/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpStrongcg)
{ /*lint --e{715}*/
SCIP_SEPADATA* sepadata;
SCIP_VAR** vars;
SCIP_COL** cols;
SCIP_ROW** rows;
SCIP_Real* varsolvals;
SCIP_Real* binvrow;
SCIP_Real* cutcoefs;
SCIP_Real cutrhs;
SCIP_Real cutact;
SCIP_Real maxscale;
SCIP_Longint maxdnom;
int* basisind;
int* inds;
int ninds;
int nvars;
int ncols;
int nrows;
int ncalls;
int depth;
int maxdepth;
int maxsepacuts;
int ncuts;
int c;
int i;
int cutrank;
SCIP_Bool success;
SCIP_Bool cutislocal;
char normtype;
assert(sepa != NULL);
assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
sepadata = SCIPsepaGetData(sepa);
assert(sepadata != NULL);
depth = SCIPgetDepth(scip);
ncalls = SCIPsepaGetNCallsAtNode(sepa);
/* only call separator, if we are not close to terminating */
if( SCIPisStopped(scip) )
return SCIP_OKAY;
/* only call the strong CG cut separator a given number of times at each node */
if( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot)
|| (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) )
return SCIP_OKAY;
/* only call separator, if an optimal LP solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call separator, if the LP solution is basic */
if( !SCIPisLPSolBasic(scip) )
return SCIP_OKAY;
/* only call separator, if there are fractional variables */
if( SCIPgetNLPBranchCands(scip) == 0 )
return SCIP_OKAY;
/* get variables data */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* get LP data */
SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
if( ncols == 0 || nrows == 0 )
return SCIP_OKAY;
#if 0 /* if too many columns, separator is usually very slow: delay it until no other cuts have been found */
if( ncols >= 50*nrows )
return SCIP_OKAY;
if( ncols >= 5*nrows )
{
int ncutsfound;
ncutsfound = SCIPgetNCutsFound(scip);
if( ncutsfound > sepadata->lastncutsfound || !SCIPsepaWasLPDelayed(sepa) )
{
sepadata->lastncutsfound = ncutsfound;
*result = SCIP_DELAYED;
return SCIP_OKAY;
}
}
#endif
/* get the type of norm to use for efficacy calculations */
SCIP_CALL( SCIPgetCharParam(scip, "separating/efficacynorm", &normtype) );
/* set the maximal denominator in rational representation of strong CG cut and the maximal scale factor to
* scale resulting cut to integral values to avoid numerical instabilities
*/
/**@todo find better but still stable strong CG cut settings: look at dcmulti, gesa3, khb0525, misc06, p2756 */
maxdepth = SCIPgetMaxDepth(scip);
if( depth == 0 )
{
maxdnom = 1000;
maxscale = 1000.0;
}
else if( depth <= maxdepth/4 )
{
maxdnom = 1000;
maxscale = 1000.0;
}
else if( depth <= maxdepth/2 )
{
maxdnom = 100;
maxscale = 100.0;
}
else
{
maxdnom = 10;
maxscale = 10.0;
}
*result = SCIP_DIDNOTFIND;
/* allocate temporary memory */
SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) );
SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) );
SCIP_CALL( SCIPallocBufferArray(scip, &inds, nrows) );
varsolvals = NULL; /* allocate this later, if needed */
/* get basis indices */
SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) );
/* get the maximal number of cuts allowed in a separation round */
if( depth == 0 )
maxsepacuts = sepadata->maxsepacutsroot;
else
maxsepacuts = sepadata->maxsepacuts;
SCIPdebugMessage("searching strong CG cuts: %d cols, %d rows, maxdnom=%" SCIP_LONGINT_FORMAT ", maxscale=%g, maxcuts=%d\n",
ncols, nrows, maxdnom, maxscale, maxsepacuts);
/* for all basic columns belonging to integer variables, try to generate a strong CG cut */
ncuts = 0;
for( i = 0; i < nrows && ncuts < maxsepacuts && !SCIPisStopped(scip) && *result != SCIP_CUTOFF; ++i )
{
SCIP_Bool tryrow;
tryrow = FALSE;
c = basisind[i];
if( c >= 0 )
{
SCIP_VAR* var;
assert(c < ncols);
var = SCIPcolGetVar(cols[c]);
if( SCIPvarGetType(var) != SCIP_VARTYPE_CONTINUOUS )
{
SCIP_Real primsol;
primsol = SCIPcolGetPrimsol(cols[c]);
assert(SCIPgetVarSol(scip, var) == primsol); /*lint !e777*/
if( SCIPfeasFrac(scip, primsol) >= MINFRAC )
{
SCIPdebugMessage("trying strong CG cut for col <%s> [%g]\n", SCIPvarGetName(var), primsol);
tryrow = TRUE;
}
}
}
#ifdef SEPARATEROWS
else
{
SCIP_ROW* row;
assert(0 <= -c-1 && -c-1 < nrows);
row = rows[-c-1];
if( SCIProwIsIntegral(row) && !SCIProwIsModifiable(row) )
{
SCIP_Real primsol;
primsol = SCIPgetRowActivity(scip, row);
if( SCIPfeasFrac(scip, primsol) >= MINFRAC )
{
SCIPdebugMessage("trying strong CG cut for row <%s> [%g]\n", SCIProwGetName(row), primsol);
tryrow = TRUE;
}
}
}
#endif
if( tryrow )
{
/* get the row of B^-1 for this basic integer variable with fractional solution value */
SCIP_CALL( SCIPgetLPBInvRow(scip, i, binvrow, inds, &ninds) );
#ifdef SCIP_DEBUG
/* initialize variables, that might not have been initialized in SCIPcalcMIR if success == FALSE */
cutact = 0.0;
cutrhs = SCIPinfinity(scip);
#endif
/* create a strong CG cut out of the weighted LP rows using the B^-1 row as weights */
SCIP_CALL( SCIPcalcStrongCG(scip, BOUNDSWITCH, USEVBDS, ALLOWLOCAL, (int) MAXAGGRLEN(nvars), sepadata->maxweightrange, MINFRAC, MAXFRAC,
binvrow, inds, ninds, 1.0, cutcoefs, &cutrhs, &cutact, &success, &cutislocal, &cutrank) );
assert(ALLOWLOCAL || !cutislocal);
SCIPdebugMessage(" -> success=%u: %g <= %g\n", success, cutact, cutrhs);
/* if successful, convert dense cut into sparse row, and add the row as a cut */
if( success && SCIPisFeasGT(scip, cutact, cutrhs) )
{
SCIP_VAR** cutvars;
SCIP_Real* cutvals;
SCIP_Real cutnorm;
int cutlen;
/* if this is the first successful cut, get the LP solution for all COLUMN variables */
if( varsolvals == NULL )
{
int v;
SCIP_CALL( SCIPallocBufferArray(scip, &varsolvals, nvars) );
for( v = 0; v < nvars; ++v )
{
if( SCIPvarGetStatus(vars[v]) == SCIP_VARSTATUS_COLUMN )
varsolvals[v] = SCIPvarGetLPSol(vars[v]);
}
}
assert(varsolvals != NULL);
/* get temporary memory for storing the cut as sparse row */
SCIP_CALL( SCIPallocBufferArray(scip, &cutvars, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &cutvals, nvars) );
/* store the cut as sparse row, calculate activity and norm of cut */
SCIP_CALL( storeCutInArrays(scip, nvars, vars, cutcoefs, varsolvals, normtype,
cutvars, cutvals, &cutlen, &cutact, &cutnorm) );
SCIPdebugMessage(" -> strong CG cut for <%s>: act=%f, rhs=%f, norm=%f, eff=%f, rank=%d\n",
c >= 0 ? SCIPvarGetName(SCIPcolGetVar(cols[c])) : SCIProwGetName(rows[-c-1]),
cutact, cutrhs, cutnorm, (cutact - cutrhs)/cutnorm, cutrank);
if( SCIPisPositive(scip, cutnorm) && SCIPisEfficacious(scip, (cutact - cutrhs)/cutnorm) )
{
SCIP_ROW* cut;
char cutname[SCIP_MAXSTRLEN];
/* create the cut */
if( c >= 0 )
(void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "scg%d_x%d", SCIPgetNLPs(scip), c);
else
(void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "scg%d_s%d", SCIPgetNLPs(scip), -c-1);
SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &cut, sepa, cutname, -SCIPinfinity(scip), cutrhs, cutislocal, FALSE, sepadata->dynamiccuts) );
SCIP_CALL( SCIPaddVarsToRow(scip, cut, cutlen, cutvars, cutvals) );
/*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
SCIProwChgRank(cut, cutrank);
assert(success);
#ifdef MAKECUTINTEGRAL
/* try to scale the cut to integral values */
SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip),
maxdnom, maxscale, MAKECONTINTEGRAL, &success) );
#else
#ifdef MAKEINTCUTINTEGRAL
/* try to scale the cut to integral values if there are no continuous variables
* -> leads to an integral slack variable that can later be used for other cuts
*/
{
int k = 0;
while ( k < cutlen && SCIPvarIsIntegral(cutvars[k]) )
++k;
if( k == cutlen )
{
SCIP_CALL( SCIPmakeRowIntegral(scip, cut, -SCIPepsilon(scip), SCIPsumepsilon(scip),
maxdnom, maxscale, MAKECONTINTEGRAL, &success) );
}
}
#endif
#endif
#ifndef FORCECUTINTEGRAL
success = TRUE;
#endif
if( success )
{
if( !SCIPisCutEfficacious(scip, NULL, cut) )
{
SCIPdebugMessage(" -> strong CG cut <%s> no longer efficacious: act=%f, rhs=%f, norm=%f, eff=%f\n",
cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
SCIPgetCutEfficacy(scip, NULL, cut));
/*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
success = FALSE;
}
else
{
SCIP_Bool infeasible;
SCIPdebugMessage(" -> found strong CG cut <%s>: act=%f, rhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n",
cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
SCIPgetCutEfficacy(scip, NULL, cut),
SCIPgetRowMinCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut),
SCIPgetRowMaxCoef(scip, cut)/SCIPgetRowMinCoef(scip, cut));
/*SCIPdebug( SCIP_CALL(SCIPprintRow(scip, cut, NULL)) );*/
SCIP_CALL( SCIPaddCut(scip, NULL, cut, FALSE, &infeasible) );
if ( infeasible )
*result = SCIP_CUTOFF;
else
{
if( !cutislocal )
{
SCIP_CALL( SCIPaddPoolCut(scip, cut) );
}
*result = SCIP_SEPARATED;
}
ncuts++;
}
}
else
{
SCIPdebugMessage(" -> strong CG cut <%s> couldn't be scaled to integral coefficients: act=%f, rhs=%f, norm=%f, eff=%f\n",
cutname, cutact, cutrhs, cutnorm, SCIPgetCutEfficacy(scip, NULL, cut));
}
/* release the row */
SCIP_CALL( SCIPreleaseRow(scip, &cut) );
}
/* free temporary memory */
SCIPfreeBufferArray(scip, &cutvals);
SCIPfreeBufferArray(scip, &cutvars);
}
}
}
/* free temporary memory */
SCIPfreeBufferArrayNull(scip, &varsolvals);
SCIPfreeBufferArray(scip, &inds);
SCIPfreeBufferArray(scip, &binvrow);
SCIPfreeBufferArray(scip, &basisind);
SCIPfreeBufferArray(scip, &cutcoefs);
SCIPdebugMessage("end searching strong CG cuts: found %d cuts\n", ncuts);
sepadata->lastncutsfound = SCIPgetNCutsFound(scip);
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecShifting) /*lint --e{715}*/
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_SOL* sol;
SCIP_VAR** lpcands;
SCIP_Real* lpcandssol;
SCIP_ROW** lprows;
SCIP_Real* activities;
SCIP_ROW** violrows;
SCIP_Real* nincreases;
SCIP_Real* ndecreases;
int* violrowpos;
int* nfracsinrow;
SCIP_Real increaseweight;
SCIP_Real obj;
SCIP_Real bestshiftval;
SCIP_Real minobj;
int nlpcands;
int nlprows;
int nvars;
int nfrac;
int nviolrows;
int nprevviolrows;
int minnviolrows;
int nnonimprovingshifts;
int c;
int r;
SCIP_Longint nlps;
SCIP_Longint ncalls;
SCIP_Longint nsolsfound;
SCIP_Longint nnodes;
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
assert(SCIPhasCurrentNodeLP(scip));
*result = SCIP_DIDNOTRUN;
/* only call heuristic, if an optimal LP solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call heuristic, if the LP objective value is smaller than the cutoff bound */
if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
return SCIP_OKAY;
/* get heuristic data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* don't call heuristic, if we have already processed the current LP solution */
nlps = SCIPgetNLPs(scip);
if( nlps == heurdata->lastlp )
return SCIP_OKAY;
heurdata->lastlp = nlps;
/* don't call heuristic, if it was not successful enough in the past */
ncalls = SCIPheurGetNCalls(heur);
nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + SCIPheurGetNSolsFound(heur);
nnodes = SCIPgetNNodes(scip);
if( nnodes % ((ncalls/100)/(nsolsfound+1)+1) != 0 )
return SCIP_OKAY;
/* get fractional variables, that should be integral */
/* todo check if heuristic should include implicit integer variables for its calculations */
SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, NULL) );
nfrac = nlpcands;
/* only call heuristic, if LP solution is fractional */
if( nfrac == 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
/* get LP rows */
SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );
SCIPdebugMessage("executing shifting heuristic: %d LP rows, %d fractionals\n", nlprows, nfrac);
/* get memory for activities, violated rows, and row violation positions */
nvars = SCIPgetNVars(scip);
SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &violrows, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &violrowpos, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &nfracsinrow, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &nincreases, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &ndecreases, nvars) );
BMSclearMemoryArray(nfracsinrow, nlprows);
BMSclearMemoryArray(nincreases, nvars);
BMSclearMemoryArray(ndecreases, nvars);
/* get the activities for all globally valid rows;
* the rows should be feasible, but due to numerical inaccuracies in the LP solver, they can be violated
*/
nviolrows = 0;
for( r = 0; r < nlprows; ++r )
{
SCIP_ROW* row;
row = lprows[r];
assert(SCIProwGetLPPos(row) == r);
if( !SCIProwIsLocal(row) )
{
activities[r] = SCIPgetRowActivity(scip, row);
if( SCIPisFeasLT(scip, activities[r], SCIProwGetLhs(row))
|| SCIPisFeasGT(scip, activities[r], SCIProwGetRhs(row)) )
{
violrows[nviolrows] = row;
violrowpos[r] = nviolrows;
nviolrows++;
}
else
violrowpos[r] = -1;
}
}
/* calc the current number of fractional variables in rows */
for( c = 0; c < nlpcands; ++c )
addFracCounter(nfracsinrow, nlprows, lpcands[c], +1);
/* get the working solution from heuristic's local data */
sol = heurdata->sol;
assert(sol != NULL);
/* copy the current LP solution to the working solution */
SCIP_CALL( SCIPlinkLPSol(scip, sol) );
/* calculate the minimal objective value possible after rounding fractional variables */
minobj = SCIPgetSolTransObj(scip, sol);
assert(minobj < SCIPgetCutoffbound(scip));
for( c = 0; c < nlpcands; ++c )
{
obj = SCIPvarGetObj(lpcands[c]);
bestshiftval = obj > 0.0 ? SCIPfeasFloor(scip, lpcandssol[c]) : SCIPfeasCeil(scip, lpcandssol[c]);
minobj += obj * (bestshiftval - lpcandssol[c]);
}
/* try to shift remaining variables in order to become/stay feasible */
nnonimprovingshifts = 0;
minnviolrows = INT_MAX;
increaseweight = 1.0;
while( (nfrac > 0 || nviolrows > 0) && nnonimprovingshifts < MAXSHIFTINGS )
{
SCIP_VAR* shiftvar;
SCIP_Real oldsolval;
SCIP_Real newsolval;
SCIP_Bool oldsolvalisfrac;
int probindex;
SCIPdebugMessage("shifting heuristic: nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g), cutoff=%g\n",
nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj),
SCIPretransformObj(scip, SCIPgetCutoffbound(scip)));
nprevviolrows = nviolrows;
/* choose next variable to process:
* - if a violated row exists, shift a variable decreasing the violation, that has least impact on other rows
* - otherwise, shift a variable, that has strongest devastating impact on rows in opposite direction
*/
shiftvar = NULL;
oldsolval = 0.0;
newsolval = 0.0;
if( nviolrows > 0 && (nfrac == 0 || nnonimprovingshifts < MAXSHIFTINGS-1) )
{
SCIP_ROW* row;
int rowidx;
int rowpos;
int direction;
rowidx = -1;
rowpos = -1;
row = NULL;
if( nfrac > 0 )
{
for( rowidx = nviolrows-1; rowidx >= 0; --rowidx )
{
row = violrows[rowidx];
rowpos = SCIProwGetLPPos(row);
assert(violrowpos[rowpos] == rowidx);
if( nfracsinrow[rowpos] > 0 )
break;
}
}
if( rowidx == -1 )
{
rowidx = SCIPgetRandomInt(0, nviolrows-1, &heurdata->randseed);
row = violrows[rowidx];
rowpos = SCIProwGetLPPos(row);
assert(0 <= rowpos && rowpos < nlprows);
assert(violrowpos[rowpos] == rowidx);
assert(nfracsinrow[rowpos] == 0);
}
assert(violrowpos[rowpos] == rowidx);
SCIPdebugMessage("shifting heuristic: try to fix violated row <%s>: %g <= %g <= %g\n",
SCIProwGetName(row), SCIProwGetLhs(row), activities[rowpos], SCIProwGetRhs(row));
SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );
/* get direction in which activity must be shifted */
assert(SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row))
|| SCIPisFeasGT(scip, activities[rowpos], SCIProwGetRhs(row)));
direction = SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row)) ? +1 : -1;
/* search a variable that can shift the activity in the necessary direction */
SCIP_CALL( selectShifting(scip, sol, row, activities[rowpos], direction,
nincreases, ndecreases, increaseweight, &shiftvar, &oldsolval, &newsolval) );
}
if( shiftvar == NULL && nfrac > 0 )
{
SCIPdebugMessage("shifting heuristic: search rounding variable and try to stay feasible\n");
SCIP_CALL( selectEssentialRounding(scip, sol, minobj, lpcands, nlpcands, &shiftvar, &oldsolval, &newsolval) );
}
/* check, whether shifting was possible */
if( shiftvar == NULL || SCIPisEQ(scip, oldsolval, newsolval) )
{
SCIPdebugMessage("shifting heuristic: -> didn't find a shifting variable\n");
break;
}
SCIPdebugMessage("shifting heuristic: -> shift var <%s>[%g,%g], type=%d, oldval=%g, newval=%g, obj=%g\n",
SCIPvarGetName(shiftvar), SCIPvarGetLbGlobal(shiftvar), SCIPvarGetUbGlobal(shiftvar), SCIPvarGetType(shiftvar),
oldsolval, newsolval, SCIPvarGetObj(shiftvar));
/* update row activities of globally valid rows */
SCIP_CALL( updateActivities(scip, activities, violrows, violrowpos, &nviolrows, nlprows,
shiftvar, oldsolval, newsolval) );
if( nviolrows >= nprevviolrows )
nnonimprovingshifts++;
else if( nviolrows < minnviolrows )
{
minnviolrows = nviolrows;
nnonimprovingshifts = 0;
}
/* store new solution value and decrease fractionality counter */
SCIP_CALL( SCIPsetSolVal(scip, sol, shiftvar, newsolval) );
/* update fractionality counter and minimal objective value possible after shifting remaining variables */
oldsolvalisfrac = !SCIPisFeasIntegral(scip, oldsolval)
&& (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER);
obj = SCIPvarGetObj(shiftvar);
if( (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER)
&& oldsolvalisfrac )
{
assert(SCIPisFeasIntegral(scip, newsolval));
nfrac--;
nnonimprovingshifts = 0;
minnviolrows = INT_MAX;
addFracCounter(nfracsinrow, nlprows, shiftvar, -1);
/* the rounding was already calculated into the minobj -> update only if rounding in "wrong" direction */
if( obj > 0.0 && newsolval > oldsolval )
minobj += obj;
else if( obj < 0.0 && newsolval < oldsolval )
minobj -= obj;
}
else
{
/* update minimal possible objective value */
minobj += obj * (newsolval - oldsolval);
}
/* update increase/decrease arrays */
if( !oldsolvalisfrac )
{
probindex = SCIPvarGetProbindex(shiftvar);
assert(0 <= probindex && probindex < nvars);
increaseweight *= WEIGHTFACTOR;
if( newsolval < oldsolval )
ndecreases[probindex] += increaseweight;
else
nincreases[probindex] += increaseweight;
if( increaseweight >= 1e+09 )
{
int i;
for( i = 0; i < nvars; ++i )
{
nincreases[i] /= increaseweight;
ndecreases[i] /= increaseweight;
}
increaseweight = 1.0;
}
}
SCIPdebugMessage("shifting heuristic: -> nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n",
nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj));
}
/* check, if the new solution is feasible */
if( nfrac == 0 && nviolrows == 0 )
{
SCIP_Bool stored;
/* check solution for feasibility, and add it to solution store if possible
* neither integrality nor feasibility of LP rows has to be checked, because this is already
* done in the shifting heuristic itself; however, we better check feasibility of LP rows,
* because of numerical problems with activity updating
*/
SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, FALSE, TRUE, &stored) );
if( stored )
{
SCIPdebugMessage("found feasible shifted solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) ) );
*result = SCIP_FOUNDSOL;
}
}
/* free memory buffers */
SCIPfreeBufferArray(scip, &ndecreases);
SCIPfreeBufferArray(scip, &nincreases);
SCIPfreeBufferArray(scip, &nfracsinrow);
SCIPfreeBufferArray(scip, &violrowpos);
SCIPfreeBufferArray(scip, &violrows);
SCIPfreeBufferArray(scip, &activities);
return SCIP_OKAY;
}
/** returns a variable, that pushes activity of the row in the given direction with minimal negative impact on other rows;
* if variables have equal impact, chooses the one with best objective value improvement in corresponding direction;
* prefer fractional integers over other variables in order to become integral during the process;
* shifting in a direction is forbidden, if this forces the objective value over the upper bound, or if the variable
* was already shifted in the opposite direction
*/
static
SCIP_RETCODE selectShifting(
SCIP* scip, /**< SCIP data structure */
SCIP_SOL* sol, /**< primal solution */
SCIP_ROW* row, /**< LP row */
SCIP_Real rowactivity, /**< activity of LP row */
int direction, /**< should the activity be increased (+1) or decreased (-1)? */
SCIP_Real* nincreases, /**< array with weighted number of increasings per variables */
SCIP_Real* ndecreases, /**< array with weighted number of decreasings per variables */
SCIP_Real increaseweight, /**< current weight of increase/decrease updates */
SCIP_VAR** shiftvar, /**< pointer to store the shifting variable, returns NULL if impossible */
SCIP_Real* oldsolval, /**< pointer to store old solution value of shifting variable */
SCIP_Real* newsolval /**< pointer to store new (shifted) solution value of shifting variable */
)
{
SCIP_COL** rowcols;
SCIP_Real* rowvals;
int nrowcols;
SCIP_Real activitydelta;
SCIP_Real bestshiftscore;
SCIP_Real bestdeltaobj;
int c;
assert(direction == +1 || direction == -1);
assert(nincreases != NULL);
assert(ndecreases != NULL);
assert(shiftvar != NULL);
assert(oldsolval != NULL);
assert(newsolval != NULL);
/* get row entries */
rowcols = SCIProwGetCols(row);
rowvals = SCIProwGetVals(row);
nrowcols = SCIProwGetNLPNonz(row);
/* calculate how much the activity must be shifted in order to become feasible */
activitydelta = (direction == +1 ? SCIProwGetLhs(row) - rowactivity : SCIProwGetRhs(row) - rowactivity);
assert((direction == +1 && SCIPisPositive(scip, activitydelta))
|| (direction == -1 && SCIPisNegative(scip, activitydelta)));
/* select shifting variable */
bestshiftscore = SCIP_REAL_MAX;
bestdeltaobj = SCIPinfinity(scip);
*shiftvar = NULL;
*newsolval = 0.0;
*oldsolval = 0.0;
for( c = 0; c < nrowcols; ++c )
{
SCIP_COL* col;
SCIP_VAR* var;
SCIP_Real val;
SCIP_Real solval;
SCIP_Real shiftval;
SCIP_Real shiftscore;
SCIP_Bool isinteger;
SCIP_Bool isfrac;
SCIP_Bool increase;
col = rowcols[c];
var = SCIPcolGetVar(col);
val = rowvals[c];
assert(!SCIPisZero(scip, val));
solval = SCIPgetSolVal(scip, sol, var);
isinteger = (SCIPvarGetType(var) == SCIP_VARTYPE_BINARY || SCIPvarGetType(var) == SCIP_VARTYPE_INTEGER);
isfrac = isinteger && !SCIPisFeasIntegral(scip, solval);
increase = (direction * val > 0.0);
/* calculate the score of the shifting (prefer smaller values) */
if( isfrac )
shiftscore = increase ? -1.0 / (SCIPvarGetNLocksUp(var) + 1.0) :
-1.0 / (SCIPvarGetNLocksDown(var) + 1.0);
else
{
int probindex;
probindex = SCIPvarGetProbindex(var);
if( increase )
shiftscore = ndecreases[probindex]/increaseweight;
else
shiftscore = nincreases[probindex]/increaseweight;
if( isinteger )
shiftscore += 1.0;
}
if( shiftscore <= bestshiftscore )
{
SCIP_Real deltaobj;
if( !increase )
{
/* shifting down */
assert(direction * val < 0.0);
if( isfrac )
shiftval = SCIPfeasFloor(scip, solval);
else
{
SCIP_Real lb;
assert(activitydelta/val < 0.0);
shiftval = solval + activitydelta/val;
assert(shiftval <= solval); /* may be equal due to numerical digit erasement in the subtraction */
if( SCIPvarIsIntegral(var) )
shiftval = SCIPfeasFloor(scip, shiftval);
lb = SCIPvarGetLbGlobal(var);
shiftval = MAX(shiftval, lb);
}
}
else
{
/* shifting up */
assert(direction * val > 0.0);
if( isfrac )
shiftval = SCIPfeasCeil(scip, solval);
else
{
SCIP_Real ub;
assert(activitydelta/val > 0.0);
shiftval = solval + activitydelta/val;
assert(shiftval >= solval); /* may be equal due to numerical digit erasement in the subtraction */
if( SCIPvarIsIntegral(var) )
shiftval = SCIPfeasCeil(scip, shiftval);
ub = SCIPvarGetUbGlobal(var);
shiftval = MIN(shiftval, ub);
}
}
if( SCIPisEQ(scip, shiftval, solval) )
continue;
deltaobj = SCIPvarGetObj(var) * (shiftval - solval);
if( shiftscore < bestshiftscore || deltaobj < bestdeltaobj )
{
bestshiftscore = shiftscore;
bestdeltaobj = deltaobj;
*shiftvar = var;
*oldsolval = solval;
*newsolval = shiftval;
}
}
}
return SCIP_OKAY;
}
/** checks whether given row is valid for the debugging solution */
SCIP_RETCODE SCIPdebugCheckRow(
SCIP_SET* set, /**< global SCIP settings */
SCIP_ROW* row /**< row to check for validity */
)
{
SCIP_COL** cols;
SCIP_Real* vals;
SCIP_Real lhs;
SCIP_Real rhs;
int nnonz;
int i;
SCIP_Real minactivity;
SCIP_Real maxactivity;
SCIP_Real solval;
assert(set != NULL);
assert(row != NULL);
/* check if we are in the original problem and not in a sub MIP */
if( !isSolutionInMip(set) )
return SCIP_OKAY;
/* check if the incumbent solution is at least as good as the debug solution, so we can stop to check the debug solution */
if( debugSolIsAchieved(set) )
return SCIP_OKAY;
/* if the row is only locally valid, check whether the debugging solution is contained in the local subproblem */
if( SCIProwIsLocal(row) )
{
SCIP_Bool solcontained;
SCIP_CALL( isSolutionInNode(SCIPblkmem(set->scip), set, SCIPgetCurrentNode(set->scip), &solcontained) );
if( !solcontained )
return SCIP_OKAY;
}
cols = SCIProwGetCols(row);
vals = SCIProwGetVals(row);
nnonz = SCIProwGetNNonz(row);
lhs = SCIProwGetLhs(row);
rhs = SCIProwGetRhs(row);
/* calculate row's activity on debugging solution */
minactivity = SCIProwGetConstant(row);
maxactivity = minactivity;
for( i = 0; i < nnonz; ++i )
{
SCIP_VAR* var;
/* get solution value of variable in debugging solution */
var = SCIPcolGetVar(cols[i]);
SCIP_CALL( getSolutionValue(set, var, &solval) );
if( solval != SCIP_UNKNOWN ) /*lint !e777*/
{
minactivity += vals[i] * solval;
maxactivity += vals[i] * solval;
}
else if( vals[i] > 0.0 )
{
minactivity += vals[i] * SCIPvarGetLbGlobal(var);
maxactivity += vals[i] * SCIPvarGetUbGlobal(var);
}
else if( vals[i] < 0.0 )
{
minactivity += vals[i] * SCIPvarGetUbGlobal(var);
maxactivity += vals[i] * SCIPvarGetLbGlobal(var);
}
}
SCIPdebugMessage("debugging solution on row <%s>: %g <= [%g,%g] <= %g\n",
SCIProwGetName(row), lhs, minactivity, maxactivity, rhs);
/* check row for violation */
if( SCIPsetIsFeasLT(set, maxactivity, lhs) || SCIPsetIsFeasGT(set, minactivity, rhs) )
{
printf("***** debug: row <%s> violates debugging solution (lhs=%.15g, rhs=%.15g, activity=[%.15g,%.15g], local=%d)\n",
SCIProwGetName(row), lhs, rhs, minactivity, maxactivity, SCIProwIsLocal(row));
SCIProwPrint(row, NULL);
/* output row with solution values */
printf("\n\n");
printf("***** debug: violated row <%s>:\n", SCIProwGetName(row));
printf(" %.15g <= %.15g", lhs, SCIProwGetConstant(row));
for( i = 0; i < nnonz; ++i )
{
/* get solution value of variable in debugging solution */
SCIP_CALL( getSolutionValue(set, SCIPcolGetVar(cols[i]), &solval) );
printf(" %+.15g<%s>[%.15g]", vals[i], SCIPvarGetName(SCIPcolGetVar(cols[i])), solval);
}
printf(" <= %.15g\n", rhs);
SCIPABORT();
}
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecRounding) /*lint --e{715}*/
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_SOL* sol;
SCIP_VAR** lpcands;
SCIP_Real* lpcandssol;
SCIP_ROW** lprows;
SCIP_Real* activities;
SCIP_ROW** violrows;
int* violrowpos;
SCIP_Real obj;
SCIP_Real bestroundval;
SCIP_Real minobj;
int nlpcands;
int nlprows;
int nfrac;
int nviolrows;
int c;
int r;
SCIP_Longint nlps;
SCIP_Longint ncalls;
SCIP_Longint nsolsfound;
SCIP_Longint nnodes;
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
assert(SCIPhasCurrentNodeLP(scip));
*result = SCIP_DIDNOTRUN;
/* only call heuristic, if an optimal LP solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call heuristic, if the LP objective value is smaller than the cutoff bound */
if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
return SCIP_OKAY;
/* get heuristic data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* don't call heuristic, if we have already processed the current LP solution */
nlps = SCIPgetNLPs(scip);
if( nlps == heurdata->lastlp )
return SCIP_OKAY;
heurdata->lastlp = nlps;
/* don't call heuristic, if it was not successful enough in the past */
ncalls = SCIPheurGetNCalls(heur);
nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + SCIPheurGetNSolsFound(heur);
nnodes = SCIPgetNNodes(scip);
if( nnodes % ((ncalls/heurdata->successfactor)/(nsolsfound+1)+1) != 0 )
return SCIP_OKAY;
/* get fractional variables, that should be integral */
SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, NULL) );
nfrac = nlpcands;
/* only call heuristic, if LP solution is fractional */
if( nfrac == 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
/* get LP rows */
SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );
SCIPdebugMessage("executing rounding heuristic: %d LP rows, %d fractionals\n", nlprows, nfrac);
/* get memory for activities, violated rows, and row violation positions */
SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &violrows, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &violrowpos, nlprows) );
/* get the activities for all globally valid rows;
* the rows should be feasible, but due to numerical inaccuracies in the LP solver, they can be violated
*/
nviolrows = 0;
for( r = 0; r < nlprows; ++r )
{
SCIP_ROW* row;
row = lprows[r];
assert(SCIProwGetLPPos(row) == r);
if( !SCIProwIsLocal(row) )
{
activities[r] = SCIPgetRowActivity(scip, row);
if( SCIPisFeasLT(scip, activities[r], SCIProwGetLhs(row))
|| SCIPisFeasGT(scip, activities[r], SCIProwGetRhs(row)) )
{
violrows[nviolrows] = row;
violrowpos[r] = nviolrows;
nviolrows++;
}
else
violrowpos[r] = -1;
}
}
/* get the working solution from heuristic's local data */
sol = heurdata->sol;
assert(sol != NULL);
/* copy the current LP solution to the working solution */
SCIP_CALL( SCIPlinkLPSol(scip, sol) );
/* calculate the minimal objective value possible after rounding fractional variables */
minobj = SCIPgetSolTransObj(scip, sol);
assert(minobj < SCIPgetCutoffbound(scip));
for( c = 0; c < nlpcands; ++c )
{
obj = SCIPvarGetObj(lpcands[c]);
bestroundval = obj > 0.0 ? SCIPfeasFloor(scip, lpcandssol[c]) : SCIPfeasCeil(scip, lpcandssol[c]);
minobj += obj * (bestroundval - lpcandssol[c]);
}
/* try to round remaining variables in order to become/stay feasible */
while( nfrac > 0 )
{
SCIP_VAR* roundvar;
SCIP_Real oldsolval;
SCIP_Real newsolval;
SCIPdebugMessage("rounding heuristic: nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n",
nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj));
/* minobj < SCIPgetCutoffbound(scip) should be true, otherwise the rounding variable selection
* should have returned NULL. Due to possible cancellation we use SCIPisLE. */
assert( SCIPisLE(scip, minobj, SCIPgetCutoffbound(scip)) );
/* choose next variable to process:
* - if a violated row exists, round a variable decreasing the violation, that has least impact on other rows
* - otherwise, round a variable, that has strongest devastating impact on rows in opposite direction
*/
if( nviolrows > 0 )
{
SCIP_ROW* row;
int rowpos;
row = violrows[nviolrows-1];
rowpos = SCIProwGetLPPos(row);
assert(0 <= rowpos && rowpos < nlprows);
assert(violrowpos[rowpos] == nviolrows-1);
SCIPdebugMessage("rounding heuristic: try to fix violated row <%s>: %g <= %g <= %g\n",
SCIProwGetName(row), SCIProwGetLhs(row), activities[rowpos], SCIProwGetRhs(row));
if( SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row)) )
{
/* lhs is violated: select a variable rounding, that increases the activity */
SCIP_CALL( selectIncreaseRounding(scip, sol, minobj, row, &roundvar, &oldsolval, &newsolval) );
}
else
{
assert(SCIPisFeasGT(scip, activities[rowpos], SCIProwGetRhs(row)));
/* rhs is violated: select a variable rounding, that decreases the activity */
SCIP_CALL( selectDecreaseRounding(scip, sol, minobj, row, &roundvar, &oldsolval, &newsolval) );
}
}
else
{
SCIPdebugMessage("rounding heuristic: search rounding variable and try to stay feasible\n");
SCIP_CALL( selectEssentialRounding(scip, sol, minobj, lpcands, nlpcands, &roundvar, &oldsolval, &newsolval) );
}
/* check, whether rounding was possible */
if( roundvar == NULL )
{
SCIPdebugMessage("rounding heuristic: -> didn't find a rounding variable\n");
break;
}
SCIPdebugMessage("rounding heuristic: -> round var <%s>, oldval=%g, newval=%g, obj=%g\n",
SCIPvarGetName(roundvar), oldsolval, newsolval, SCIPvarGetObj(roundvar));
/* update row activities of globally valid rows */
SCIP_CALL( updateActivities(scip, activities, violrows, violrowpos, &nviolrows, nlprows,
roundvar, oldsolval, newsolval) );
/* store new solution value and decrease fractionality counter */
SCIP_CALL( SCIPsetSolVal(scip, sol, roundvar, newsolval) );
nfrac--;
/* update minimal objective value possible after rounding remaining variables */
obj = SCIPvarGetObj(roundvar);
if( obj > 0.0 && newsolval > oldsolval )
minobj += obj;
else if( obj < 0.0 && newsolval < oldsolval )
minobj -= obj;
SCIPdebugMessage("rounding heuristic: -> nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n",
nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj));
}
/* check, if the new solution is feasible */
if( nfrac == 0 && nviolrows == 0 )
{
SCIP_Bool stored;
/* check solution for feasibility, and add it to solution store if possible
* neither integrality nor feasibility of LP rows has to be checked, because this is already
* done in the rounding heuristic itself; however, be better check feasibility of LP rows,
* because of numerical problems with activity updating
*/
SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, FALSE, TRUE, &stored) );
if( stored )
{
#ifdef SCIP_DEBUG
SCIPdebugMessage("found feasible rounded solution:\n");
SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) );
#endif
*result = SCIP_FOUNDSOL;
}
}
/* free memory buffers */
SCIPfreeBufferArray(scip, &violrowpos);
SCIPfreeBufferArray(scip, &violrows);
SCIPfreeBufferArray(scip, &activities);
return SCIP_OKAY;
}
/** 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;
}
