/** problem writing method of reader */
static
SCIP_DECL_READERWRITE(readerWriteCip)
{ /*lint --e{715}*/
SCIP_HASHTABLE* varhash = NULL;
SCIP_READERDATA* readerdata;
int i;
assert(reader != NULL);
assert(strcmp(SCIPreaderGetName(reader), READER_NAME) == 0);
SCIPinfoMessage(scip, file, "STATISTICS\n");
SCIPinfoMessage(scip, file, " Problem name : %s\n", name);
SCIPinfoMessage(scip, file, " Variables : %d (%d binary, %d integer, %d implicit integer, %d continuous)\n",
nvars, nbinvars, nintvars, nimplvars, ncontvars);
SCIPinfoMessage(scip, file, " Constraints : %d initial, %d maximal\n", startnconss, maxnconss);
SCIPinfoMessage(scip, file, "OBJECTIVE\n");
SCIPinfoMessage(scip, file, " Sense : %s\n", objsense == SCIP_OBJSENSE_MINIMIZE ? "minimize" : "maximize");
if( !SCIPisZero(scip, objoffset) )
SCIPinfoMessage(scip, file, " Offset : %+.15g\n", objoffset);
if( !SCIPisEQ(scip, objscale, 1.0) )
SCIPinfoMessage(scip, file, " Scale : %.15g\n", objscale);
if ( nfixedvars > 0 )
{
/* set up hash table for variables that have been written property (used for writing out fixed vars in the right order) */
SCIP_CALL( SCIPhashtableCreate(&varhash, SCIPblkmem(scip), SCIPcalcHashtableSize(10 * (nvars + nfixedvars)), hashGetKeyVar, hashKeyEqVar, hashKeyValVar, NULL) );
}
if ( nvars + nfixedvars > 0 )
{
SCIPinfoMessage(scip, file, "VARIABLES\n");
}
if( nvars > 0 )
{
for( i = 0; i < nvars; ++i )
{
SCIP_VAR* var;
var = vars[i];
assert( var != NULL );
SCIP_CALL( SCIPprintVar(scip, var, file) );
if ( varhash != NULL )
{
/* add free variable to hashtable */
if ( ! SCIPhashtableExists(varhash, (void*) var) )
{
SCIP_CALL( SCIPhashtableInsert(varhash, (void*) var) );
}
}
}
}
readerdata = SCIPreaderGetData(reader);
assert(readerdata != NULL);
if( readerdata->writefixedvars && nfixedvars > 0 )
{
int nwritten = 0;
SCIPinfoMessage(scip, file, "FIXED\n");
/* loop through variables until each has been written after the variables that it depends on have been written; this
* requires several runs over the variables, but the depth (= number of loops) is usually small. */
while ( nwritten < nfixedvars )
{
SCIPdebugMessage("written %d of %d fixed variables.\n", nwritten, nfixedvars);
for (i = 0; i < nfixedvars; ++i)
{
SCIP_VAR* var;
SCIP_VAR* tmpvar;
var = fixedvars[i];
assert( var != NULL );
/* skip variables already written */
if ( SCIPhashtableExists(varhash, (void*) var) )
continue;
switch ( SCIPvarGetStatus(var) )
{
case SCIP_VARSTATUS_FIXED:
/* fixed variables can simply be output and added to the hashtable */
SCIP_CALL( SCIPprintVar(scip, var, file) );
assert( ! SCIPhashtableExists(varhash, (void*) var) );
SCIP_CALL( SCIPhashtableInsert(varhash, (void*) var) );
++nwritten;
break;
case SCIP_VARSTATUS_NEGATED:
tmpvar = SCIPvarGetNegationVar(var);
assert( tmpvar != NULL );
assert( var == SCIPvarGetNegatedVar(tmpvar) );
/* if the negated variable has been written, we can write the current variable */
if ( SCIPhashtableExists(varhash, (void*) tmpvar) )
{
SCIP_CALL( SCIPprintVar(scip, var, file) );
assert( ! SCIPhashtableExists(varhash, (void*) var) );
SCIP_CALL( SCIPhashtableInsert(varhash, (void*) var) );
++nwritten;
}
break;
case SCIP_VARSTATUS_AGGREGATED:
tmpvar = SCIPvarGetAggrVar(var);
assert( tmpvar != NULL );
/* if the aggregating variable has been written, we can write the current variable */
if ( SCIPhashtableExists(varhash, (void*) tmpvar) )
{
SCIP_CALL( SCIPprintVar(scip, var, file) );
assert( ! SCIPhashtableExists(varhash, (void*) var) );
SCIP_CALL( SCIPhashtableInsert(varhash, (void*) var) );
++nwritten;
}
break;
case SCIP_VARSTATUS_MULTAGGR:
{
SCIP_VAR** aggrvars;
int naggrvars;
int j;
/* get the active representation */
SCIP_CALL( SCIPflattenVarAggregationGraph(scip, var) );
naggrvars = SCIPvarGetMultaggrNVars(var);
aggrvars = SCIPvarGetMultaggrVars(var);
assert(aggrvars != NULL || naggrvars == 0);
for (j = 0; j < naggrvars; ++j)
{
if( !SCIPhashtableExists(varhash, (void*) aggrvars[j]) ) /*lint !e613*/
break;
}
/* if all multi-aggregating variables have been written, we can write the current variable */
if ( j >= naggrvars )
{
SCIP_CALL( SCIPprintVar(scip, var, file) );
assert( ! SCIPhashtableExists(varhash, (void*) var) );
SCIP_CALL( SCIPhashtableInsert(varhash, (void*) var) );
++nwritten;
}
break;
}
case SCIP_VARSTATUS_ORIGINAL:
case SCIP_VARSTATUS_LOOSE:
case SCIP_VARSTATUS_COLUMN:
SCIPerrorMessage("Only fixed variables are allowed to be present in fixedvars list.\n");
SCIPABORT();
return SCIP_ERROR; /*lint !e527*/
}
}
}
}
if( nconss > 0 )
{
SCIPinfoMessage(scip, file, "CONSTRAINTS\n");
for( i = 0; i < nconss; ++i )
{
SCIP_CALL( SCIPprintCons(scip, conss[i], file) );
SCIPinfoMessage(scip, file, ";\n");
}
}
SCIPinfoMessage(scip, file, "END\n");
*result = SCIP_SUCCESS;
if( nfixedvars > 0 )
SCIPhashtableFree(&varhash);
else
assert(varhash == NULL);
return SCIP_OKAY;
}
/** creates a subproblem for subscip by fixing a number of variables */
static
SCIP_RETCODE setupSubproblem(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP data structure for the subproblem */
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_SOL** sols; /* array of all solutions found so far */
int nsols; /* number of all solutions found so far */
int nusedsols; /* number of solutions to use in crossover */
int i;
char consname[SCIP_MAXSTRLEN];
/* get solutions' data */
nsols = SCIPgetNSols(scip);
sols = SCIPgetSols(scip);
nusedsols = heurdata->nusedsols;
assert(nusedsols > 1);
assert(nsols >= nusedsols);
/* use nusedsols best solutions if randomization is deactivated or there are only nusedsols solutions at hand
* or a good new solution was found since last call */
if( !heurdata->randomization || nsols == nusedsols || heurdata->prevlastsol != sols[nusedsols-1] )
{
SOLTUPLE* elem;
SCIP_HEUR* solheur;
SCIP_Longint solnodenum;
SCIP_Bool allsame;
for( i = 0; i < nusedsols; i++ )
selection[i] = i;
SCIP_CALL( createSolTuple(scip, &elem, selection, nusedsols, heurdata) );
solheur = SCIPsolGetHeur(sols[0]);
solnodenum = SCIPsolGetNodenum(sols[0]);
allsame = TRUE;
/* check, whether all solutions have been found by the same heuristic at the same node; in this case we do not run
* crossover, since it would probably just optimize over the same space as the other heuristic
*/
for( i = 1; i < nusedsols; i++ )
{
if( SCIPsolGetHeur(sols[i]) != solheur || SCIPsolGetNodenum(sols[i]) != solnodenum )
allsame = FALSE;
}
*success = !allsame && !SCIPhashtableExists(heurdata->hashtable, elem);
/* check, whether solution tuple has already been tried */
if( !SCIPhashtableExists(heurdata->hashtable, elem) )
{
SCIP_CALL( SCIPhashtableInsert(heurdata->hashtable, elem) );
}
/* if solution tuple has already been tried, randomization is allowed and enough solutions are at hand, try
* to randomize another tuple. E.g., this can happen if the last crossover solution was among the best ones */
if( !(*success) && heurdata->randomization && nsols > nusedsols )
{
SCIP_CALL( selectSolsRandomized(scip, selection, heurdata, success) );
}
}
/* otherwise randomize the set of solutions */
else
{
SCIP_CALL( selectSolsRandomized(scip, selection, heurdata, success) );
}
/* no acceptable solution tuple could be created */
if( !(*success) )
return SCIP_OKAY;
/* get name of the original problem and add the string "_crossoversub" */
(void) SCIPsnprintf(consname, SCIP_MAXSTRLEN, "%s_crossoversub", SCIPgetProbName(scip));
/* set up the variables of the subproblem */
SCIP_CALL( fixVariables(scip, subscip, subvars, selection, heurdata, success) );
/* we copy the rows of the LP, if the enough variables could be fixed and we work on the MIP
relaxation of the problem */
if( *success && heurdata->uselprows )
{
SCIP_CALL( createRows(scip, subscip, subvars) );
}
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecCrossover)
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata; /* primal heuristic data */
SCIP* subscip; /* the subproblem created by crossover */
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_SOL** sols;
SCIP_Real memorylimit; /* memory limit for the subproblem */
SCIP_Real timelimit; /* time limit for the subproblem */
SCIP_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real upperbound;
SCIP_Bool success;
SCIP_Longint nstallnodes; /* node limit for the subproblem */
int* selection; /* pool of solutions crossover uses */
int nvars; /* number of original problem's variables */
int nbinvars;
int nintvars;
int nusedsols;
int i;
SCIP_RETCODE retcode;
assert(heur != NULL);
assert(scip != NULL);
assert(result != NULL);
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
nusedsols = heurdata->nusedsols;
*result = SCIP_DELAYED;
/* only call heuristic, if enough solutions are at hand */
if( SCIPgetNSols(scip) < nusedsols )
return SCIP_OKAY;
sols = SCIPgetSols(scip);
assert(sols != NULL);
/* if one good solution was found, heuristic should not be delayed any longer */
if( sols[nusedsols-1] != heurdata->prevlastsol )
{
heurdata->nextnodenumber = SCIPgetNNodes(scip);
if( sols[0] != heurdata->prevbestsol )
heurdata->nfailures = 0;
}
/* in nonrandomized mode: only recall heuristic, if at least one new good solution was found in the meantime */
else if( !heurdata->randomization )
return SCIP_OKAY;
/* if heuristic should be delayed, wait until certain number of nodes is reached */
if( SCIPgetNNodes(scip) < heurdata->nextnodenumber )
return SCIP_OKAY;
/* only call heuristic, if enough nodes were processed since last incumbent */
if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip,SCIPgetBestSol(scip)) < heurdata->nwaitingnodes
&& (SCIPgetDepth(scip) > 0 || !heurdata->dontwaitatroot) )
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* calculate the maximal number of branching nodes until heuristic is aborted */
nstallnodes = (SCIP_Longint)(heurdata->nodesquot * SCIPgetNNodes(scip));
/* reward Crossover if it succeeded often */
nstallnodes = (SCIP_Longint)
(nstallnodes * (1.0 + 2.0*(SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur)+1.0)));
/* count the setup costs for the sub-MIP as 100 nodes */
nstallnodes -= 100 * SCIPheurGetNCalls(heur);
nstallnodes += heurdata->nodesofs;
/* determine the node limit for the current process */
nstallnodes -= heurdata->usednodes;
nstallnodes = MIN(nstallnodes, heurdata->maxnodes);
/* check whether we have enough nodes left to call subproblem solving */
if( nstallnodes < heurdata->minnodes )
return SCIP_OKAY;
if( SCIPisStopped(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
assert(nvars > 0);
/* check whether discrete variables are available */
if( nbinvars == 0 && nintvars == 0 )
return SCIP_OKAY;
/* initializing the subproblem */
SCIP_CALL( SCIPcreate(&subscip) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
success = FALSE;
if( heurdata->uselprows )
{
char probname[SCIP_MAXSTRLEN];
/* copy all plugins */
SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );
/* get name of the original problem and add the string "_crossoversub" */
(void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_crossoversub", 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, "crossover", 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) );
}
}
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &selection, nusedsols) );
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) (size_t) SCIPhashmapGetImage(varmapfw, vars[i]);
/* free hash map */
SCIPhashmapFree(&varmapfw);
success = FALSE;
/* create a new problem, which fixes variables with same value in a certain set of solutions */
SCIP_CALL( setupSubproblem(scip, subscip, subvars, selection, heurdata, &success) );
heurdata->prevbestsol = SCIPgetBestSol(scip);
heurdata->prevlastsol = sols[heurdata->nusedsols-1];
/* if creation of sub-SCIP was aborted (e.g. due to number of fixings), free sub-SCIP and abort */
if( !success )
{
*result = SCIP_DIDNOTRUN;
/* this run will be counted as a failure since no new solution tuple could be generated or the neighborhood of the
* solution was not fruitful in the sense that it was too big
*/
updateFailureStatistic(scip, heurdata);
goto TERMINATE;
}
/* 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) );
/* 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 */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nstallnodes) );
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) );
}
/* 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) );
/* permute the subproblem to increase diversification */
if( heurdata->permute )
{
SCIP_CALL( SCIPpermuteProb(subscip, (unsigned int) SCIPheurGetNCalls(heur), TRUE, TRUE, TRUE, TRUE, TRUE) );
}
/* solve the subproblem */
SCIPdebugMessage("Solve Crossover subMIP\n");
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(scip, "Error while solving subproblem in Crossover heuristic; sub-SCIP terminated with code <%d>\n", retcode);
}
heurdata->usednodes += SCIPgetNNodes(subscip);
/* check, whether a solution was found */
if( SCIPgetNSols(subscip) > 0 )
{
SCIP_SOL** subsols;
int nsubsols;
int solindex; /* index of the solution created by crossover */
/* 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;
solindex = -1;
for( i = 0; i < nsubsols && !success; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &solindex, &success) );
}
if( success )
{
int tmp;
assert(solindex != -1);
*result = SCIP_FOUNDSOL;
/* insert all crossings of the new solution and (nusedsols-1) of its parents into the hashtable
* in order to avoid incest ;)
*/
for( i = 0; i < nusedsols; i++ )
{
SOLTUPLE* elem;
tmp = selection[i];
selection[i] = solindex;
SCIP_CALL( createSolTuple(scip, &elem, selection, nusedsols, heurdata) );
SCIP_CALL( SCIPhashtableInsert(heurdata->hashtable, elem) );
selection[i] = tmp;
}
/* if solution was among the best ones, crossover should not be called until another good solution was found */
if( !heurdata->randomization )
{
heurdata->prevbestsol = SCIPgetBestSol(scip);
heurdata->prevlastsol = SCIPgetSols(scip)[heurdata->nusedsols-1];
}
}
/* if solution is not better then incumbent or could not be added to problem => run is counted as a failure */
if( !success || solindex != SCIPsolGetIndex(SCIPgetBestSol(scip)) )
updateFailureStatistic(scip, heurdata);
}
else
{
/* if no new solution was found, run was a failure */
updateFailureStatistic(scip, heurdata);
}
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &selection);
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/** randomly selects the solutions crossover will use from the pool of all solutions found so far */
static
SCIP_RETCODE selectSolsRandomized(
SCIP* scip, /**< original SCIP data structure */
int* selection, /**< pool of solutions crossover uses */
SCIP_HEURDATA* heurdata, /**< primal heuristic data */
SCIP_Bool* success /**< pointer to store whether the process was successful */
)
{
int i;
int j;
int lastsol; /* the worst solution possible to choose */
int nusedsols; /* number of solutions which will be chosen */
SOLTUPLE* elem;
SCIP_SOL** sols;
/* initialization */
nusedsols = heurdata->nusedsols;
lastsol = SCIPgetNSols(scip);
sols = SCIPgetSols(scip);
assert(nusedsols < lastsol);
i = 0;
*success = FALSE;
/* perform at maximum 10 restarts and stop as soon as a new set of solutions is found */
while( !*success && i < 10 )
{
SCIP_Bool validtuple;
validtuple = TRUE;
for( j = 0; j < nusedsols && validtuple; j++ )
{
int k;
k = SCIPgetRandomInt(nusedsols-j-1, lastsol-1, &heurdata->randseed);
/* ensure that the solution does not have a similar source as the others */
while( k >= nusedsols-j-1 && !solHasNewSource(sols, selection, j, k) )
k--;
validtuple = (k >= nusedsols-j-1);
selection[j] = k;
lastsol = k;
}
if( validtuple )
{
/* creates an object ready to be inserted into the hashtable */
SCIP_CALL( createSolTuple(scip, &elem, selection, nusedsols, heurdata) );
/* check whether the randomized set is already in the hashtable, if not, insert it */
if( !SCIPhashtableExists(heurdata->hashtable, elem) )
{
SCIP_CALL( SCIPhashtableInsert(heurdata->hashtable, elem) );
*success = TRUE;
}
}
i++;
}
return SCIP_OKAY;
}
