIPisZero(scip, origvals[j]) )
break;
assert(!SCIPisZero(scip, origvals[j]));
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done above) */
if( GCGvarIsLinking(origvars[j]) )
continue;
pricingvar = GCGoriginalVarGetPricingVar(origvars[j]);
assert(GCGvarIsPricing(pricingvar));
norigpricingvars = GCGpricingVarGetNOrigvars(pricingvar);
origpricingvars = GCGpricingVarGetOrigvars(pricingvar);
/* just in case a variable has a value higher than the number of blocks, it represents */
if( norigpricingvars <= blocknrs[blocknr] )
{
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[norigpricingvars-1]), mastervals[i] * origvals[j], SCIPvarGetName(mastervars[i]));
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[norigpricingvars-1], mastervals[i] * origvals[j]) );
mastervals[i] = 1.0;
}
/* this should be default */
else
{
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[blocknrs[blocknr]]), origvals[j], SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[blocknrs[blocknr]], origvals[j]) );
}
}
mastervals[i] = mastervals[i] - 1.0;
blocknrs[blocknr]++;
}
}
}
/* loop over all given master variables */
for( i = 0; i < nmastervars; i++ )
{
SCIP_VAR** origvars;
int norigvars;
SCIP_Real* origvals;
int blocknr;
origvars = GCGmasterVarGetOrigvars(mastervars[i]);
norigvars = GCGmasterVarGetNOrigvars(mastervars[i]);
origvals = GCGmasterVarGetOrigvals(mastervars[i]);
blocknr = GCGvarGetBlock(mastervars[i]);
if( SCIPisFeasZero(scip, mastervals[i]) )
{
continue;
}
assert(SCIPisFeasGE(scip, mastervals[i], 0.0) && SCIPisFeasLT(scip, mastervals[i], 1.0));
while( SCIPisFeasPositive(scip, mastervals[i]) )
{
assert(GCGvarIsMaster(mastervars[i]));
assert(!GCGmasterVarIsRay(mastervars[i]));
if( blocknr == -1 )
{
assert(norigvars == 1);
assert(origvals[0] == 1.0);
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[0]), origvals[0] * mastervals[i], SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[0], origvals[0] * mastervals[i]) );
mastervals[i] = 0.0;
}
else
{
increaseval = MIN(mastervals[i], 1.0 - blockvalue[blocknr]);
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
SCIP_VAR* pricingvar;
int norigpricingvars;
SCIP_VAR** origpricingvars;
if( SCIPisZero(scip, origvals[j]) )
continue;
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done above) */
if( GCGvarIsLinking(origvars[j]) )
continue;
pricingvar = GCGoriginalVarGetPricingVar(origvars[j]);
assert(GCGvarIsPricing(pricingvar));
norigpricingvars = GCGpricingVarGetNOrigvars(pricingvar);
origpricingvars = GCGpricingVarGetOrigvars(pricingvar);
if( norigpricingvars <= blocknrs[blocknr] )
{
increaseval = mastervals[i];
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[norigpricingvars-1]), origvals[j] * increaseval, SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[norigpricingvars-1], origvals[j] * increaseval) );
}
else
{
/* increase the corresponding value */
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[blocknrs[blocknr]]), origvals[j] * increaseval, SCIPvarGetName(mastervars[i]) );
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[blocknrs[blocknr]], origvals[j] * increaseval) );
}
}
mastervals[i] = mastervals[i] - increaseval;
if( SCIPisFeasZero(scip, mastervals[i]) )
{
mastervals[i] = 0.0;
}
blockvalue[blocknr] += increaseval;
/* if the value assigned to the block is equal to 1, this block is full and we take the next block */
if( SCIPisFeasGE(scip, blockvalue[blocknr], 1.0) )
{
blockvalue[blocknr] = 0.0;
blocknrs[blocknr]++;
}
}
}
}
SCIPfreeBufferArray(scip, &mastervals);
SCIPfreeBufferArray(scip, &blocknrs);
SCIPfreeBufferArray(scip, &blockvalue);
/* if the solution violates one of its bounds by more than feastol
* and less than 10*feastol, round it and print a warning
*/
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPgetRealParam(scip, "numerics/feastol", &feastol) );
for( i = 0; i < nvars; ++i )
{
SCIP_Real solval;
SCIP_Real lb;
SCIP_Real ub;
solval = SCIPgetSolVal(scip, *origsol, vars[i]);
lb = SCIPvarGetLbLocal(vars[i]);
ub = SCIPvarGetUbLocal(vars[i]);
if( SCIPisFeasGT(scip, solval, ub) && EPSEQ(solval, ub, 10 * feastol) )
{
SCIP_CALL( SCIPsetSolVal(scip, *origsol, vars[i], ub) );
SCIPwarningMessage(scip, "Variable %s rounded from %g to %g in relaxation solution\n",
SCIPvarGetName(vars[i]), solval, ub);
}
else if( SCIPisFeasLT(scip, solval, lb) && EPSEQ(solval, lb, 10 * feastol) )
{
SCIP_CALL( SCIPsetSolVal(scip, *origsol, vars[i], lb) );
SCIPwarningMessage(scip, "Variable %s rounded from %g to %g in relaxation solution\n",
SCIPvarGetName(vars[i]), solval, lb);
}
}
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecLocalbranching)
{ /*lint --e{715}*/
SCIP_Longint maxnnodes; /* maximum number of subnodes */
SCIP_Longint nsubnodes; /* nodelimit for subscip */
SCIP_HEURDATA* heurdata;
SCIP* subscip; /* the subproblem created by localbranching */
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_SOL* bestsol; /* best solution so far */
SCIP_EVENTHDLR* eventhdlr; /* event handler for LP events */
SCIP_Real timelimit; /* timelimit for subscip (equals remaining time of scip) */
SCIP_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real upperbound;
SCIP_Real memorylimit;
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_VAR** vars;
int nvars;
int i;
SCIP_Bool success;
SCIP_RETCODE retcode;
assert(heur != NULL);
assert(scip != NULL);
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert( heurdata != NULL );
/* there should be enough binary variables that a local branching constraint makes sense */
if( SCIPgetNBinVars(scip) < 2*heurdata->neighborhoodsize )
return SCIP_OKAY;
*result = SCIP_DELAYED;
/* only call heuristic, if an IP solution is at hand */
if( SCIPgetNSols(scip) <= 0 )
return SCIP_OKAY;
bestsol = SCIPgetBestSol(scip);
assert(bestsol != NULL);
/* only call heuristic, if the best solution comes from transformed problem */
if( SCIPsolIsOriginal(bestsol) )
return SCIP_OKAY;
/* only call heuristic, if enough nodes were processed since last incumbent */
if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip, bestsol) < heurdata->nwaitingnodes)
return SCIP_OKAY;
/* only call heuristic, if the best solution does not come from trivial heuristic */
if( SCIPsolGetHeur(bestsol) != NULL && strcmp(SCIPheurGetName(SCIPsolGetHeur(bestsol)), "trivial") == 0 )
return SCIP_OKAY;
/* reset neighborhood and minnodes, if new solution was found */
if( heurdata->lastsol != bestsol )
{
heurdata->curneighborhoodsize = heurdata->neighborhoodsize;
heurdata->curminnodes = heurdata->minnodes;
heurdata->emptyneighborhoodsize = 0;
heurdata->callstatus = EXECUTE;
heurdata->lastsol = bestsol;
}
/* if no new solution was found and local branching also seems to fail, just keep on waiting */
if( heurdata->callstatus == WAITFORNEWSOL )
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* calculate the maximal number of branching nodes until heuristic is aborted */
maxnnodes = (SCIP_Longint)(heurdata->nodesquot * SCIPgetNNodes(scip));
/* reward local branching if it succeeded often */
maxnnodes = (SCIP_Longint)(maxnnodes * (1.0 + 2.0*(SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur)+1.0)));
maxnnodes -= 100 * SCIPheurGetNCalls(heur); /* count the setup costs for the sub-MIP as 100 nodes */
maxnnodes += heurdata->nodesofs;
/* determine the node limit for the current process */
nsubnodes = maxnnodes - heurdata->usednodes;
nsubnodes = MIN(nsubnodes, heurdata->maxnodes);
/* check whether we have enough nodes left to call sub problem solving */
if( nsubnodes < heurdata->curminnodes )
return SCIP_OKAY;
if( SCIPisStopped(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
SCIPdebugMessage("running localbranching heuristic ...\n");
/* get the data of the variables and the best solution */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* initializing the subproblem */
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
SCIP_CALL( SCIPcreate(&subscip) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
success = FALSE;
eventhdlr = NULL;
if( heurdata->uselprows )
{
char probname[SCIP_MAXSTRLEN];
/* copy all plugins */
SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );
/* get name of the original problem and add the string "_localbranchsub" */
(void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_localbranchsub", SCIPgetProbName(scip));
/* create the subproblem */
SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );
/* copy all variables */
SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
}
else
{
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "localbranchsub", TRUE, FALSE, TRUE, &success) );
if( heurdata->copycuts )
{
/* copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
}
/* create event handler for LP events */
SCIP_CALL( SCIPincludeEventhdlrBasic(subscip, &eventhdlr, EVENTHDLR_NAME, EVENTHDLR_DESC, eventExecLocalbranching, NULL) );
if( eventhdlr == NULL )
{
SCIPerrorMessage("event handler for "HEUR_NAME" heuristic not found.\n");
return SCIP_PLUGINNOTFOUND;
}
}
SCIPdebugMessage("Copying the plugins was %ssuccessful.\n", success ? "" : "not ");
for (i = 0; i < nvars; ++i)
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
/* free hash map */
SCIPhashmapFree(&varmapfw);
/* if the subproblem could not be created, free memory and return */
if( !success )
{
*result = SCIP_DIDNOTRUN;
goto TERMINATE;
}
/* do not abort subproblem on CTRL-C */
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
#ifndef SCIP_DEBUG
/* disable output to console */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
#endif
/* check whether there is enough time and memory left */
SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
if( !SCIPisInfinity(scip, timelimit) )
timelimit -= SCIPgetSolvingTime(scip);
SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
/* substract the memory already used by the main SCIP and the estimated memory usage of external software */
if( !SCIPisInfinity(scip, memorylimit) )
{
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
}
/* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
goto TERMINATE;
/* set limits for the subproblem */
heurdata->nodelimit = nsubnodes;
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nsubnodes) );
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/stallnodes", MAX(10, nsubnodes/10)) );
SCIP_CALL( SCIPsetIntParam(subscip, "limits/bestsol", 3) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
/* forbid recursive call of heuristics and separators solving subMIPs */
SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
/* disable cutting plane separation */
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
/* disable expensive presolving */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );
/* use best estimate node selection */
if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
}
/* use inference branching */
if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
}
/* disable conflict analysis */
if( !SCIPisParamFixed(subscip, "conflict/useprop") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/useinflp") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/usesb") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/usepseudo") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
}
/* employ a limit on the number of enforcement rounds in the quadratic constraint handler; this fixes the issue that
* sometimes the quadratic constraint handler needs hundreds or thousands of enforcement rounds to determine the
* feasibility status of a single node without fractional branching candidates by separation (namely for uflquad
* instances); however, the solution status of the sub-SCIP might get corrupted by this; hence no deductions shall be
* made for the original SCIP
*/
if( SCIPfindConshdlr(subscip, "quadratic") != NULL && !SCIPisParamFixed(subscip, "constraints/quadratic/enfolplimit") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "constraints/quadratic/enfolplimit", 500) );
}
/* copy the original problem and add the local branching constraint */
if( heurdata->uselprows )
{
SCIP_CALL( createSubproblem(scip, subscip, subvars) );
}
SCIP_CALL( addLocalBranchingConstraint(scip, subscip, subvars, heurdata) );
/* add an objective cutoff */
cutoff = SCIPinfinity(scip);
assert( !SCIPisInfinity(scip,SCIPgetUpperbound(scip)) );
upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
{
cutoff = (1-heurdata->minimprove)*SCIPgetUpperbound(scip) + heurdata->minimprove*SCIPgetLowerbound(scip);
}
else
{
if( SCIPgetUpperbound ( scip ) >= 0 )
cutoff = ( 1 - heurdata->minimprove ) * SCIPgetUpperbound ( scip );
else
cutoff = ( 1 + heurdata->minimprove ) * SCIPgetUpperbound ( scip );
}
cutoff = MIN(upperbound, cutoff );
SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );
/* catch LP events of sub-SCIP */
if( !heurdata->uselprows )
{
assert(eventhdlr != NULL);
SCIP_CALL( SCIPtransformProb(subscip) );
SCIP_CALL( SCIPcatchEvent(subscip, SCIP_EVENTTYPE_LPSOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, NULL) );
}
/* solve the subproblem */
SCIPdebugMessage("solving local branching subproblem with neighborhoodsize %d and maxnodes %"SCIP_LONGINT_FORMAT"\n",
heurdata->curneighborhoodsize, nsubnodes);
retcode = SCIPsolve(subscip);
/* drop LP events of sub-SCIP */
if( !heurdata->uselprows )
{
assert(eventhdlr != NULL);
SCIP_CALL( SCIPdropEvent(subscip, SCIP_EVENTTYPE_LPSOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, -1) );
}
/* Errors in solving the subproblem should not kill the overall solving process
* Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage(scip, "Error while solving subproblem in local branching heuristic; sub-SCIP terminated with code <%d>\n",retcode);
}
/* print solving statistics of subproblem if we are in SCIP's debug mode */
SCIPdebug( SCIP_CALL( SCIPprintStatistics(subscip, NULL) ) );
heurdata->usednodes += SCIPgetNNodes(subscip);
SCIPdebugMessage("local branching used %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT" nodes\n",
SCIPgetNNodes(subscip), nsubnodes);
/* check, whether a solution was found */
if( SCIPgetNSols(subscip) > 0 )
{
SCIP_SOL** subsols;
int nsubsols;
/* check, whether a solution was found;
* due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
*/
nsubsols = SCIPgetNSols(subscip);
subsols = SCIPgetSols(subscip);
success = FALSE;
for( i = 0; i < nsubsols && !success; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
}
if( success )
{
SCIPdebugMessage("-> accepted solution of value %g\n", SCIPgetSolOrigObj(subscip, subsols[i]));
*result = SCIP_FOUNDSOL;
}
}
/* check the status of the sub-MIP */
switch( SCIPgetStatus(subscip) )
{
case SCIP_STATUS_OPTIMAL:
case SCIP_STATUS_BESTSOLLIMIT:
heurdata->callstatus = WAITFORNEWSOL; /* new solution will immediately be installed at next call */
SCIPdebugMessage(" -> found new solution\n");
break;
case SCIP_STATUS_NODELIMIT:
case SCIP_STATUS_STALLNODELIMIT:
case SCIP_STATUS_TOTALNODELIMIT:
heurdata->callstatus = EXECUTE;
heurdata->curneighborhoodsize = (heurdata->emptyneighborhoodsize + heurdata->curneighborhoodsize)/2;
heurdata->curminnodes *= 2;
SCIPdebugMessage(" -> node limit reached: reduced neighborhood to %d, increased minnodes to %d\n",
heurdata->curneighborhoodsize, heurdata->curminnodes);
if( heurdata->curneighborhoodsize <= heurdata->emptyneighborhoodsize )
{
heurdata->callstatus = WAITFORNEWSOL;
SCIPdebugMessage(" -> new neighborhood was already proven to be empty: wait for new solution\n");
}
break;
case SCIP_STATUS_INFEASIBLE:
case SCIP_STATUS_INFORUNBD:
heurdata->emptyneighborhoodsize = heurdata->curneighborhoodsize;
heurdata->curneighborhoodsize += heurdata->curneighborhoodsize/2;
heurdata->curneighborhoodsize = MAX(heurdata->curneighborhoodsize, heurdata->emptyneighborhoodsize + 2);
heurdata->callstatus = EXECUTE;
SCIPdebugMessage(" -> neighborhood is empty: increased neighborhood to %d\n", heurdata->curneighborhoodsize);
break;
case SCIP_STATUS_UNKNOWN:
case SCIP_STATUS_USERINTERRUPT:
case SCIP_STATUS_TIMELIMIT:
case SCIP_STATUS_MEMLIMIT:
case SCIP_STATUS_GAPLIMIT:
case SCIP_STATUS_SOLLIMIT:
case SCIP_STATUS_UNBOUNDED:
default:
heurdata->callstatus = WAITFORNEWSOL;
SCIPdebugMessage(" -> unexpected sub-MIP status <%d>: waiting for new solution\n", SCIPgetStatus(subscip));
break;
}
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/* standard "main" method for mex interface */
void mexFunction(
int nlhs, /* number of expected outputs */
mxArray* plhs[], /* array of pointers to output arguments */
int nrhs, /* number of inputs */
const mxArray* prhs[] /* array of pointers to input arguments */
)
{
SCIP* scip;
SCIP_VAR** vars;
SCIP_Real* objs;
SCIP_Real* lhss;
SCIP_Real* rhss;
SCIP_Real* lbs;
SCIP_Real* ubs;
SCIP_Real* matrix;
SCIP_Real* bestsol;
SCIP_Real* objval;
char* vartypes;
char objsense[SCIP_MAXSTRLEN];
int nvars;
int nconss;
int stringsize;
int i;
if( SCIPmajorVersion() < 2 )
{
mexErrMsgTxt("SCIP versions less than 2.0 are not supported\n");
return;
}
/* initialize SCIP */
SCIP_CALL_ABORT( SCIPcreate(&scip) );
/* output SCIP information */
SCIPprintVersion(scip, NULL);
/* include default SCIP plugins */
SCIP_CALL_ABORT( SCIPincludeDefaultPlugins(scip) );
if( nlhs != 2 || nrhs != 8 )
mexErrMsgTxt("invalid number of parameters. Call as [bestsol, objval] = matscip(matrix, lhs, rhs, obj, lb, ub, vartype, objsense)\n");
if( mxIsSparse(prhs[0]) )
mexErrMsgTxt("sparse matrices are not supported yet"); /* ???????? of course this has to change */
/* get linear constraint coefficient matrix */
matrix = mxGetPr(prhs[0]);
if( matrix == NULL )
mexErrMsgTxt("matrix must not be NULL");
if( mxGetNumberOfDimensions(prhs[0]) != 2 )
mexErrMsgTxt("matrix must have exactly two dimensions");
/* get dimensions of matrix */
nconss = mxGetM(prhs[0]);
nvars = mxGetN(prhs[0]);
assert(nconss > 0);
assert(nvars > 0);
/* get left hand sides of linear constraints */
lhss = mxGetPr(prhs[1]);
if( mxGetM(prhs[1]) != nconss )
mexErrMsgTxt("dimension of left hand side vector does not match matrix dimension");
assert(lhss != NULL);
/* get right hand sides of linear constraints */
rhss = mxGetPr(prhs[2]);
if( mxGetM(prhs[2]) != nconss )
mexErrMsgTxt("dimension of right hand side vector does not match matrix dimension");
assert(rhss != NULL);
/* get objective coefficients */
objs = mxGetPr(prhs[3]);
if( mxGetM(prhs[3]) != nvars )
mexErrMsgTxt("dimension of objective coefficient vector does not match matrix dimension");
/* get lower bounds of variables */
lbs = mxGetPr(prhs[4]);
if( mxGetM(prhs[4]) != nvars )
mexErrMsgTxt("dimension of lower bound vector does not match matrix dimension");
/* get upper bounds of variables */
ubs = mxGetPr(prhs[5]);
if( mxGetM(prhs[5]) != nvars )
mexErrMsgTxt("dimension of upper bound vector does not match matrix dimension");
/* allocate memory for variable type characters */
SCIP_CALL_ABORT( SCIPallocMemoryArray(scip, &vartypes, nvars+1) );
/* get variable types */
if( mxGetString(prhs[6], vartypes, nvars+1) != 0 )
mexErrMsgTxt("Error when parsing variable types, maybe a wrong vector dimension?");
/* get objective sense */
stringsize = mxGetNumberOfElements(prhs[7]);
if( stringsize != 3 )
mexErrMsgTxt("objective sense must be a three character word: \"max\" or \"min\"");
if( mxGetString(prhs[7], objsense, stringsize+1) != 0)
mexErrMsgTxt("Error when parsing objective sense string");
if( strcmp(objsense,"max") != 0 && strcmp(objsense,"min") != 0 )
mexErrMsgTxt("objective sense must be either \"max\" or \"min\"");
/* get output parameters */
plhs[0] = mxCreateDoubleMatrix(nvars, 1, mxREAL);
bestsol = mxGetPr(plhs[0]);
plhs[1] = mxCreateDoubleScalar(mxREAL);
objval = mxGetPr(plhs[1]);
/* create SCIP problem */
SCIP_CALL_ABORT( SCIPcreateProb(scip, "mex_prob", NULL, NULL, NULL, NULL, NULL, NULL, NULL) );
/* allocate memory for variable array */
SCIP_CALL_ABORT( SCIPallocMemoryArray(scip, &vars, nvars) );
/* create variables */
for( i = 0; i < nvars; ++i)
{
SCIP_VARTYPE vartype;
char varname[SCIP_MAXSTRLEN];
/* convert vartype character to SCIP vartype */
if( vartypes[i] == 'i' )
vartype = SCIP_VARTYPE_INTEGER;
else if( vartypes[i] == 'b' )
vartype = SCIP_VARTYPE_BINARY;
else if( vartypes[i] == 'c' )
vartype = SCIP_VARTYPE_CONTINUOUS;
else
mexErrMsgTxt("unkown variable type");
/* variables get canonic names x_i */
(void) SCIPsnprintf(varname, SCIP_MAXSTRLEN, "x_%d", i);
/* create variable object and add it to SCIP */
SCIP_CALL_ABORT( SCIPcreateVar(scip, &vars[i], varname, lbs[i], ubs[i], objs[i],
vartype, TRUE, FALSE, NULL, NULL, NULL, NULL, NULL) );
assert(vars[i] != NULL);
SCIP_CALL_ABORT( SCIPaddVar(scip, vars[i]) );
}
/* create linear constraints */
for( i = 0; i < nconss; ++i )
{
SCIP_CONS* cons;
char consname[SCIP_MAXSTRLEN];
int j;
/* constraints get canonic names cons_i */
(void) SCIPsnprintf(consname, SCIP_MAXSTRLEN, "cons_%d", i);
/* create empty linear constraint */
SCIP_CALL_ABORT( SCIPcreateConsLinear(scip, &cons, consname, 0, NULL, NULL, lhss[i], rhss[i],
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE) );
/* add non-zero coefficients to linear constraint */
for( j = 0; j < nvars; ++j )
{
if( !SCIPisFeasZero(scip, matrix[i+j*nconss]) )
{
SCIP_CALL_ABORT( SCIPaddCoefLinear(scip, cons, vars[j], matrix[i+j*nconss]) );
}
}
/* add constraint to SCIP and release it */
SCIP_CALL_ABORT( SCIPaddCons(scip, cons) );
SCIP_CALL_ABORT( SCIPreleaseCons(scip, &cons) );
}
/* set objective sense in SCIP */
if( strcmp(objsense,"max") == 0)
{
SCIP_CALL_ABORT( SCIPsetObjsense(scip, SCIP_OBJSENSE_MAXIMIZE) );
}
else if( strcmp(objsense,"min") == 0)
{
SCIP_CALL_ABORT( SCIPsetObjsense(scip, SCIP_OBJSENSE_MINIMIZE) );
}
else
/* this should have been caught earlier when parsing objsense */
mexErrMsgTxt("unkown objective sense");
/* solve SCIP problem */
SCIP_CALL_ABORT( SCIPsolve(scip) );
/* if SCIP found a solution, pass it back into MATLAB output parameters */
if( SCIPgetNSols > 0 )
{
SCIP_SOL* scipbestsol;
/* get incumbent solution vector */
scipbestsol = SCIPgetBestSol(scip);
assert(scipbestsol != NULL);
/* get objective value of incumbent solution */
*objval = SCIPgetSolOrigObj(scip, scipbestsol);
assert(!SCIPisInfinity(scip, REALABS(*objval)));
/* copy solution values into output vector */
for( i = 0; i < nvars; ++i )
bestsol[i] = SCIPgetSolVal(scip,scipbestsol,vars[i]);
}
/* release variables */
for( i = 0; i < nvars; ++i )
{
SCIP_CALL_ABORT( SCIPreleaseVar(scip, &vars[i]) );
}
/* free memory for variable arrays */
SCIPfreeMemoryArray(scip, &vartypes);
SCIPfreeMemoryArray(scip, &vars);
/* deinitialize SCIP */
SCIP_CALL_ABORT( SCIPfree(&scip) );
/* check for memory leaks */
BMScheckEmptyMemory();
return;
}
/** reduced cost pricing method of variable pricer for feasible LPs */
static
SCIP_DECL_PRICERREDCOST(pricerRedcostBinpacking)
{ /*lint --e{715}*/
SCIP* subscip;
SCIP_PRICERDATA* pricerdata;
SCIP_CONS** conss;
SCIP_VAR** vars;
int* ids;
SCIP_Bool addvar;
SCIP_SOL** sols;
int nsols;
int s;
int nitems;
SCIP_Longint capacity;
SCIP_Real timelimit;
SCIP_Real memorylimit;
assert(scip != NULL);
assert(pricer != NULL);
(*result) = SCIP_DIDNOTRUN;
/* get the pricer data */
pricerdata = SCIPpricerGetData(pricer);
assert(pricerdata != NULL);
capacity = pricerdata->capacity;
conss = pricerdata->conss;
ids = pricerdata->ids;
nitems = pricerdata->nitems;
/* get the remaining time and memory limit */
SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
if( !SCIPisInfinity(scip, timelimit) )
timelimit -= SCIPgetSolvingTime(scip);
SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
if( !SCIPisInfinity(scip, memorylimit) )
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
/* initialize SCIP */
SCIP_CALL( SCIPcreate(&subscip) );
SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );
/* create problem in sub SCIP */
SCIP_CALL( SCIPcreateProbBasic(subscip, "pricing") );
SCIP_CALL( SCIPsetObjsense(subscip, SCIP_OBJSENSE_MAXIMIZE) );
/* do not abort subproblem on CTRL-C */
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
/* disable output to console */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
/* set time and memory limit */
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
SCIP_CALL( SCIPallocMemoryArray(subscip, &vars, nitems) );
/* initialization local pricing problem */
SCIP_CALL( initPricing(scip, pricerdata, subscip, vars) );
SCIPdebugMessage("solve pricer problem\n");
/* solve sub SCIP */
SCIP_CALL( SCIPsolve(subscip) );
sols = SCIPgetSols(subscip);
nsols = SCIPgetNSols(subscip);
addvar = FALSE;
/* loop over all solutions and create the corresponding column to master if the reduced cost are negative for master,
* that is the objective value i greater than 1.0
*/
for( s = 0; s < nsols; ++s )
{
SCIP_Bool feasible;
SCIP_SOL* sol;
/* the soultion should be sorted w.r.t. the objective function value */
assert(s == 0 || SCIPisFeasGE(subscip, SCIPgetSolOrigObj(subscip, sols[s-1]), SCIPgetSolOrigObj(subscip, sols[s])));
sol = sols[s];
assert(sol != NULL);
/* check if solution is feasible in original sub SCIP */
SCIP_CALL( SCIPcheckSolOrig(subscip, sol, &feasible, FALSE, FALSE ) );
if( !feasible )
{
SCIPwarningMessage(scip, "solution in pricing problem (capacity <%d>) is infeasible\n", capacity);
continue;
}
/* check if the solution has a value greater than 1.0 */
if( SCIPisFeasGT(subscip, SCIPgetSolOrigObj(subscip, sol), 1.0) )
{
SCIP_VAR* var;
SCIP_VARDATA* vardata;
int* consids;
char strtmp[SCIP_MAXSTRLEN];
char name[SCIP_MAXSTRLEN];
int nconss;
int o;
int v;
SCIPdebug( SCIP_CALL( SCIPprintSol(subscip, sol, NULL, FALSE) ) );
nconss = 0;
(void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "items");
SCIP_CALL( SCIPallocBufferArray(scip, &consids, nitems) );
/* check which variables are fixed -> which item belongs to this packing */
for( o = 0, v = 0; o < nitems; ++o )
{
if( !SCIPconsIsEnabled(conss[o]) )
continue;
assert(SCIPgetNFixedonesSetppc(scip, conss[o]) == 0);
if( SCIPgetSolVal(subscip, sol, vars[v]) > 0.5 )
{
(void) SCIPsnprintf(strtmp, SCIP_MAXSTRLEN, "_%d", ids[o]);
strcat(name, strtmp);
consids[nconss] = o;
nconss++;
}
else
assert( SCIPisFeasEQ(subscip, SCIPgetSolVal(subscip, sol, vars[v]), 0.0) );
v++;
}
SCIP_CALL( SCIPvardataCreateBinpacking(scip, &vardata, consids, nconss) );
/* create variable for a new column with objective function coefficient 0.0 */
SCIP_CALL( SCIPcreateVarBinpacking(scip, &var, name, 1.0, FALSE, TRUE, vardata) );
/* add the new variable to the pricer store */
SCIP_CALL( SCIPaddPricedVar(scip, var, 1.0) );
addvar = TRUE;
/* change the upper bound of the binary variable to lazy since the upper bound is already enforced due to
* the objective function the set covering constraint; The reason for doing is that, is to avoid the bound
* of x <= 1 in the LP relaxation since this bound constraint would produce a dual variable which might have
* a positive reduced cost
*/
SCIP_CALL( SCIPchgVarUbLazy(scip, var, 1.0) );
/* check which variable are fixed -> which orders belong to this packing */
for( v = 0; v < nconss; ++v )
{
assert(SCIPconsIsEnabled(conss[consids[v]]));
SCIP_CALL( SCIPaddCoefSetppc(scip, conss[consids[v]], var) );
}
SCIPdebug(SCIPprintVar(scip, var, NULL) );
SCIP_CALL( SCIPreleaseVar(scip, &var) );
SCIPfreeBufferArray(scip, &consids);
}
else
break;
}
/* free pricer MIP */
SCIPfreeMemoryArray(subscip, &vars);
if( addvar || SCIPgetStatus(subscip) == SCIP_STATUS_OPTIMAL )
(*result) = SCIP_SUCCESS;
/* free sub SCIP */
SCIP_CALL( SCIPfree(&subscip) );
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;
}
/** 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;
}
