/** creates a new solution for the original problem by copying the solution of the subproblem */
static
SCIP_RETCODE createNewSol(
SCIP* scip, /**< original SCIP data structure */
SCIP_HEUR* heur, /**< the current heuristic */
SCIP_SOL* sol, /**< solution of the subproblem */
SCIP_Bool* success /**< used to store whether new solution was found or not */
)
{
SCIP_VAR** vars; /* the original problem's variables */
int nvars; /* the original problem's number of variables */
SCIP_Real* solvals; /* solution values of the subproblem */
SCIP_SOL* newsol; /* solution to be created for the original problem */
assert(scip != NULL);
/* get variables' data */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPallocBufferArray(scip, &solvals, nvars) );
/* copy the solution */
SCIP_CALL( SCIPgetSolVals(scip, sol, nvars, vars, solvals) );
/* create new solution for the original problem */
SCIP_CALL( SCIPcreateSol(scip, &newsol, heur) );
SCIP_CALL( SCIPsetSolVals(scip, newsol, nvars, vars, solvals) );
/* try to add new solution to scip and free it immediately */
SCIP_CALL( SCIPtrySolFree(scip, &newsol, FALSE, TRUE, TRUE, TRUE, success) );
SCIPfreeBufferArray(scip, &solvals);
return SCIP_OKAY;
}
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpImpliedbounds)
{ /*lint --e{715}*/
SCIP_VAR** vars;
SCIP_VAR** fracvars;
SCIP_Real* solvals;
SCIP_Real* fracvals;
SCIP_Bool cutoff;
int nvars;
int nbinvars;
int nfracs;
int ncuts;
assert(sepa != NULL);
assert(scip != NULL);
*result = SCIP_DIDNOTRUN;
/* gets active problem variables */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, NULL, NULL, NULL) );
if( nbinvars == 0 )
return SCIP_OKAY;
/* get fractional problem variables */
/* todo try out also separating fractional implicit integer variables */
SCIP_CALL( SCIPgetLPBranchCands(scip, &fracvars, &fracvals, NULL, &nfracs, NULL, NULL) );
if( nfracs == 0 )
return SCIP_OKAY;
/* get solution values for all variables */
SCIP_CALL( SCIPallocBufferArray(scip, &solvals, nvars) );
SCIP_CALL( SCIPgetVarSols(scip, nvars, vars, solvals) );
/* call the cut separation */
SCIP_CALL( separateCuts(scip, sepa, NULL, solvals, fracvars, fracvals, nfracs, &cutoff, &ncuts) );
/* adjust result code */
if ( cutoff )
*result = SCIP_CUTOFF;
else if ( ncuts > 0 )
*result = SCIP_SEPARATED;
else
*result = SCIP_DIDNOTFIND;
/* free temporary memory */
SCIPfreeBufferArray(scip, &solvals);
return SCIP_OKAY;
}
/** creates a new solution for the original problem by copying the solution of the subproblem */
static
SCIP_RETCODE createNewSol(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP structure of the subproblem */
SCIP_VAR** subvars, /**< the variables of the subproblem */
SCIP_HEUR* heur, /**< crossover heuristic structure */
SCIP_SOL* subsol, /**< solution of the subproblem */
int* solindex, /**< index of the solution */
SCIP_Bool* success /**< used to store whether new solution was found or not */
)
{
SCIP_VAR** vars; /* the original problem's variables */
int nvars;
SCIP_SOL* newsol; /* solution to be created for the original problem */
SCIP_Real* subsolvals; /* solution values of the subproblem */
assert(scip != NULL);
assert(subscip != NULL);
assert(subvars != NULL);
assert(subsol != NULL);
/* get variables' data */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* sub-SCIP may have more variables than the number of active (transformed) variables in the main SCIP
* since constraint copying may have required the copy of variables that are fixed in the main SCIP
*/
assert(nvars <= SCIPgetNOrigVars(subscip));
SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );
/* copy the solution */
SCIP_CALL( SCIPgetSolVals(subscip, subsol, nvars, subvars, subsolvals) );
/* create new solution for the original problem */
SCIP_CALL( SCIPcreateSol(scip, &newsol, heur) );
SCIP_CALL( SCIPsetSolVals(scip, newsol, nvars, vars, subsolvals) );
*solindex = SCIPsolGetIndex(newsol);
/* try to add new solution to scip and free it immediately */
SCIP_CALL( SCIPtrySolFree(scip, &newsol, FALSE, TRUE, TRUE, TRUE, success) );
SCIPfreeBufferArray(scip, &subsolvals);
return SCIP_OKAY;
}
/** creates a new solution for the original problem by copying the solution of the subproblem */
static
SCIP_RETCODE createNewSol(
SCIP* scip, /**< SCIP data structure of the original problem */
SCIP* subscip, /**< SCIP data structure of the subproblem */
SCIP_VAR** subvars, /**< the variables of the subproblem */
SCIP_HEUR* heur, /**< the Localbranching heuristic */
SCIP_SOL* subsol, /**< solution of the subproblem */
SCIP_Bool* success /**< pointer to store, whether new solution was found */
)
{
SCIP_VAR** vars;
int nvars;
SCIP_SOL* newsol;
SCIP_Real* subsolvals;
assert( scip != NULL );
assert( subscip != NULL );
assert( subvars != NULL );
assert( subsol != NULL );
/* copy the solution */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* sub-SCIP may have more variables than the number of active (transformed) variables in the main SCIP
* since constraint copying may have required the copy of variables that are fixed in the main SCIP
*/
assert(nvars <= SCIPgetNOrigVars(subscip));
SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );
/* copy the solution */
SCIP_CALL( SCIPgetSolVals(subscip, subsol, nvars, subvars, subsolvals) );
/* create new solution for the original problem */
SCIP_CALL( SCIPcreateSol(scip, &newsol, heur) );
SCIP_CALL( SCIPsetSolVals(scip, newsol, nvars, vars, subsolvals) );
SCIP_CALL( SCIPtrySolFree(scip, &newsol, FALSE, TRUE, TRUE, TRUE, success) );
SCIPfreeBufferArray(scip, &subsolvals);
return SCIP_OKAY;
}
/** main procedure of the RENS heuristic, creates and solves a subMIP */
SCIP_RETCODE SCIPapplyGcgrens(
SCIP* scip, /**< original SCIP data structure */
SCIP_HEUR* heur, /**< heuristic data structure */
SCIP_RESULT* result, /**< result data structure */
SCIP_Real minfixingrate, /**< minimum percentage of integer variables that have to be fixed */
SCIP_Real minimprove, /**< factor by which RENS should at least improve the incumbent */
SCIP_Longint maxnodes, /**< maximum number of nodes for the subproblem */
SCIP_Longint nstallnodes, /**< number of stalling nodes for the subproblem */
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* subscip; /* the subproblem created by RENS */
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_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real timelimit;
SCIP_Real memorylimit;
int nvars;
int i;
SCIP_Bool success;
SCIP_RETCODE retcode;
assert(scip != NULL);
assert(heur != NULL);
assert(result != NULL);
assert(maxnodes >= 0);
assert(nstallnodes >= 0);
assert(0.0 <= minfixingrate && minfixingrate <= 1.0);
assert(0.0 <= minimprove && minimprove <= 1.0);
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) );
if( uselprows )
{
char probname[SCIP_MAXSTRLEN];
/* copy all plugins */
SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );
/* get name of the original problem and add the string "_gcgrenssub" */
(void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_gcgrenssub", 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_Bool valid;
SCIP_HEURDATA* heurdata;
valid = FALSE;
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "gcgrens", TRUE, FALSE, TRUE, &valid) ); /** @todo check for thread safeness */
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert( heurdata != NULL );
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) );
}
SCIPdebugMessage("Copying the SCIP instance was %s complete.\n", valid ? "" : "not ");
}
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
/* free hash map */
SCIPhashmapFree(&varmapfw);
/* create a new problem, which fixes variables with same value in bestsol and LP relaxation */
SCIP_CALL( createSubproblem(scip, subscip, subvars, minfixingrate, binarybounds, uselprows, &success) );
SCIPdebugMessage("RENS subproblem: %d vars, %d cons, success=%u\n", SCIPgetNVars(subscip), SCIPgetNConss(subscip), success);
/* 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 */
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) );
if( !SCIPisInfinity(scip, memorylimit) )
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
if( timelimit <= 0.0 || memorylimit <= 0.0 )
goto TERMINATE;
/* set limits for the subproblem */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/stallnodes", nstallnodes) );
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", maxnodes) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
/* forbid recursive call of heuristics and separators solving sub-SCIPs */
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(scip, "estimate") != NULL )
{
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
}
/* use inference branching */
if( SCIPfindBranchrule(scip, "inference") != NULL )
{
SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
}
/* disable conflict analysis */
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
#ifdef SCIP_DEBUG
/* for debugging RENS, enable MIP output */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 5) );
SCIP_CALL( SCIPsetIntParam(subscip, "display/freq", 100000000) );
#endif
/* if the subproblem could not be created, free memory and return */
if( !success )
{
*result = SCIP_DIDNOTRUN;
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/* if there is already a solution, add an objective cutoff */
if( SCIPgetNSols(scip) > 0 )
{
SCIP_Real upperbound;
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( SCIPsetObjlimit(subscip, cutoff) );
}
/* presolve the subproblem */
retcode = SCIPpresolve(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 presolving subproblem in GCG RENS heuristic; sub-SCIP terminated with code <%d>\n",retcode);
}
SCIPdebugMessage("GCG RENS presolved subproblem: %d vars, %d cons, success=%u\n", SCIPgetNVars(subscip), SCIPgetNConss(subscip), success);
/* after presolving, we should have at least reached a certain fixing rate over ALL variables (including continuous)
* to ensure that not only the MIP but also the LP relaxation is easy enough
*/
if( ( nvars - SCIPgetNVars(subscip) ) / (SCIP_Real)nvars >= minfixingrate / 2.0 )
{
SCIP_SOL** subsols;
int nsubsols;
/* solve the subproblem */
SCIPdebugMessage("solving subproblem: nstallnodes=%"SCIP_LONGINT_FORMAT", maxnodes=%"SCIP_LONGINT_FORMAT"\n", nstallnodes, maxnodes);
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 GCG RENS 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; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
}
if( success )
*result = SCIP_FOUNDSOL;
}
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpGomory)
{ /*lint --e{715}*/
SCIP_SEPADATA* sepadata;
SCIP_VAR** vars;
SCIP_COL** cols;
SCIP_ROW** rows;
SCIP_Real* binvrow;
SCIP_Real* cutcoefs;
SCIP_Real maxscale;
SCIP_Real minfrac;
SCIP_Real maxfrac;
SCIP_Longint maxdnom;
SCIP_Bool cutoff;
int* basisind;
int naddedcuts;
int nvars;
int ncols;
int nrows;
int ncalls;
int depth;
int maxdepth;
int maxsepacuts;
int c;
int i;
assert(sepa != NULL);
assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
sepadata = SCIPsepaGetData(sepa);
assert(sepadata != NULL);
depth = SCIPgetDepth(scip);
ncalls = SCIPsepaGetNCallsAtNode(sepa);
minfrac = sepadata->away;
maxfrac = 1.0 - sepadata->away;
/* only call separator, if we are not close to terminating */
if( SCIPisStopped(scip) )
return SCIP_OKAY;
/* only call the gomory cut separator a given number of times at each node */
if( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot)
|| (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) )
return SCIP_OKAY;
/* only call separator, if an optimal LP solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call separator, if the LP solution is basic */
if( !SCIPisLPSolBasic(scip) )
return SCIP_OKAY;
/* only call separator, if there are fractional variables */
if( SCIPgetNLPBranchCands(scip) == 0 )
return SCIP_OKAY;
/* get variables data */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* get LP data */
SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
if( ncols == 0 || nrows == 0 )
return SCIP_OKAY;
#if 0 /* if too many columns, separator is usually very slow: delay it until no other cuts have been found */
if( ncols >= 50*nrows )
return SCIP_OKAY;
if( ncols >= 5*nrows )
{
int ncutsfound;
ncutsfound = SCIPgetNCutsFound(scip);
if( ncutsfound > sepadata->lastncutsfound || !SCIPsepaWasLPDelayed(sepa) )
{
sepadata->lastncutsfound = ncutsfound;
*result = SCIP_DELAYED;
return SCIP_OKAY;
}
}
#endif
/* set the maximal denominator in rational representation of gomory cut and the maximal scale factor to
* scale resulting cut to integral values to avoid numerical instabilities
*/
/**@todo find better but still stable gomory cut settings: look at dcmulti, gesa3, khb0525, misc06, p2756 */
maxdepth = SCIPgetMaxDepth(scip);
if( depth == 0 )
{
maxdnom = 1000;
maxscale = 1000.0;
}
else if( depth <= maxdepth/4 )
{
maxdnom = 1000;
maxscale = 1000.0;
}
else if( depth <= maxdepth/2 )
{
maxdnom = 100;
maxscale = 100.0;
}
else
{
maxdnom = 10;
maxscale = 10.0;
}
/* allocate temporary memory */
SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) );
SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) );
/* get basis indices */
SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) );
/* get the maximal number of cuts allowed in a separation round */
if( depth == 0 )
maxsepacuts = sepadata->maxsepacutsroot;
else
maxsepacuts = sepadata->maxsepacuts;
SCIPdebugMessage("searching gomory cuts: %d cols, %d rows, maxdnom=%"SCIP_LONGINT_FORMAT", maxscale=%g, maxcuts=%d\n",
ncols, nrows, maxdnom, maxscale, maxsepacuts);
cutoff = FALSE;
naddedcuts = 0;
/* for all basic columns belonging to integer variables, try to generate a gomory cut */
for( i = 0; i < nrows && naddedcuts < maxsepacuts && !SCIPisStopped(scip) && !cutoff; ++i )
{
SCIP_Bool tryrow;
tryrow = FALSE;
c = basisind[i];
if( c >= 0 )
{
SCIP_VAR* var;
assert(c < ncols);
var = SCIPcolGetVar(cols[c]);
if( SCIPvarGetType(var) != SCIP_VARTYPE_CONTINUOUS )
{
SCIP_Real primsol;
primsol = SCIPcolGetPrimsol(cols[c]);
assert(SCIPgetVarSol(scip, var) == primsol); /*lint !e777*/
if( SCIPfeasFrac(scip, primsol) >= minfrac )
{
SCIPdebugMessage("trying gomory cut for col <%s> [%g]\n", SCIPvarGetName(var), primsol);
tryrow = TRUE;
}
}
}
else if( sepadata->separaterows )
{
SCIP_ROW* row;
assert(0 <= -c-1 && -c-1 < nrows);
row = rows[-c-1];
if( SCIProwIsIntegral(row) && !SCIProwIsModifiable(row) )
{
SCIP_Real primsol;
primsol = SCIPgetRowActivity(scip, row);
if( SCIPfeasFrac(scip, primsol) >= minfrac )
{
SCIPdebugMessage("trying gomory cut for row <%s> [%g]\n", SCIProwGetName(row), primsol);
tryrow = TRUE;
}
}
}
if( tryrow )
{
SCIP_Real cutrhs;
SCIP_Real cutact;
SCIP_Bool success;
SCIP_Bool cutislocal;
/* get the row of B^-1 for this basic integer variable with fractional solution value */
SCIP_CALL( SCIPgetLPBInvRow(scip, i, binvrow) );
cutact = 0.0;
cutrhs = SCIPinfinity(scip);
/* create a MIR cut out of the weighted LP rows using the B^-1 row as weights */
SCIP_CALL( SCIPcalcMIR(scip, NULL, BOUNDSWITCH, USEVBDS, ALLOWLOCAL, FIXINTEGRALRHS, NULL, NULL,
(int) MAXAGGRLEN(nvars), sepadata->maxweightrange, minfrac, maxfrac,
binvrow, 1.0, NULL, NULL, cutcoefs, &cutrhs, &cutact, &success, &cutislocal) );
assert(ALLOWLOCAL || !cutislocal);
/* @todo Currently we are using the SCIPcalcMIR() function to compute the coefficients of the Gomory
* cut. Alternatively, we could use the direct version (see thesis of Achterberg formula (8.4)) which
* leads to cut a of the form \sum a_i x_i \geq 1. Rumor has it that these cuts are better.
*/
SCIPdebugMessage(" -> success=%u: %g <= %g\n", success, cutact, cutrhs);
/* if successful, convert dense cut into sparse row, and add the row as a cut */
if( success && SCIPisFeasGT(scip, cutact, cutrhs) )
{
SCIP_ROW* cut;
char cutname[SCIP_MAXSTRLEN];
int v;
/* construct cut name */
if( c >= 0 )
(void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "gom%d_x%d", SCIPgetNLPs(scip), c);
else
(void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "gom%d_s%d", SCIPgetNLPs(scip), -c-1);
/* create empty cut */
SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &cut, sepa, cutname, -SCIPinfinity(scip), cutrhs,
cutislocal, FALSE, sepadata->dynamiccuts) );
/* cache the row extension and only flush them if the cut gets added */
SCIP_CALL( SCIPcacheRowExtensions(scip, cut) );
/* collect all non-zero coefficients */
for( v = 0; v < nvars; ++v )
{
if( !SCIPisZero(scip, cutcoefs[v]) )
{
SCIP_CALL( SCIPaddVarToRow(scip, cut, vars[v], cutcoefs[v]) );
}
}
if( SCIProwGetNNonz(cut) == 0 )
{
assert(SCIPisFeasNegative(scip, cutrhs));
SCIPdebugMessage(" -> gomory cut detected infeasibility with cut 0 <= %f\n", cutrhs);
cutoff = TRUE;
}
else if( SCIProwGetNNonz(cut) == 1 )
{
/* add the bound change as cut to avoid that the LP gets modified. that would mean the LP is not flushed
* and the method SCIPgetLPBInvRow() fails; SCIP internally will apply that bound change automatically
*/
SCIP_CALL( SCIPaddCut(scip, NULL, cut, TRUE) );
naddedcuts++;
}
else
{
/* Only take efficacious cuts, except for cuts with one non-zero coefficients (= bound
* changes); the latter cuts will be handeled internally in sepastore.
*/
if( SCIPisCutEfficacious(scip, NULL, cut) )
{
assert(success == TRUE);
SCIPdebugMessage(" -> gomory cut for <%s>: act=%f, rhs=%f, eff=%f\n",
c >= 0 ? SCIPvarGetName(SCIPcolGetVar(cols[c])) : SCIProwGetName(rows[-c-1]),
cutact, cutrhs, SCIPgetCutEfficacy(scip, NULL, cut));
if( sepadata->makeintegral )
{
/* try to scale the cut to integral values */
SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip),
maxdnom, maxscale, MAKECONTINTEGRAL, &success) );
if( sepadata->forcecuts )
success = TRUE;
/* in case the left hand side in minus infinity and the right hand side is plus infinity the cut is
* useless so we are not taking it at all
*/
if( (SCIPisInfinity(scip, -SCIProwGetLhs(cut)) && SCIPisInfinity(scip, SCIProwGetRhs(cut))) )
success = FALSE;
/* @todo Trying to make the Gomory cut integral might fail. Due to numerical reasons/arguments we
* currently ignore such cuts. If the cut, however, has small support (let's say smaller or equal to
* 5), we might want to add that cut (even it does not have integral coefficients). To be able to
* do that we need to add a rank to the data structure of a row. The rank of original rows are
* zero and for aggregated rows it is the maximum over all used rows plus one.
*/
}
if( success )
{
SCIPdebugMessage(" -> found gomory cut <%s>: act=%f, rhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n",
cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
SCIPgetCutEfficacy(scip, NULL, cut),
SCIPgetRowMinCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut),
SCIPgetRowMaxCoef(scip, cut)/SCIPgetRowMinCoef(scip, cut));
/* flush all changes before adding the cut */
SCIP_CALL( SCIPflushRowExtensions(scip, cut) );
/* add global cuts which are not implicit bound changes to the cut pool */
if( !cutislocal )
{
if( sepadata->delayedcuts )
{
SCIP_CALL( SCIPaddDelayedPoolCut(scip, cut) );
}
else
{
SCIP_CALL( SCIPaddPoolCut(scip, cut) );
}
}
else
{
/* local cuts we add to the sepastore */
SCIP_CALL( SCIPaddCut(scip, NULL, cut, FALSE) );
}
naddedcuts++;
}
}
}
/* release the row */
SCIP_CALL( SCIPreleaseRow(scip, &cut) );
}
}
}
/* free temporary memory */
SCIPfreeBufferArray(scip, &binvrow);
SCIPfreeBufferArray(scip, &basisind);
SCIPfreeBufferArray(scip, &cutcoefs);
SCIPdebugMessage("end searching gomory cuts: found %d cuts\n", naddedcuts);
sepadata->lastncutsfound = SCIPgetNCutsFound(scip);
/* evalute the result of the separation */
if( cutoff )
*result = SCIP_CUTOFF;
else if ( naddedcuts > 0 )
*result = SCIP_SEPARATED;
else
*result = SCIP_DIDNOTFIND;
return SCIP_OKAY;
}
/** 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;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecMutation)
{ /*lint --e{715}*/
SCIP_Longint maxnnodes;
SCIP_Longint nsubnodes; /* node limit for the subproblem */
SCIP_HEURDATA* heurdata; /* heuristic's data */
SCIP* subscip; /* the subproblem created by mutation */
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_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real maxnnodesr;
SCIP_Real memorylimit;
SCIP_Real timelimit; /* timelimit for the subproblem */
SCIP_Real upperbound;
int nvars; /* number of original problem's variables */
int i;
SCIP_Bool success;
SCIP_RETCODE retcode;
assert( heur != NULL );
assert( scip != NULL );
assert( result != NULL );
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert( heurdata != NULL );
*result = SCIP_DELAYED;
/* only call heuristic, if feasible solution is available */
if( SCIPgetNSols(scip) <= 0 )
return SCIP_OKAY;
/* only call heuristic, if the best solution comes from transformed problem */
assert( SCIPgetBestSol(scip) != NULL );
if( SCIPsolIsOriginal(SCIPgetBestSol(scip)) )
return SCIP_OKAY;
/* only call heuristic, if enough nodes were processed since last incumbent */
if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip,SCIPgetBestSol(scip)) < heurdata->nwaitingnodes)
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* only call heuristic, if discrete variables are present */
if( SCIPgetNBinVars(scip) == 0 && SCIPgetNIntVars(scip) == 0 )
return SCIP_OKAY;
/* calculate the maximal number of branching nodes until heuristic is aborted */
maxnnodesr = heurdata->nodesquot * SCIPgetNNodes(scip);
/* reward mutation if it succeeded often, count the setup costs for the sub-MIP as 100 nodes */
maxnnodesr *= 1.0 + 2.0 * (SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur) + 1.0);
maxnnodes = (SCIP_Longint) maxnnodesr - 100 * SCIPheurGetNCalls(heur);
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 subproblem solving */
if( nsubnodes < heurdata->minnodes )
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) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
if( heurdata->uselprows )
{
char probname[SCIP_MAXSTRLEN];
/* copy all plugins */
SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );
/* get name of the original problem and add the string "_mutationsub" */
(void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_mutationsub", 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_Bool valid;
valid = FALSE;
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "rens", TRUE, FALSE, TRUE, &valid) );
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) );
}
SCIPdebugMessage("Copying the SCIP instance was %s complete.\n", valid ? "" : "not ");
}
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
/* free hash map */
SCIPhashmapFree(&varmapfw);
/* create a new problem, which fixes variables with same value in bestsol and LP relaxation */
SCIP_CALL( createSubproblem(scip, subscip, subvars, heurdata->minfixingrate, &heurdata->randseed, heurdata->uselprows) );
/* 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", nsubnodes) );
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 handlers; 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 decutions 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) );
}
/* 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) );
/* solve the subproblem */
SCIPdebugMessage("Solve Mutation 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 Mutation 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;
/* 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 )
*result = SCIP_FOUNDSOL;
}
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
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(heurExecOneopt)
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_SOL* bestsol; /* incumbent solution */
SCIP_SOL* worksol; /* heuristic's working solution */
SCIP_VAR** vars; /* SCIP variables */
SCIP_VAR** shiftcands; /* shiftable variables */
SCIP_ROW** lprows; /* SCIP LP rows */
SCIP_Real* activities; /* row activities for working solution */
SCIP_Real* shiftvals;
SCIP_Real lb;
SCIP_Real ub;
SCIP_Bool localrows;
SCIP_Bool valid;
int nchgbound;
int nbinvars;
int nintvars;
int nvars;
int nlprows;
int i;
int nshiftcands;
int shiftcandssize;
SCIP_RETCODE retcode;
assert(heur != NULL);
assert(scip != NULL);
assert(result != NULL);
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
*result = SCIP_DELAYED;
/* we only want to process each solution once */
bestsol = SCIPgetBestSol(scip);
if( bestsol == NULL || heurdata->lastsolindex == SCIPsolGetIndex(bestsol) )
return SCIP_OKAY;
/* reset the timing mask to its default value (at the root node it could be different) */
if( SCIPgetNNodes(scip) > 1 )
SCIPheurSetTimingmask(heur, HEUR_TIMING);
/* get problem variables */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
nintvars += nbinvars;
/* do not run if there are no discrete variables */
if( nintvars == 0 )
{
*result = SCIP_DIDNOTRUN;
return SCIP_OKAY;
}
if( heurtiming == SCIP_HEURTIMING_BEFOREPRESOL )
{
SCIP* subscip; /* the subproblem created by zeroobj */
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_Real* subsolvals; /* solution values of the subproblem */
SCIP_Real timelimit; /* time limit for zeroobj subproblem */
SCIP_Real memorylimit; /* memory limit for zeroobj subproblem */
SCIP_SOL* startsol;
SCIP_SOL** subsols;
int nsubsols;
if( !heurdata->beforepresol )
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;
/* 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) );
/* copy complete SCIP instance */
valid = FALSE;
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "oneopt", TRUE, FALSE, TRUE, &valid) );
SCIP_CALL( SCIPtransformProb(subscip) );
/* get variable image */
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
/* copy the solution */
SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );
SCIP_CALL( SCIPgetSolVals(scip, bestsol, nvars, vars, subsolvals) );
/* create start solution for the subproblem */
SCIP_CALL( SCIPcreateOrigSol(subscip, &startsol, NULL) );
SCIP_CALL( SCIPsetSolVals(subscip, startsol, nvars, subvars, subsolvals) );
/* try to add new solution to sub-SCIP and free it immediately */
valid = FALSE;
SCIP_CALL( SCIPtrySolFree(subscip, &startsol, FALSE, FALSE, FALSE, FALSE, &valid) );
SCIPfreeBufferArray(scip, &subsolvals);
SCIPhashmapFree(&varmapfw);
/* disable statistic timing inside sub SCIP */
SCIP_CALL( SCIPsetBoolParam(subscip, "timing/statistictiming", FALSE) );
/* deactivate basically everything except oneopt in the sub-SCIP */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
SCIP_CALL( SCIPsetHeuristics(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", 1LL) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
/* if necessary, some of the parameters have to be unfixed first */
if( SCIPisParamFixed(subscip, "lp/solvefreq") )
{
SCIPwarningMessage(scip, "unfixing parameter lp/solvefreq in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "lp/solvefreq") );
}
SCIP_CALL( SCIPsetIntParam(subscip, "lp/solvefreq", -1) );
if( SCIPisParamFixed(subscip, "heuristics/oneopt/freq") )
{
SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/freq in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/freq") );
}
SCIP_CALL( SCIPsetIntParam(subscip, "heuristics/oneopt/freq", 1) );
if( SCIPisParamFixed(subscip, "heuristics/oneopt/forcelpconstruction") )
{
SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/forcelpconstruction in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/forcelpconstruction") );
}
SCIP_CALL( SCIPsetBoolParam(subscip, "heuristics/oneopt/forcelpconstruction", TRUE) );
/* avoid recursive call, which would lead to an endless loop */
if( SCIPisParamFixed(subscip, "heuristics/oneopt/beforepresol") )
{
SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/beforepresol in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/beforepresol") );
}
SCIP_CALL( SCIPsetBoolParam(subscip, "heuristics/oneopt/beforepresol", FALSE) );
if( valid )
{
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 zeroobj heuristic; sub-SCIP terminated with code <%d>\n",retcode);
}
#ifdef SCIP_DEBUG
SCIP_CALL( SCIPprintStatistics(subscip, NULL) );
#endif
}
/* 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);
valid = FALSE;
for( i = 0; i < nsubsols && !valid; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &valid) );
if( valid )
*result = SCIP_FOUNDSOL;
}
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/* we can only work on solutions valid in the transformed space */
if( SCIPsolIsOriginal(bestsol) )
return SCIP_OKAY;
if( heurtiming == SCIP_HEURTIMING_BEFORENODE && (SCIPhasCurrentNodeLP(scip) || heurdata->forcelpconstruction) )
{
SCIP_Bool cutoff;
cutoff = FALSE;
SCIP_CALL( SCIPconstructLP(scip, &cutoff) );
SCIP_CALL( SCIPflushLP(scip) );
/* get problem variables again, SCIPconstructLP() might have added new variables */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
nintvars += nbinvars;
}
/* we need an LP */
if( SCIPgetNLPRows(scip) == 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
nchgbound = 0;
/* initialize data */
nshiftcands = 0;
shiftcandssize = 8;
heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
SCIP_CALL( SCIPcreateSolCopy(scip, &worksol, bestsol) );
SCIPsolSetHeur(worksol,heur);
SCIPdebugMessage("Starting bound adjustment in 1-opt heuristic\n");
/* maybe change solution values due to global bound changes first */
for( i = nvars - 1; i >= 0; --i )
{
SCIP_VAR* var;
SCIP_Real solval;
var = vars[i];
lb = SCIPvarGetLbGlobal(var);
ub = SCIPvarGetUbGlobal(var);
solval = SCIPgetSolVal(scip, bestsol,var);
/* old solution value is smaller than the actual lower bound */
if( SCIPisFeasLT(scip, solval, lb) )
{
/* set the solution value to the global lower bound */
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, lb) );
++nchgbound;
SCIPdebugMessage("var <%s> type %d, old solval %g now fixed to lb %g\n", SCIPvarGetName(var), SCIPvarGetType(var), solval, lb);
}
/* old solution value is greater than the actual upper bound */
else if( SCIPisFeasGT(scip, solval, SCIPvarGetUbGlobal(var)) )
{
/* set the solution value to the global upper bound */
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, ub) );
++nchgbound;
SCIPdebugMessage("var <%s> type %d, old solval %g now fixed to ub %g\n", SCIPvarGetName(var), SCIPvarGetType(var), solval, ub);
}
}
SCIPdebugMessage("number of bound changes (due to global bounds) = %d\n", nchgbound);
SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );
localrows = FALSE;
valid = TRUE;
/* initialize activities */
for( i = 0; i < nlprows; ++i )
{
SCIP_ROW* row;
row = lprows[i];
assert(SCIProwGetLPPos(row) == i);
if( !SCIProwIsLocal(row) )
{
activities[i] = SCIPgetRowSolActivity(scip, row, worksol);
SCIPdebugMessage("Row <%s> has activity %g\n", SCIProwGetName(row), activities[i]);
if( SCIPisFeasLT(scip, activities[i], SCIProwGetLhs(row)) || SCIPisFeasGT(scip, activities[i], SCIProwGetRhs(row)) )
{
valid = FALSE;
SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );
SCIPdebugMessage("row <%s> activity %g violates bounds, lhs = %g, rhs = %g\n", SCIProwGetName(row), activities[i], SCIProwGetLhs(row), SCIProwGetRhs(row));
break;
}
}
else
localrows = TRUE;
}
if( !valid )
{
/** @todo try to correct lp rows */
SCIPdebugMessage("Some global bound changes were not valid in lp rows.\n");
goto TERMINATE;
}
SCIP_CALL( SCIPallocBufferArray(scip, &shiftcands, shiftcandssize) );
SCIP_CALL( SCIPallocBufferArray(scip, &shiftvals, shiftcandssize) );
SCIPdebugMessage("Starting 1-opt heuristic\n");
/* enumerate all integer variables and find out which of them are shiftable */
for( i = 0; i < nintvars; i++ )
{
if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
{
SCIP_Real shiftval;
SCIP_Real solval;
/* find out whether the variable can be shifted */
solval = SCIPgetSolVal(scip, worksol, vars[i]);
shiftval = calcShiftVal(scip, vars[i], solval, activities);
/* insert the variable into the list of shifting candidates */
if( !SCIPisFeasZero(scip, shiftval) )
{
SCIPdebugMessage(" -> Variable <%s> can be shifted by <%1.1f> \n", SCIPvarGetName(vars[i]), shiftval);
if( nshiftcands == shiftcandssize)
{
shiftcandssize *= 8;
SCIP_CALL( SCIPreallocBufferArray(scip, &shiftcands, shiftcandssize) );
SCIP_CALL( SCIPreallocBufferArray(scip, &shiftvals, shiftcandssize) );
}
shiftcands[nshiftcands] = vars[i];
shiftvals[nshiftcands] = shiftval;
nshiftcands++;
}
}
}
/* if at least one variable can be shifted, shift variables sorted by their objective */
if( nshiftcands > 0 )
{
SCIP_Real shiftval;
SCIP_Real solval;
SCIP_VAR* var;
/* the case that exactly one variable can be shifted is slightly easier */
if( nshiftcands == 1 )
{
var = shiftcands[0];
assert(var != NULL);
solval = SCIPgetSolVal(scip, worksol, var);
shiftval = shiftvals[0];
assert(!SCIPisFeasZero(scip,shiftval));
SCIPdebugMessage(" Only one shiftcand found, var <%s>, which is now shifted by<%1.1f> \n",
SCIPvarGetName(var), shiftval);
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, solval+shiftval) );
}
else
{
SCIP_Real* objcoeffs;
SCIP_CALL( SCIPallocBufferArray(scip, &objcoeffs, nshiftcands) );
SCIPdebugMessage(" %d shiftcands found \n", nshiftcands);
/* sort the variables by their objective, optionally weighted with the shiftval */
if( heurdata->weightedobj )
{
for( i = 0; i < nshiftcands; ++i )
objcoeffs[i] = SCIPvarGetObj(shiftcands[i])*shiftvals[i];
}
else
{
for( i = 0; i < nshiftcands; ++i )
objcoeffs[i] = SCIPvarGetObj(shiftcands[i]);
}
/* sort arrays with respect to the first one */
SCIPsortRealPtr(objcoeffs, (void**)shiftcands, nshiftcands);
/* try to shift each variable -> Activities have to be updated */
for( i = 0; i < nshiftcands; ++i )
{
var = shiftcands[i];
assert(var != NULL);
solval = SCIPgetSolVal(scip, worksol, var);
shiftval = calcShiftVal(scip, var, solval, activities);
SCIPdebugMessage(" -> Variable <%s> is now shifted by <%1.1f> \n", SCIPvarGetName(vars[i]), shiftval);
assert(i > 0 || !SCIPisFeasZero(scip, shiftval));
assert(SCIPisFeasGE(scip, solval+shiftval, SCIPvarGetLbGlobal(var)) && SCIPisFeasLE(scip, solval+shiftval, SCIPvarGetUbGlobal(var)));
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, solval+shiftval) );
SCIP_CALL( updateRowActivities(scip, activities, var, shiftval) );
}
SCIPfreeBufferArray(scip, &objcoeffs);
}
/* if the problem is a pure IP, try to install the solution, if it is a MIP, solve LP again to set the continuous
* variables to the best possible value
*/
if( nvars == nintvars || !SCIPhasCurrentNodeLP(scip) || SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
{
SCIP_Bool success;
/* since we ignore local rows, we cannot guarantee their feasibility and have to set the checklprows flag to
* TRUE if local rows are present
*/
SCIP_CALL( SCIPtrySol(scip, worksol, FALSE, FALSE, FALSE, localrows, &success) );
if( success )
{
SCIPdebugMessage("found feasible shifted solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, worksol, NULL, FALSE) ) );
heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
*result = SCIP_FOUNDSOL;
}
}
else
{
SCIP_Bool lperror;
#ifdef NDEBUG
SCIP_RETCODE retstat;
#endif
SCIPdebugMessage("shifted solution should be feasible -> solve LP to fix continuous variables to best values\n");
/* start diving to calculate the LP relaxation */
SCIP_CALL( SCIPstartDive(scip) );
/* set the bounds of the variables: fixed for integers, global bounds for continuous */
for( i = 0; i < nvars; ++i )
{
if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
{
SCIP_CALL( SCIPchgVarLbDive(scip, vars[i], SCIPvarGetLbGlobal(vars[i])) );
SCIP_CALL( SCIPchgVarUbDive(scip, vars[i], SCIPvarGetUbGlobal(vars[i])) );
}
}
/* apply this after global bounds to not cause an error with intermediate empty domains */
for( i = 0; i < nintvars; ++i )
{
if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
{
solval = SCIPgetSolVal(scip, worksol, vars[i]);
SCIP_CALL( SCIPchgVarLbDive(scip, vars[i], solval) );
SCIP_CALL( SCIPchgVarUbDive(scip, vars[i], solval) );
}
}
/* solve LP */
SCIPdebugMessage(" -> old LP iterations: %" SCIP_LONGINT_FORMAT "\n", SCIPgetNLPIterations(scip));
/**@todo in case of an MINLP, if SCIPisNLPConstructed() is TRUE, say, rather solve the NLP instead of the 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
retstat = SCIPsolveDiveLP(scip, -1, &lperror, NULL);
if( retstat != SCIP_OKAY )
{
SCIPwarningMessage(scip, "Error while solving LP in Oneopt heuristic; LP solve terminated with code <%d>\n",retstat);
}
#else
SCIP_CALL( SCIPsolveDiveLP(scip, -1, &lperror, NULL) );
#endif
SCIPdebugMessage(" -> new LP iterations: %" SCIP_LONGINT_FORMAT "\n", SCIPgetNLPIterations(scip));
SCIPdebugMessage(" -> error=%u, status=%d\n", lperror, SCIPgetLPSolstat(scip));
/* check if this is a feasible solution */
if( !lperror && SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OPTIMAL )
{
SCIP_Bool success;
/* copy the current LP solution to the working solution */
SCIP_CALL( SCIPlinkLPSol(scip, worksol) );
SCIP_CALL( SCIPtrySol(scip, worksol, FALSE, FALSE, FALSE, FALSE, &success) );
/* check solution for feasibility */
if( success )
{
SCIPdebugMessage("found feasible shifted solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, worksol, NULL, FALSE) ) );
heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
*result = SCIP_FOUNDSOL;
}
}
/* terminate the diving */
SCIP_CALL( SCIPendDive(scip) );
}
}
SCIPdebugMessage("Finished 1-opt heuristic\n");
SCIPfreeBufferArray(scip, &shiftvals);
SCIPfreeBufferArray(scip, &shiftcands);
TERMINATE:
SCIPfreeBufferArray(scip, &activities);
SCIP_CALL( SCIPfreeSol(scip, &worksol) );
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;
}
/** 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;
}
/** arbitrary primal solution separation method of separator */
static
SCIP_DECL_SEPAEXECSOL(sepaExecsolImpliedbounds)
{ /*lint --e{715}*/
SCIP_VAR** vars;
SCIP_VAR** fracvars;
SCIP_Real* solvals;
SCIP_Real* fracvals;
SCIP_Bool cutoff;
int nvars;
int nbinvars;
int nfracs;
int ncuts;
int i;
assert(sepa != NULL);
assert(scip != NULL);
*result = SCIP_DIDNOTRUN;
/* gets active problem variables */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, NULL, NULL, NULL) );
if( nbinvars == 0 )
return SCIP_OKAY;
/* get solution values for all variables */
SCIP_CALL( SCIPallocBufferArray(scip, &solvals, nvars) );
SCIP_CALL( SCIPgetSolVals(scip, sol, nvars, vars, solvals) );
/* get binary problem variables that are fractional in given solution */
SCIP_CALL( SCIPallocBufferArray(scip, &fracvars, nbinvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &fracvals, nbinvars) );
nfracs = 0;
for( i = 0; i < nbinvars; ++i )
{
if( !SCIPisFeasIntegral(scip, solvals[i]) )
{
fracvars[nfracs] = vars[i];
fracvals[nfracs] = solvals[i];
nfracs++;
}
}
/* call the cut separation */
ncuts = 0;
cutoff = FALSE;
if( nfracs > 0 )
{
SCIP_CALL( separateCuts(scip, sepa, sol, solvals, fracvars, fracvals, nfracs, &cutoff, &ncuts) );
}
/* adjust result code */
if ( cutoff )
*result = SCIP_CUTOFF;
else if ( ncuts > 0 )
*result = SCIP_SEPARATED;
else
*result = SCIP_DIDNOTFIND;
/* free temporary memory */
SCIPfreeBufferArray(scip, &fracvals);
SCIPfreeBufferArray(scip, &fracvars);
SCIPfreeBufferArray(scip, &solvals);
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;
}
/** 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;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecTrivial)
{ /*lint --e{715}*/
SCIP_VAR** vars;
SCIP_SOL* lbsol; /* solution where all variables are set to their lower bounds */
SCIP_SOL* ubsol; /* solution where all variables are set to their upper bounds */
SCIP_SOL* zerosol; /* solution where all variables are set to zero */
SCIP_SOL* locksol; /* solution where all variables are set to the bound with the fewer locks */
SCIP_Real large;
int nvars;
int nbinvars;
int i;
SCIP_Bool success;
SCIP_Bool zerovalid;
*result = SCIP_DIDNOTRUN;
if( SCIPgetNRuns(scip) > 1 )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
success = FALSE;
/* initialize data structure */
SCIP_CALL( SCIPcreateSol(scip, &lbsol, heur) );
SCIP_CALL( SCIPcreateSol(scip, &ubsol, heur) );
SCIP_CALL( SCIPcreateSol(scip, &zerosol, heur) );
SCIP_CALL( SCIPcreateSol(scip, &locksol, heur) );
/* determine large value to set variables to */
large = SCIPinfinity(scip);
if( !SCIPisInfinity(scip, 0.1 / SCIPfeastol(scip)) )
large = 0.1 / SCIPfeastol(scip);
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, NULL, NULL, NULL) );
/* if the problem is binary, we do not have to check the zero solution, since it is equal to the lower bound
* solution */
zerovalid = (nvars != nbinvars);
assert(vars != NULL || nvars == 0);
for( i = 0; i < nvars; i++ )
{
SCIP_Real lb;
SCIP_Real ub;
assert(vars != NULL); /* this assert is needed for flexelint */
lb = SCIPvarGetLbLocal(vars[i]);
ub = SCIPvarGetUbLocal(vars[i]);
/* if problem is obviously infeasible due to empty domain, stop */
if( SCIPisGT(scip, lb, ub) )
goto TERMINATE;
/* set bounds to sufficient large value */
if( SCIPisInfinity(scip, -lb) )
lb = MIN(-large, ub);
if( SCIPisInfinity(scip, ub) )
{
SCIP_Real tmp;
tmp = SCIPvarGetLbLocal(vars[i]);
ub = MAX(tmp, large);
}
SCIP_CALL( SCIPsetSolVal(scip, lbsol, vars[i], lb) );
SCIP_CALL( SCIPsetSolVal(scip, ubsol, vars[i], ub) );
/* try the zero vector, if it is in the bounds region */
if( zerovalid )
{
if( SCIPisLE(scip, lb, 0.0) && SCIPisLE(scip, 0.0, ub) )
{
SCIP_CALL( SCIPsetSolVal(scip, zerosol, vars[i], 0.0) );
}
else
zerovalid = FALSE;
}
/* set variables to the bound with fewer locks, if tie choose an average value */
if( SCIPvarGetNLocksDown(vars[i]) > SCIPvarGetNLocksUp(vars[i]) )
{
SCIP_CALL( SCIPsetSolVal(scip, locksol, vars[i], ub) );
}
else if( SCIPvarGetNLocksDown(vars[i]) < SCIPvarGetNLocksUp(vars[i]) )
{
SCIP_CALL( SCIPsetSolVal(scip, locksol, vars[i], lb) );
}
else
{
SCIP_Real solval;
solval = (lb+ub)/2.0;
/* if a tie occurs, roughly every third integer variable will be rounded up */
if( SCIPvarGetType(vars[i]) != SCIP_VARTYPE_CONTINUOUS )
solval = i % 3 == 0 ? SCIPceil(scip,solval) : SCIPfloor(scip,solval);
assert(SCIPisFeasLE(scip,SCIPvarGetLbLocal(vars[i]),solval) && SCIPisFeasLE(scip,solval,SCIPvarGetUbLocal(vars[i])));
SCIP_CALL( SCIPsetSolVal(scip, locksol, vars[i], solval) );
}
}
/* try lower bound solution */
SCIPdebugMessage("try lower bound solution\n");
SCIP_CALL( SCIPtrySol(scip, lbsol, FALSE, FALSE, TRUE, TRUE, &success) );
if( success )
{
SCIPdebugMessage("found feasible lower bound solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, lbsol, NULL, FALSE) ) );
*result = SCIP_FOUNDSOL;
}
/* try upper bound solution */
SCIPdebugMessage("try upper bound solution\n");
SCIP_CALL( SCIPtrySol(scip, ubsol, FALSE, FALSE, TRUE, TRUE, &success) );
if( success )
{
SCIPdebugMessage("found feasible upper bound solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, ubsol, NULL, FALSE) ) );
*result = SCIP_FOUNDSOL;
}
/* try zero solution */
if( zerovalid )
{
SCIPdebugMessage("try zero solution\n");
SCIP_CALL( SCIPtrySol(scip, zerosol, FALSE, FALSE, TRUE, TRUE, &success) );
if( success )
{
SCIPdebugMessage("found feasible zero solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, zerosol, NULL, FALSE) ) );
*result = SCIP_FOUNDSOL;
}
}
/* try lock solution */
SCIPdebugMessage("try lock solution\n");
SCIP_CALL( SCIPtrySol(scip, locksol, FALSE, FALSE, TRUE, TRUE, &success) );
if( success )
{
SCIPdebugMessage("found feasible lock solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, locksol, NULL, FALSE) ) );
*result = SCIP_FOUNDSOL;
}
TERMINATE:
/* free solutions */
SCIP_CALL( SCIPfreeSol(scip, &lbsol) );
SCIP_CALL( SCIPfreeSol(scip, &ubsol) );
SCIP_CALL( SCIPfreeSol(scip, &zerosol) );
SCIP_CALL( SCIPfreeSol(scip, &locksol) );
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;
}
/** call writing method */
static
SCIP_RETCODE writeBounds(
SCIP* scip, /**< SCIP data structure */
FILE* file, /**< file to write to or NULL */
SCIP_Bool writesubmipdualbound/**< write dualbounds of submip roots for all open nodes */
)
{
SCIP_NODE** opennodes;
int nopennodes;
int n;
int v;
assert(scip != NULL);
nopennodes = -1;
#ifdef LONGSTATS
SCIPinfoMessage(scip, file, "Status after %"SCIP_LONGINT_FORMAT" processed nodes (%d open)\n", SCIPgetNNodes(scip), SCIPgetNNodesLeft(scip));
SCIPinfoMessage(scip, file, "Primalbound: %g\n", SCIPgetPrimalbound(scip));
SCIPinfoMessage(scip, file, "Dualbound: %g\n", SCIPgetDualbound(scip));
#else
SCIPinfoMessage(scip, file, "PB %g\n", SCIPgetPrimalbound(scip));
#endif
/* get all open nodes and therefor print all dualbounds */
for( v = 2; v >= 0; --v )
{
SCIP_NODE* node;
switch( v )
{
case 2:
SCIP_CALL( SCIPgetChildren(scip, &opennodes, &nopennodes) );
break;
case 1:
SCIP_CALL( SCIPgetSiblings(scip, &opennodes, &nopennodes) );
break;
case 0:
SCIP_CALL( SCIPgetLeaves(scip, &opennodes, &nopennodes) );
break;
default:
assert(0);
break;
}
assert(nopennodes >= 0);
/* print all node information */
for( n = nopennodes - 1; n >= 0 && !SCIPisStopped(scip); --n )
{
node = opennodes[n];
if( writesubmipdualbound )
{
SCIP* subscip;
SCIP_Bool valid;
SCIP_HASHMAP* varmap; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_VAR** vars; /* original problem's variables */
int nvars;
SCIP_Real submipdb;
SCIP_Bool cutoff;
SCIP_CALL( SCIPcreate(&subscip) );
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmap, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
submipdb = SCIP_INVALID;
valid = FALSE;
cutoff = FALSE;
SCIP_CALL( SCIPcopy(scip, subscip, varmap, NULL, "__boundwriting", TRUE, FALSE, TRUE, &valid) );
if( valid )
{
SCIP_VAR** branchvars;
SCIP_Real* branchbounds;
SCIP_BOUNDTYPE* boundtypes;
int nbranchvars;
int size;
size = SCIPnodeGetDepth(node);
/* allocate memory for all branching decisions */
SCIP_CALL( SCIPallocBufferArray(scip, &branchvars, size) );
SCIP_CALL( SCIPallocBufferArray(scip, &branchbounds, size) );
SCIP_CALL( SCIPallocBufferArray(scip, &boundtypes, size) );
/* we assume that we only have one branching decision at each node */
SCIPnodeGetAncestorBranchings( node, branchvars, branchbounds, boundtypes, &nbranchvars, size );
/* check if did not have enough memory */
if( nbranchvars > size )
{
size = nbranchvars;
SCIP_CALL( SCIPallocBufferArray(scip, &branchvars, size) );
SCIP_CALL( SCIPallocBufferArray(scip, &branchbounds, size) );
SCIP_CALL( SCIPallocBufferArray(scip, &boundtypes, size) );
/* now getting all information */
SCIPnodeGetAncestorBranchings( node, branchvars, branchbounds, boundtypes, &nbranchvars, size );
}
/* apply all changes to the submip */
SCIP_CALL( applyDomainChanges(subscip, branchvars, branchbounds, boundtypes, nbranchvars, varmap) );
/* free memory for all branching decisions */
SCIPfreeBufferArray(scip, &boundtypes);
SCIPfreeBufferArray(scip, &branchbounds);
SCIPfreeBufferArray(scip, &branchvars);
/* 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) );
/* solve only root node */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", 1LL) );
/* set cutoffbound as objective limit for subscip */
SCIP_CALL( SCIPsetObjlimit(subscip, SCIPgetCutoffbound(scip)) );
SCIP_CALL( SCIPsolve(subscip) );
cutoff = (SCIPgetStatus(subscip) == SCIP_STATUS_INFEASIBLE);
submipdb = SCIPgetDualbound(subscip) * SCIPgetTransObjscale(scip) + SCIPgetTransObjoffset(scip);
}
#ifdef LONGSTATS
SCIPinfoMessage(scip, file, "Node %"SCIP_LONGINT_FORMAT" (depth %d): dualbound: %g, nodesubmiprootdualbound: %g %s\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node), submipdb, cutoff ? "(cutoff)" : "");
#else
SCIPinfoMessage(scip, file, "%"SCIP_LONGINT_FORMAT" %d %g %g %s\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node), submipdb, cutoff ? "(cutoff)" : "");
#endif
/* free hash map */
SCIPhashmapFree(&varmap);
SCIP_CALL( SCIPfree(&subscip) );
}
else
{
#ifdef LONGSTATS
SCIPinfoMessage(scip, file, "Node %"SCIP_LONGINT_FORMAT" (depth %d): dualbound: %g\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node));
#else
SCIPinfoMessage(scip, file, "%"SCIP_LONGINT_FORMAT" %d %g\n", SCIPnodeGetNumber(node), SCIPnodeGetDepth(node), SCIPgetNodeDualbound(scip, node));
#endif
}
}
}
#ifdef LONGSTATS
SCIPinfoMessage(scip, file, "\n");
#endif
return SCIP_OKAY;
}
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpStrongcg)
{ /*lint --e{715}*/
SCIP_SEPADATA* sepadata;
SCIP_VAR** vars;
SCIP_COL** cols;
SCIP_ROW** rows;
SCIP_Real* varsolvals;
SCIP_Real* binvrow;
SCIP_Real* cutcoefs;
SCIP_Real cutrhs;
SCIP_Real cutact;
SCIP_Real maxscale;
SCIP_Longint maxdnom;
int* basisind;
int* inds;
int ninds;
int nvars;
int ncols;
int nrows;
int ncalls;
int depth;
int maxdepth;
int maxsepacuts;
int ncuts;
int c;
int i;
int cutrank;
SCIP_Bool success;
SCIP_Bool cutislocal;
char normtype;
assert(sepa != NULL);
assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
sepadata = SCIPsepaGetData(sepa);
assert(sepadata != NULL);
depth = SCIPgetDepth(scip);
ncalls = SCIPsepaGetNCallsAtNode(sepa);
/* only call separator, if we are not close to terminating */
if( SCIPisStopped(scip) )
return SCIP_OKAY;
/* only call the strong CG cut separator a given number of times at each node */
if( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot)
|| (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) )
return SCIP_OKAY;
/* only call separator, if an optimal LP solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call separator, if the LP solution is basic */
if( !SCIPisLPSolBasic(scip) )
return SCIP_OKAY;
/* only call separator, if there are fractional variables */
if( SCIPgetNLPBranchCands(scip) == 0 )
return SCIP_OKAY;
/* get variables data */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* get LP data */
SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
if( ncols == 0 || nrows == 0 )
return SCIP_OKAY;
#if 0 /* if too many columns, separator is usually very slow: delay it until no other cuts have been found */
if( ncols >= 50*nrows )
return SCIP_OKAY;
if( ncols >= 5*nrows )
{
int ncutsfound;
ncutsfound = SCIPgetNCutsFound(scip);
if( ncutsfound > sepadata->lastncutsfound || !SCIPsepaWasLPDelayed(sepa) )
{
sepadata->lastncutsfound = ncutsfound;
*result = SCIP_DELAYED;
return SCIP_OKAY;
}
}
#endif
/* get the type of norm to use for efficacy calculations */
SCIP_CALL( SCIPgetCharParam(scip, "separating/efficacynorm", &normtype) );
/* set the maximal denominator in rational representation of strong CG cut and the maximal scale factor to
* scale resulting cut to integral values to avoid numerical instabilities
*/
/**@todo find better but still stable strong CG cut settings: look at dcmulti, gesa3, khb0525, misc06, p2756 */
maxdepth = SCIPgetMaxDepth(scip);
if( depth == 0 )
{
maxdnom = 1000;
maxscale = 1000.0;
}
else if( depth <= maxdepth/4 )
{
maxdnom = 1000;
maxscale = 1000.0;
}
else if( depth <= maxdepth/2 )
{
maxdnom = 100;
maxscale = 100.0;
}
else
{
maxdnom = 10;
maxscale = 10.0;
}
*result = SCIP_DIDNOTFIND;
/* allocate temporary memory */
SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) );
SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) );
SCIP_CALL( SCIPallocBufferArray(scip, &inds, nrows) );
varsolvals = NULL; /* allocate this later, if needed */
/* get basis indices */
SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) );
/* get the maximal number of cuts allowed in a separation round */
if( depth == 0 )
maxsepacuts = sepadata->maxsepacutsroot;
else
maxsepacuts = sepadata->maxsepacuts;
SCIPdebugMessage("searching strong CG cuts: %d cols, %d rows, maxdnom=%" SCIP_LONGINT_FORMAT ", maxscale=%g, maxcuts=%d\n",
ncols, nrows, maxdnom, maxscale, maxsepacuts);
/* for all basic columns belonging to integer variables, try to generate a strong CG cut */
ncuts = 0;
for( i = 0; i < nrows && ncuts < maxsepacuts && !SCIPisStopped(scip) && *result != SCIP_CUTOFF; ++i )
{
SCIP_Bool tryrow;
tryrow = FALSE;
c = basisind[i];
if( c >= 0 )
{
SCIP_VAR* var;
assert(c < ncols);
var = SCIPcolGetVar(cols[c]);
if( SCIPvarGetType(var) != SCIP_VARTYPE_CONTINUOUS )
{
SCIP_Real primsol;
primsol = SCIPcolGetPrimsol(cols[c]);
assert(SCIPgetVarSol(scip, var) == primsol); /*lint !e777*/
if( SCIPfeasFrac(scip, primsol) >= MINFRAC )
{
SCIPdebugMessage("trying strong CG cut for col <%s> [%g]\n", SCIPvarGetName(var), primsol);
tryrow = TRUE;
}
}
}
#ifdef SEPARATEROWS
else
{
SCIP_ROW* row;
assert(0 <= -c-1 && -c-1 < nrows);
row = rows[-c-1];
if( SCIProwIsIntegral(row) && !SCIProwIsModifiable(row) )
{
SCIP_Real primsol;
primsol = SCIPgetRowActivity(scip, row);
if( SCIPfeasFrac(scip, primsol) >= MINFRAC )
{
SCIPdebugMessage("trying strong CG cut for row <%s> [%g]\n", SCIProwGetName(row), primsol);
tryrow = TRUE;
}
}
}
#endif
if( tryrow )
{
/* get the row of B^-1 for this basic integer variable with fractional solution value */
SCIP_CALL( SCIPgetLPBInvRow(scip, i, binvrow, inds, &ninds) );
#ifdef SCIP_DEBUG
/* initialize variables, that might not have been initialized in SCIPcalcMIR if success == FALSE */
cutact = 0.0;
cutrhs = SCIPinfinity(scip);
#endif
/* create a strong CG cut out of the weighted LP rows using the B^-1 row as weights */
SCIP_CALL( SCIPcalcStrongCG(scip, BOUNDSWITCH, USEVBDS, ALLOWLOCAL, (int) MAXAGGRLEN(nvars), sepadata->maxweightrange, MINFRAC, MAXFRAC,
binvrow, inds, ninds, 1.0, cutcoefs, &cutrhs, &cutact, &success, &cutislocal, &cutrank) );
assert(ALLOWLOCAL || !cutislocal);
SCIPdebugMessage(" -> success=%u: %g <= %g\n", success, cutact, cutrhs);
/* if successful, convert dense cut into sparse row, and add the row as a cut */
if( success && SCIPisFeasGT(scip, cutact, cutrhs) )
{
SCIP_VAR** cutvars;
SCIP_Real* cutvals;
SCIP_Real cutnorm;
int cutlen;
/* if this is the first successful cut, get the LP solution for all COLUMN variables */
if( varsolvals == NULL )
{
int v;
SCIP_CALL( SCIPallocBufferArray(scip, &varsolvals, nvars) );
for( v = 0; v < nvars; ++v )
{
if( SCIPvarGetStatus(vars[v]) == SCIP_VARSTATUS_COLUMN )
varsolvals[v] = SCIPvarGetLPSol(vars[v]);
}
}
assert(varsolvals != NULL);
/* get temporary memory for storing the cut as sparse row */
SCIP_CALL( SCIPallocBufferArray(scip, &cutvars, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &cutvals, nvars) );
/* store the cut as sparse row, calculate activity and norm of cut */
SCIP_CALL( storeCutInArrays(scip, nvars, vars, cutcoefs, varsolvals, normtype,
cutvars, cutvals, &cutlen, &cutact, &cutnorm) );
SCIPdebugMessage(" -> strong CG cut for <%s>: act=%f, rhs=%f, norm=%f, eff=%f, rank=%d\n",
c >= 0 ? SCIPvarGetName(SCIPcolGetVar(cols[c])) : SCIProwGetName(rows[-c-1]),
cutact, cutrhs, cutnorm, (cutact - cutrhs)/cutnorm, cutrank);
if( SCIPisPositive(scip, cutnorm) && SCIPisEfficacious(scip, (cutact - cutrhs)/cutnorm) )
{
SCIP_ROW* cut;
char cutname[SCIP_MAXSTRLEN];
/* create the cut */
if( c >= 0 )
(void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "scg%d_x%d", SCIPgetNLPs(scip), c);
else
(void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "scg%d_s%d", SCIPgetNLPs(scip), -c-1);
SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &cut, sepa, cutname, -SCIPinfinity(scip), cutrhs, cutislocal, FALSE, sepadata->dynamiccuts) );
SCIP_CALL( SCIPaddVarsToRow(scip, cut, cutlen, cutvars, cutvals) );
/*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
SCIProwChgRank(cut, cutrank);
assert(success);
#ifdef MAKECUTINTEGRAL
/* try to scale the cut to integral values */
SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip),
maxdnom, maxscale, MAKECONTINTEGRAL, &success) );
#else
#ifdef MAKEINTCUTINTEGRAL
/* try to scale the cut to integral values if there are no continuous variables
* -> leads to an integral slack variable that can later be used for other cuts
*/
{
int k = 0;
while ( k < cutlen && SCIPvarIsIntegral(cutvars[k]) )
++k;
if( k == cutlen )
{
SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip),
maxdnom, maxscale, MAKECONTINTEGRAL, &success) );
}
}
#endif
#endif
#ifndef FORCECUTINTEGRAL
success = TRUE;
#endif
if( success )
{
if( !SCIPisCutEfficacious(scip, NULL, cut) )
{
SCIPdebugMessage(" -> strong CG cut <%s> no longer efficacious: act=%f, rhs=%f, norm=%f, eff=%f\n",
cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
SCIPgetCutEfficacy(scip, NULL, cut));
/*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
success = FALSE;
}
else
{
SCIP_Bool infeasible;
SCIPdebugMessage(" -> found strong CG cut <%s>: act=%f, rhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n",
cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
SCIPgetCutEfficacy(scip, NULL, cut),
SCIPgetRowMinCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut),
SCIPgetRowMaxCoef(scip, cut)/SCIPgetRowMinCoef(scip, cut));
/*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
SCIP_CALL( SCIPaddCut(scip, NULL, cut, FALSE, &infeasible) );
if ( infeasible )
*result = SCIP_CUTOFF;
else
{
if( !cutislocal )
{
SCIP_CALL( SCIPaddPoolCut(scip, cut) );
}
*result = SCIP_SEPARATED;
}
ncuts++;
}
}
else
{
SCIPdebugMessage(" -> strong CG cut <%s> couldn't be scaled to integral coefficients: act=%f, rhs=%f, norm=%f, eff=%f\n",
cutname, cutact, cutrhs, cutnorm, SCIPgetCutEfficacy(scip, NULL, cut));
}
/* release the row */
SCIP_CALL( SCIPreleaseRow(scip, &cut) );
}
/* free temporary memory */
SCIPfreeBufferArray(scip, &cutvals);
SCIPfreeBufferArray(scip, &cutvars);
}
}
}
/* free temporary memory */
SCIPfreeBufferArrayNull(scip, &varsolvals);
SCIPfreeBufferArray(scip, &inds);
SCIPfreeBufferArray(scip, &binvrow);
SCIPfreeBufferArray(scip, &basisind);
SCIPfreeBufferArray(scip, &cutcoefs);
SCIPdebugMessage("end searching strong CG cuts: found %d cuts\n", ncuts);
sepadata->lastncutsfound = SCIPgetNCutsFound(scip);
return SCIP_OKAY;
}
/** 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;
}
/** create the extra constraint of local branching and add it to subscip */
static
SCIP_RETCODE addLocalBranchingConstraint(
SCIP* scip, /**< SCIP data structure of the original problem */
SCIP* subscip, /**< SCIP data structure of the subproblem */
SCIP_VAR** subvars, /**< variables of the subproblem */
SCIP_HEURDATA* heurdata /**< heuristic's data structure */
)
{
SCIP_CONS* cons; /* local branching constraint to create */
SCIP_VAR** consvars;
SCIP_VAR** vars;
SCIP_SOL* bestsol;
int nbinvars;
int i;
SCIP_Real lhs;
SCIP_Real rhs;
SCIP_Real* consvals;
char consname[SCIP_MAXSTRLEN];
(void) SCIPsnprintf(consname, SCIP_MAXSTRLEN, "%s_localbranchcons", SCIPgetProbName(scip));
/* get the data of the variables and the best solution */
SCIP_CALL( SCIPgetVarsData(scip, &vars, NULL, &nbinvars, NULL, NULL, NULL) );
bestsol = SCIPgetBestSol(scip);
assert( bestsol != NULL );
/* memory allocation */
SCIP_CALL( SCIPallocBufferArray(scip, &consvars, nbinvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &consvals, nbinvars) );
/* set initial left and right hand sides of local branching constraint */
lhs = (SCIP_Real)heurdata->emptyneighborhoodsize + 1.0;
rhs = (SCIP_Real)heurdata->curneighborhoodsize;
/* create the distance (to incumbent) function of the binary variables */
for( i = 0; i < nbinvars; i++ )
{
SCIP_Real solval;
solval = SCIPgetSolVal(scip, bestsol, vars[i]);
assert( SCIPisFeasIntegral(scip,solval) );
/* is variable i part of the binary support of bestsol? */
if( SCIPisFeasEQ(scip,solval,1.0) )
{
consvals[i] = -1.0;
rhs -= 1.0;
lhs -= 1.0;
}
else
consvals[i] = 1.0;
consvars[i] = subvars[i];
assert( SCIPvarGetType(consvars[i]) == SCIP_VARTYPE_BINARY );
}
/* creates localbranching constraint and adds it to subscip */
SCIP_CALL( SCIPcreateConsLinear(subscip, &cons, consname, nbinvars, consvars, consvals,
lhs, rhs, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
/* free local memory */
SCIPfreeBufferArray(scip, &consvals);
SCIPfreeBufferArray(scip, &consvars);
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;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecOctane)
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_SOL* sol;
SCIP_SOL** first_sols; /* stores the first ffirst sols in order to check for common violation of a row */
SCIP_VAR** vars; /* the variables of the problem */
SCIP_VAR** fracvars; /* variables, that are fractional in current LP solution */
SCIP_VAR** subspacevars; /* the variables on which the search is performed. Either coinciding with vars or with the
* space of all fractional variables of the current LP solution */
SCIP_Real p; /* n/2 - <delta,x> ( for some facet delta ) */
SCIP_Real q; /* <delta,a> */
SCIP_Real* rayorigin; /* origin of the ray, vector x in paper */
SCIP_Real* raydirection; /* direction of the ray, vector a in paper */
SCIP_Real* negquotient; /* negated quotient of rayorigin and raydirection, vector v in paper */
SCIP_Real* lambda; /* stores the distance of the facets (s.b.) to the origin of the ray */
SCIP_Bool usefracspace; /* determines whether the search concentrates on fractional variables and fixes integer ones */
SCIP_Bool cons_viol; /* used for checking whether a linear constraint is violated by one of the possible solutions */
SCIP_Bool success;
SCIP_Bool* sign; /* signature of the direction of the ray */
SCIP_Bool** facets; /* list of extended facets */
int nvars; /* number of variables */
int nbinvars; /* number of 0-1-variables */
int nfracvars; /* number of fractional variables in current LP solution */
int nsubspacevars; /* dimension of the subspace on which the search is performed */
int nfacets; /* number of facets hidden by the ray that where already found */
int i; /* counter */
int j; /* counter */
int f_max; /* {0,1}-points to be checked */
int f_first; /* {0,1}-points to be generated at first in order to check whether a restart is necessary */
int r; /* counter */
int firstrule;
int* perm; /* stores the way in which the coordinates were permuted */
int* fracspace; /* maps the variables of the subspace to the original variables */
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;
*result = SCIP_DIDNOTRUN;
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, NULL, NULL, NULL) );
/* OCTANE is for use in 0-1 programs only */
if( nvars != nbinvars )
return SCIP_OKAY;
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert( heurdata != NULL );
/* don't call heuristic, if it was not successful enough in the past */
/*lint --e{647}*/
if( SCIPgetNNodes(scip) % (SCIPheurGetNCalls(heur) / (100 * SCIPheurGetNBestSolsFound(heur) + 10*heurdata->nsuccess + 1) + 1) != 0 )
return SCIP_OKAY;
SCIP_CALL( SCIPgetLPBranchCands(scip, &fracvars, NULL, NULL, &nfracvars, NULL) );
/* don't use integral starting points */
if( nfracvars == 0 )
return SCIP_OKAY;
/* get working pointers from heurdata */
sol = heurdata->sol;
assert( sol != NULL );
f_max = heurdata->f_max;
f_first = heurdata->f_first;
usefracspace = heurdata->usefracspace;
SCIP_CALL( SCIPallocBufferArray(scip, &fracspace, nvars) );
/* determine the space one which OCTANE should work either as the whole space or as the space of fractional variables */
if( usefracspace )
{
nsubspacevars = nfracvars;
SCIP_CALL( SCIPallocBufferArray(scip, &subspacevars, nsubspacevars) );
BMScopyMemoryArray(subspacevars, fracvars, nsubspacevars);
for( i = nvars - 1; i >= 0; --i )
fracspace[i] = -1;
for( i = nsubspacevars - 1; i >= 0; --i )
fracspace[SCIPvarGetProbindex(subspacevars[i])] = i;
}
else
{
int currentindex;
nsubspacevars = nvars;
SCIP_CALL( SCIPallocBufferArray(scip, &subspacevars, nsubspacevars) );
/* only copy the variables which are in the current LP */
currentindex = 0;
for( i = 0; i < nvars; ++i )
{
if( SCIPcolGetLPPos(SCIPvarGetCol(vars[i])) >= 0 )
{
subspacevars[currentindex] = vars[i];
fracspace[i] = currentindex;
++currentindex;
}
else
{
fracspace[i] = -1;
--nsubspacevars;
}
}
}
/* nothing to do for empty search space */
if( nsubspacevars == 0 )
return SCIP_OKAY;
assert(0 < nsubspacevars && nsubspacevars <= nvars);
for( i = 0; i < nsubspacevars; i++)
assert(fracspace[SCIPvarGetProbindex(subspacevars[i])] == i);
/* at most 2^(n-1) facets can be hit */
if( nsubspacevars < 30 )
{
/*lint --e{701}*/
assert(f_max > 0);
f_max = MIN(f_max, 1 << (nsubspacevars - 1) );
}
f_first = MIN(f_first, f_max);
/* memory allocation */
SCIP_CALL( SCIPallocBufferArray(scip, &rayorigin, nsubspacevars) );
SCIP_CALL( SCIPallocBufferArray(scip, &raydirection, nsubspacevars) );
SCIP_CALL( SCIPallocBufferArray(scip, &negquotient, nsubspacevars) );
SCIP_CALL( SCIPallocBufferArray(scip, &sign, nsubspacevars) );
SCIP_CALL( SCIPallocBufferArray(scip, &perm, nsubspacevars) );
SCIP_CALL( SCIPallocBufferArray(scip, &lambda, f_max + 1) );
SCIP_CALL( SCIPallocBufferArray(scip, &facets, f_max + 1) );
for( i = f_max; i >= 0; --i )
{
/*lint --e{866}*/
SCIP_CALL( SCIPallocBufferArray(scip, &facets[i], nsubspacevars) );
}
SCIP_CALL( SCIPallocBufferArray(scip, &first_sols, f_first) );
*result = SCIP_DIDNOTFIND;
/* starting OCTANE */
SCIPdebugMessage("run Octane heuristic on %s variables, which are %d vars, generate at most %d facets, using rule number %d\n",
usefracspace ? "fractional" : "all", nsubspacevars, f_max, (heurdata->lastrule+1)%5);
/* generate starting point in original coordinates */
SCIP_CALL( generateStartingPoint(scip, rayorigin, subspacevars, nsubspacevars) );
for( i = nsubspacevars - 1; i >= 0; --i )
rayorigin[i] -= 0.5;
firstrule = heurdata->lastrule;
++firstrule;
for( r = firstrule; r <= firstrule + 10 && !SCIPisStopped(scip); r++ )
{
SCIP_ROW** rows;
int nrows;
/* generate shooting ray in original coordinates by certain rules */
switch(r % 5)
{
case 1:
if( heurdata->useavgnbray )
{
SCIP_CALL( generateAverageNBRay(scip, raydirection, fracspace, subspacevars, nsubspacevars) );
}
break;
case 2:
if( heurdata->useobjray )
{
SCIP_CALL( generateObjectiveRay(scip, raydirection, subspacevars, nsubspacevars) );
}
break;
case 3:
if( heurdata->usediffray )
{
SCIP_CALL( generateDifferenceRay(scip, raydirection, subspacevars, nsubspacevars) );
}
break;
case 4:
if( heurdata->useavgwgtray && SCIPisLPSolBasic(scip) )
{
SCIP_CALL( generateAverageRay(scip, raydirection, subspacevars, nsubspacevars, TRUE) );
}
break;
case 0:
if( heurdata->useavgray && SCIPisLPSolBasic(scip) )
{
SCIP_CALL( generateAverageRay(scip, raydirection, subspacevars, nsubspacevars, FALSE) );
}
break;
default:
SCIPerrorMessage("invalid ray rule identifier\n");
SCIPABORT();
}
/* there must be a feasible direction for the shooting ray */
if( isZero(scip, raydirection, nsubspacevars) )
continue;
/* transform coordinates such that raydirection >= 0 */
flipCoords(rayorigin, raydirection, sign, nsubspacevars);
for( i = f_max - 1; i >= 0; --i)
lambda[i] = SCIPinfinity(scip);
/* calculate negquotient, initialize perm, facets[0], p, and q */
p = 0.5 * nsubspacevars;
q = 0.0;
for( i = nsubspacevars - 1; i >= 0; --i )
{
/* calculate negquotient, the ratio of rayorigin and raydirection, paying special attention to the case raydirection[i] == 0 */
if( SCIPisFeasZero(scip, raydirection[i]) )
{
if( rayorigin[i] < 0 )
negquotient[i] = SCIPinfinity(scip);
else
negquotient[i] = -SCIPinfinity(scip);
}
else
negquotient[i] = - (rayorigin[i] / raydirection[i]);
perm[i] = i;
/* initialization of facets[0] to the all-one facet with p and q its characteristic values */
facets[0][i] = TRUE;
p -= rayorigin[i];
q += raydirection[i];
}
assert(SCIPisPositive(scip, q));
/* resort the coordinates in nonincreasing order of negquotient */
SCIPsortDownRealRealRealBoolPtr( negquotient, raydirection, rayorigin, sign, (void**) subspacevars, nsubspacevars);
#ifndef NDEBUG
for( i = 0; i < nsubspacevars; i++ )
assert( raydirection[i] >= 0 );
for( i = 1; i < nsubspacevars; i++ )
assert( negquotient[i - 1] >= negquotient[i] );
#endif
/* finished initialization */
/* find the first facet of the octahedron hit by a ray shot from rayorigin into direction raydirection */
for( i = 0; i < nsubspacevars && negquotient[i] * q > p; ++i )
{
facets[0][i] = FALSE;
p += 2 * rayorigin[i];
q -= 2 * raydirection[i];
assert(SCIPisPositive(scip, p));
assert(SCIPisPositive(scip, q));
}
/* avoid dividing by values close to 0.0 */
if( !SCIPisFeasPositive(scip, q) )
continue;
/* assert necessary for flexelint */
assert(q > 0);
lambda[0] = p / q;
nfacets = 1;
/* find the first facets hit by the ray */
for( i = 0; i < nfacets && i < f_first; ++i)
generateNeighborFacets(scip, facets, lambda, rayorigin, raydirection, negquotient, nsubspacevars, f_max, i, &nfacets);
/* construct the first ffirst possible solutions */
for( i = 0; i < nfacets && i < f_first; ++i )
{
SCIP_CALL( SCIPcreateSol(scip, &first_sols[i], heur) );
SCIP_CALL( getSolFromFacet(scip, facets[i], first_sols[i], sign, subspacevars, nsubspacevars) );
assert( first_sols[i] != NULL );
}
/* try, whether there is a row violated by all of the first ffirst solutions */
cons_viol = FALSE;
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
for( i = nrows - 1; i >= 0; --i )
{
if( !SCIProwIsLocal(rows[i]) )
{
SCIP_COL** cols;
SCIP_Real constant;
SCIP_Real lhs;
SCIP_Real rhs;
SCIP_Real rowval;
SCIP_Real* coeffs;
int nnonzerovars;
int k;
/* get the row's data */
constant = SCIProwGetConstant(rows[i]);
lhs = SCIProwGetLhs(rows[i]);
rhs = SCIProwGetRhs(rows[i]);
coeffs = SCIProwGetVals(rows[i]);
nnonzerovars = SCIProwGetNNonz(rows[i]);
cols = SCIProwGetCols(rows[i]);
rowval = constant;
for( j = nnonzerovars - 1; j >= 0; --j )
rowval += coeffs[j] * SCIPgetSolVal(scip, first_sols[0], SCIPcolGetVar(cols[j]));
/* if the row's lhs is violated by the first sol, test, whether it is violated by the next ones, too */
if( lhs > rowval )
{
cons_viol = TRUE;
for( k = MIN(f_first, nfacets) - 1; k > 0; --k )
{
rowval = constant;
for( j = nnonzerovars - 1; j >= 0; --j )
rowval += coeffs[j] * SCIPgetSolVal(scip, first_sols[k], SCIPcolGetVar(cols[j]));
if( lhs <= rowval )
{
cons_viol = FALSE;
break;
}
}
}
/* dito for the right hand side */
else if( rhs < rowval )
{
cons_viol = TRUE;
for( k = MIN(f_first, nfacets) - 1; k > 0; --k )
{
rowval = constant;
for( j = nnonzerovars - 1; j >= 0; --j )
rowval += coeffs[j] * SCIPgetSolVal(scip, first_sols[k], SCIPcolGetVar(cols[j]));
if( rhs >= rowval )
{
cons_viol = FALSE;
break;
}
}
}
/* break as soon as one row is violated by all of the ffirst solutions */
if( cons_viol )
break;
}
}
if( !cons_viol )
{
/* if there was no row violated by all solutions, try whether one or more of them are feasible */
for( i = MIN(f_first, nfacets) - 1; i >= 0; --i )
{
assert(first_sols[i] != NULL);
SCIP_CALL( SCIPtrySol(scip, first_sols[i], FALSE, TRUE, FALSE, TRUE, &success) );
if( success )
*result = SCIP_FOUNDSOL;
}
/* search for further facets and construct and try solutions out of facets fixed as closest ones */
for( i = f_first; i < f_max; ++i)
{
if( i >= nfacets )
break;
generateNeighborFacets(scip, facets, lambda, rayorigin, raydirection, negquotient, nsubspacevars, f_max, i, &nfacets);
SCIP_CALL( getSolFromFacet(scip, facets[i], sol, sign, subspacevars, nsubspacevars) );
SCIP_CALL( SCIPtrySol(scip, sol, FALSE, TRUE, FALSE, TRUE, &success) );
if( success )
*result = SCIP_FOUNDSOL;
}
}
/* finished OCTANE */
for( i = MIN(f_first, nfacets) - 1; i >= 0; --i )
{
SCIP_CALL( SCIPfreeSol(scip, &first_sols[i]) );
}
}
heurdata->lastrule = r;
if( *result == SCIP_FOUNDSOL )
++(heurdata->nsuccess);
/* free temporary memory */
SCIPfreeBufferArray(scip, &first_sols);
for( i = f_max; i >= 0; --i )
SCIPfreeBufferArray(scip, &facets[i]);
SCIPfreeBufferArray(scip, &facets);
SCIPfreeBufferArray(scip, &lambda);
SCIPfreeBufferArray(scip, &perm);
SCIPfreeBufferArray(scip, &sign);
SCIPfreeBufferArray(scip, &negquotient);
SCIPfreeBufferArray(scip, &raydirection);
SCIPfreeBufferArray(scip, &rayorigin);
SCIPfreeBufferArray(scip, &subspacevars);
SCIPfreeBufferArray(scip, &fracspace);
return SCIP_OKAY;
}