/* apply all changes to the submip */
static
SCIP_RETCODE applyDomainChanges(
SCIP* subscip, /**< scip to apply domain changes */
SCIP_VAR** vars, /**< variables in original scip instance */
SCIP_Real* bounds, /**< bounds which should be applied */
SCIP_BOUNDTYPE* boundtypes, /**< bound types for bounds which should be applied */
int nvars, /**< number of variables */
SCIP_HASHMAP* varmap /**< hashmap for identifiing the corresponding variables in subscip */
)
{
SCIP_VAR* subscipvar;
int v;
assert(subscip != NULL);
assert(vars != NULL);
assert(bounds != NULL);
assert(boundtypes != NULL);
assert(nvars > 0);
assert(varmap != NULL);
/* need to do a downwards loop, because ing decisions are collect from bottom to root and if we ed twice on a variable, then the weaker bound is behind the stronger in this array */
for( v = nvars - 1; v >= 0; --v )
{
subscipvar = (SCIP_VAR*) SCIPhashmapGetImage(varmap, vars[v]);
assert(subscipvar != NULL);
if( boundtypes[v] == SCIP_BOUNDTYPE_LOWER )
{
SCIP_CALL( SCIPchgVarLbGlobal(subscip, subscipvar, bounds[v]) );
}
else
{
assert(boundtypes[v] == SCIP_BOUNDTYPE_UPPER);
SCIP_CALL( SCIPchgVarUbGlobal(subscip, subscipvar, bounds[v]) );
}
}
return SCIP_OKAY;
}
/** creates a subproblem for subscip by fixing a number of variables */
static
SCIP_RETCODE createSubproblem(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP data structure for the subproblem */
SCIP_VAR** subvars, /**< the variables of the subproblem */
SCIP_Real minfixingrate, /**< percentage of integer variables that have to be fixed */
unsigned int* randseed, /**< a seed value for the random number generator */
SCIP_Bool uselprows /**< should subproblem be created out of the rows in the LP rows? */
)
{
SCIP_VAR** vars; /* original scip variables */
SCIP_SOL* sol; /* pool of solutions */
SCIP_Bool* marked; /* array of markers, which variables to fixed */
SCIP_Bool fixingmarker; /* which flag should label a fixed variable? */
int nvars;
int nbinvars;
int nintvars;
int i;
int j;
int nmarkers;
/* get required data of the original problem */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
sol = SCIPgetBestSol(scip);
assert(sol != NULL);
SCIP_CALL( SCIPallocBufferArray(scip, &marked, nbinvars+nintvars) );
if( minfixingrate > 0.5 )
{
nmarkers = nbinvars + nintvars - (int) SCIPfloor(scip, minfixingrate*(nbinvars+nintvars));
fixingmarker = FALSE;
}
else
{
nmarkers = (int) SCIPceil(scip, minfixingrate*(nbinvars+nintvars));
fixingmarker = TRUE;
}
assert( 0 <= nmarkers && nmarkers <= SCIPceil(scip,(nbinvars+nintvars)/2.0 ) );
j = 0;
BMSclearMemoryArray(marked, nbinvars+nintvars);
while( j < nmarkers )
{
do
{
i = SCIPgetRandomInt(0, nbinvars+nintvars-1, randseed);
}
while( marked[i] );
marked[i] = TRUE;
j++;
}
assert( j == nmarkers );
/* change bounds of variables of the subproblem */
for( i = 0; i < nbinvars + nintvars; i++ )
{
/* fix all randomly marked variables */
if( marked[i] == fixingmarker )
{
SCIP_Real solval;
SCIP_Real lb;
SCIP_Real ub;
solval = SCIPgetSolVal(scip, sol, vars[i]);
lb = SCIPvarGetLbGlobal(subvars[i]);
ub = SCIPvarGetUbGlobal(subvars[i]);
assert(SCIPisLE(scip, lb, ub));
/* due to dual reductions, it may happen that the solution value is not in
the variable's domain anymore */
if( SCIPisLT(scip, solval, lb) )
solval = lb;
else if( SCIPisGT(scip, solval, ub) )
solval = ub;
/* perform the bound change */
if( !SCIPisInfinity(scip, solval) && !SCIPisInfinity(scip, -solval) )
{
SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], solval) );
SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], solval) );
}
}
}
if( uselprows )
{
SCIP_ROW** rows; /* original scip rows */
int nrows;
/* get the rows and their number */
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
/* copy all rows to linear constraints */
for( i = 0; i < nrows; i++ )
{
SCIP_CONS* cons;
SCIP_VAR** consvars;
SCIP_COL** cols;
SCIP_Real constant;
SCIP_Real lhs;
SCIP_Real rhs;
SCIP_Real* vals;
int nnonz;
/* ignore rows that are only locally valid */
if( SCIProwIsLocal(rows[i]) )
continue;
/* get the row's data */
constant = SCIProwGetConstant(rows[i]);
lhs = SCIProwGetLhs(rows[i]) - constant;
rhs = SCIProwGetRhs(rows[i]) - constant;
vals = SCIProwGetVals(rows[i]);
nnonz = SCIProwGetNNonz(rows[i]);
cols = SCIProwGetCols(rows[i]);
assert( lhs <= rhs );
/* allocate memory array to be filled with the corresponding subproblem variables */
SCIP_CALL( SCIPallocBufferArray(scip, &consvars, nnonz) );
for( j = 0; j < nnonz; j++ )
consvars[j] = subvars[SCIPvarGetProbindex(SCIPcolGetVar(cols[j]))];
/* create a new linear constraint and add it to the subproblem */
SCIP_CALL( SCIPcreateConsLinear(subscip, &cons, SCIProwGetName(rows[i]), nnonz, consvars, vals, lhs, rhs,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
/* free temporary memory */
SCIPfreeBufferArray(scip, &consvars);
}
}
SCIPfreeBufferArray(scip, &marked);
return SCIP_OKAY;
}
/** main procedure of the zeroobj heuristic, creates and solves a sub-SCIP */
SCIP_RETCODE SCIPapplyZeroobj(
SCIP* scip, /**< original SCIP data structure */
SCIP_HEUR* heur, /**< heuristic data structure */
SCIP_RESULT* result, /**< result data structure */
SCIP_Real minimprove, /**< factor by which zeroobj should at least improve the incumbent */
SCIP_Longint nnodes /**< node limit for the subproblem */
)
{
SCIP* subscip; /* the subproblem created by zeroobj */
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_VAR** vars; /* original problem's variables */
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_HEURDATA* heurdata; /* heuristic's private data structure */
SCIP_EVENTHDLR* eventhdlr; /* event handler for LP events */
SCIP_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real timelimit; /* time limit for zeroobj subproblem */
SCIP_Real memorylimit; /* memory limit for zeroobj subproblem */
SCIP_Real large;
int nvars; /* number of original problem's variables */
int i;
SCIP_Bool success;
SCIP_Bool valid;
SCIP_RETCODE retcode;
SCIP_SOL** subsols;
int nsubsols;
assert(scip != NULL);
assert(heur != NULL);
assert(result != NULL);
assert(nnodes >= 0);
assert(0.0 <= minimprove && minimprove <= 1.0);
*result = SCIP_DIDNOTRUN;
/* only call heuristic once at the root */
if( SCIPgetDepth(scip) <= 0 && SCIPheurGetNCalls(heur) > 0 )
return SCIP_OKAY;
/* get heuristic data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* only call the heuristic if we do not have an incumbent */
if( SCIPgetNSolsFound(scip) > 0 && heurdata->onlywithoutsol )
return SCIP_OKAY;
/* check whether there is enough time and memory left */
timelimit = 0.0;
memorylimit = 0.0;
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 )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
/* get variable data */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* initialize the subproblem */
SCIP_CALL( SCIPcreate(&subscip) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
/* different methods to create sub-problem: either copy LP relaxation or the CIP with all constraints */
valid = FALSE;
/* copy complete SCIP instance */
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "zeroobj", TRUE, FALSE, TRUE, &valid) );
SCIPdebugMessage("Copying the SCIP instance was %s complete.\n", valid ? "" : "not ");
/* create event handler for LP events */
eventhdlr = NULL;
SCIP_CALL( SCIPincludeEventhdlrBasic(subscip, &eventhdlr, EVENTHDLR_NAME, EVENTHDLR_DESC, eventExecZeroobj, NULL) );
if( eventhdlr == NULL )
{
SCIPerrorMessage("event handler for "HEUR_NAME" heuristic not found.\n");
return SCIP_PLUGINNOTFOUND;
}
/* determine large value to set variables to */
large = SCIPinfinity(scip);
if( !SCIPisInfinity(scip, 0.1 / SCIPfeastol(scip)) )
large = 0.1 / SCIPfeastol(scip);
/* get variable image and change to 0.0 in sub-SCIP */
for( i = 0; i < nvars; i++ )
{
SCIP_Real adjustedbound;
SCIP_Real lb;
SCIP_Real ub;
SCIP_Real inf;
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
SCIP_CALL( SCIPchgVarObj(subscip, subvars[i], 0.0) );
lb = SCIPvarGetLbGlobal(subvars[i]);
ub = SCIPvarGetUbGlobal(subvars[i]);
inf = SCIPinfinity(subscip);
/* adjust infinite bounds in order to avoid that variables with non-zero objective
* get fixed to infinite value in zeroobj subproblem
*/
if( SCIPisInfinity(subscip, ub ) )
{
adjustedbound = MAX(large, lb+large);
adjustedbound = MIN(adjustedbound, inf);
SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], adjustedbound) );
}
if( SCIPisInfinity(subscip, -lb ) )
{
adjustedbound = MIN(-large, ub-large);
adjustedbound = MAX(adjustedbound, -inf);
SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], adjustedbound) );
}
}
/* free hash map */
SCIPhashmapFree(&varmapfw);
/* 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 limits for the subproblem */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nnodes) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
SCIP_CALL( SCIPsetIntParam(subscip, "limits/solutions", 1) );
/* forbid recursive call of heuristics and separators solving sub-SCIPs */
SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
/* disable expensive techniques that merely work on the dual bound */
/* disable cutting plane separation */
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
/* disable expensive presolving */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );
if( !SCIPisParamFixed(subscip, "presolving/maxrounds") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "presolving/maxrounds", 50) );
}
/* use best dfs node selection */
if( SCIPfindNodesel(subscip, "dfs") != NULL && !SCIPisParamFixed(subscip, "nodeselection/dfs/stdpriority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/dfs/stdpriority", INT_MAX/4) );
}
/* use inference branching */
if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "branching/leastinf/priority", INT_MAX/4) );
}
/* 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", 10) );
}
/* disable feaspump and fracdiving */
if( !SCIPisParamFixed(subscip, "heuristics/feaspump/freq") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "heuristics/feaspump/freq", -1) );
}
if( !SCIPisParamFixed(subscip, "heuristics/fracdiving/freq") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "heuristics/fracdiving/freq", -1) );
}
/* restrict LP iterations */
SCIP_CALL( SCIPsetLongintParam(subscip, "lp/iterlim", 2*heurdata->maxlpiters / MAX(1,nnodes)) );
SCIP_CALL( SCIPsetLongintParam(subscip, "lp/rootiterlim", heurdata->maxlpiters) );
#ifdef SCIP_DEBUG
/* for debugging zeroobj, enable MIP output */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 5) );
SCIP_CALL( SCIPsetIntParam(subscip, "display/freq", 100000000) );
#endif
/* if there is already a solution, add an objective cutoff */
if( SCIPgetNSols(scip) > 0 )
{
SCIP_Real upperbound;
SCIP_CONS* origobjcons;
#ifndef NDEBUG
int nobjvars;
nobjvars = 0;
#endif
cutoff = SCIPinfinity(scip);
assert( !SCIPisInfinity(scip,SCIPgetUpperbound(scip)) );
upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
{
cutoff = (1-minimprove)*SCIPgetUpperbound(scip) + minimprove*SCIPgetLowerbound(scip);
}
else
{
if( SCIPgetUpperbound(scip) >= 0 )
cutoff = ( 1 - minimprove ) * SCIPgetUpperbound ( scip );
else
cutoff = ( 1 + minimprove ) * SCIPgetUpperbound ( scip );
}
cutoff = MIN(upperbound, cutoff);
SCIP_CALL( SCIPcreateConsLinear(subscip, &origobjcons, "objbound_of_origscip", 0, NULL, NULL, -SCIPinfinity(subscip), cutoff,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE) );
for( i = 0; i < nvars; ++i)
{
if( !SCIPisFeasZero(subscip, SCIPvarGetObj(vars[i])) )
{
SCIP_CALL( SCIPaddCoefLinear(subscip, origobjcons, subvars[i], SCIPvarGetObj(vars[i])) );
#ifndef NDEBUG
nobjvars++;
#endif
}
}
SCIP_CALL( SCIPaddCons(subscip, origobjcons) );
SCIP_CALL( SCIPreleaseCons(subscip, &origobjcons) );
assert(nobjvars == SCIPgetNObjVars(scip));
}
/* catch LP events of sub-SCIP */
SCIP_CALL( SCIPtransformProb(subscip) );
SCIP_CALL( SCIPcatchEvent(subscip, SCIP_EVENTTYPE_NODESOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, NULL) );
SCIPdebugMessage("solving subproblem: nnodes=%"SCIP_LONGINT_FORMAT"\n", nnodes);
retcode = SCIPsolve(subscip);
/* drop LP events of sub-SCIP */
SCIP_CALL( SCIPdropEvent(subscip, SCIP_EVENTTYPE_NODESOLVED, 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 zeroobj heuristic; sub-SCIP terminated with code <%d>\n",retcode);
}
/* 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 || heurdata->addallsols); ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
if( success )
*result = SCIP_FOUNDSOL;
}
#ifdef SCIP_DEBUG
SCIP_CALL( SCIPprintStatistics(subscip, NULL) );
#endif
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/** creates a subproblem for subscip by fixing a number of variables */
static
SCIP_RETCODE createSubproblem(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP data structure for the subproblem */
SCIP_VAR** subvars, /**< the variables of the subproblem */
SCIP_Real minfixingrate, /**< percentage of integer variables that have to be fixed */
SCIP_Bool binarybounds, /**< should general integers get binary bounds [floor(.),ceil(.)] ? */
SCIP_Bool uselprows, /**< should subproblem be created out of the rows in the LP rows? */
SCIP_Bool* success /**< pointer to store whether the problem was created successfully */
)
{
SCIP_VAR** vars; /* original SCIP variables */
SCIP_Real fixingrate;
int nvars;
int nbinvars;
int nintvars;
int i;
int fixingcounter;
assert(scip != NULL);
assert(subscip != NULL);
assert(subvars != NULL);
assert(0.0 <= minfixingrate && minfixingrate <= 1.0);
/* get required variable data */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
fixingcounter = 0;
/* change bounds of variables of the subproblem */
for( i = 0; i < nbinvars + nintvars; i++ )
{
SCIP_Real lpsolval;
SCIP_Real lb;
SCIP_Real ub;
/* get the current LP solution for each variable */
lpsolval = SCIPgetRelaxSolVal(scip, vars[i]);
if( SCIPisFeasIntegral(scip, lpsolval) )
{
/* fix variables to current LP solution if it is integral,
* use exact integral value, if the variable is only integral within numerical tolerances
*/
lb = SCIPfloor(scip, lpsolval+0.5);
ub = lb;
fixingcounter++;
}
else if( binarybounds )
{
/* if the sub problem should be a binary problem, change the bounds to nearest integers */
lb = SCIPfeasFloor(scip,lpsolval);
ub = SCIPfeasCeil(scip,lpsolval);
}
else
{
/* otherwise just copy bounds */
lb = SCIPvarGetLbGlobal(vars[i]);
ub = SCIPvarGetUbGlobal(vars[i]);
}
/* perform the bound change */
SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], lb) );
SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], ub) );
}
/* abort, if all integer variables were fixed (which should not happen for MIP) */
if( fixingcounter == nbinvars + nintvars )
{
*success = FALSE;
return SCIP_OKAY;
}
else
fixingrate = fixingcounter / (SCIP_Real)(MAX(nbinvars + nintvars, 1));
SCIPdebugMessage("fixing rate: %g = %d of %d\n", fixingrate, fixingcounter, nbinvars + nintvars);
/* abort, if the amount of fixed variables is insufficient */
if( fixingrate < minfixingrate )
{
*success = FALSE;
return SCIP_OKAY;
}
if( uselprows )
{
SCIP_ROW** rows; /* original scip rows */
int nrows;
/* get the rows and their number */
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
/* copy all rows to linear constraints */
for( i = 0; i < nrows; i++ )
{
SCIP_CONS* cons;
SCIP_VAR** consvars;
SCIP_COL** cols;
SCIP_Real constant;
SCIP_Real lhs;
SCIP_Real rhs;
SCIP_Real* vals;
int nnonz;
int j;
/* ignore rows that are only locally valid */
if( SCIProwIsLocal(rows[i]) )
continue;
/* get the row's data */
constant = SCIProwGetConstant(rows[i]);
lhs = SCIProwGetLhs(rows[i]) - constant;
rhs = SCIProwGetRhs(rows[i]) - constant;
vals = SCIProwGetVals(rows[i]);
nnonz = SCIProwGetNNonz(rows[i]);
cols = SCIProwGetCols(rows[i]);
assert( lhs <= rhs );
/* allocate memory array to be filled with the corresponding subproblem variables */
SCIP_CALL( SCIPallocBufferArray(subscip, &consvars, nnonz) );
for( j = 0; j < nnonz; j++ )
consvars[j] = subvars[SCIPvarGetProbindex(SCIPcolGetVar(cols[j]))];
/* create a new linear constraint and add it to the subproblem */
SCIP_CALL( SCIPcreateConsLinear(subscip, &cons, SCIProwGetName(rows[i]), nnonz, consvars, vals, lhs, rhs,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
/* free temporary memory */
SCIPfreeBufferArray(subscip, &consvars);
}
}
*success = TRUE;
return SCIP_OKAY;
}
/** creates the all variables of the subproblem */
static SCIP_RETCODE fixVariables(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP data structure for the subproblemd */
SCIP_VAR** subvars, /**< the variables of the subproblem */
int* selection, /**< pool of solutions crossover will use */
SCIP_HEURDATA* heurdata, /**< primal heuristic data */
SCIP_Bool* success /**< pointer to store whether the problem was created successfully */
)
{
SCIP_VAR** vars; /* original scip variables */
SCIP_SOL** sols; /* pool of solutions */
SCIP_Real fixingrate; /* percentage of variables that are fixed */
int nvars;
int nbinvars;
int nintvars;
int i;
int j;
int fixingcounter;
sols = SCIPgetSols(scip);
assert(sols != NULL);
/* get required data of the original problem */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
fixingcounter = 0;
/* create the binary and general integer variables of the subproblem */
for( i = 0; i < nbinvars + nintvars; i++ )
{
SCIP_Real solval;
SCIP_Bool fixable;
fixable = TRUE;
solval = SCIPgetSolVal(scip, sols[selection[0]], vars[i]);
/* check, whether variable's value is identical for each selected solution */
for( j = 1; j < heurdata->nusedsols; j++ )
{
SCIP_Real varsolval;
varsolval = SCIPgetSolVal(scip, sols[selection[j]], vars[i]);
if( REALABS(solval - varsolval) > 0.5 )
{
fixable = FALSE;
break;
}
}
/* original solval can be outside transformed global bounds */
fixable = fixable && SCIPvarGetLbGlobal(vars[i]) <= solval && solval <= SCIPvarGetUbGlobal(vars[i]);
/* if solutions' values are equal, variable is fixed in the subproblem */
if( fixable )
{
SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], solval) );
SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], solval) );
fixingcounter++;
}
}
fixingrate = (SCIP_Real)fixingcounter / (SCIP_Real)(MAX(nbinvars + nintvars, 1));
/* if all variables were fixed or amount of fixed variables is insufficient, skip residual part of
* subproblem creation and abort immediately */
*success = fixingcounter < nbinvars + nintvars && fixingrate >= heurdata->minfixingrate;
return SCIP_OKAY;
}
