/** creates the rows of the subproblem */
static
SCIP_RETCODE createRows(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP data structure for the subproblem */
SCIP_VAR** subvars /**< the variables of the subproblem */
)
{
SCIP_ROW** rows; /* original scip rows */
SCIP_CONS* cons; /* new constraint */
SCIP_VAR** consvars; /* new constraint's variables */
SCIP_COL** cols; /* original row's columns */
SCIP_Real constant; /* constant added to the row */
SCIP_Real lhs; /* left hand side of the row */
SCIP_Real rhs; /* left right side of the row */
SCIP_Real* vals; /* variables' coefficient values of the row */
int nrows;
int nnonz;
int i;
int j;
/* get the rows and their number */
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
/* copy all rows to linear constraints */
for( i = 0; i < nrows; i++ )
{
/* 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);
}
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(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 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;
}
/** 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;
}
/** LP solution separation method for disjunctive cuts */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpDisjunctive)
{
SCIP_SEPADATA* sepadata;
SCIP_CONSHDLR* conshdlr;
SCIP_DIGRAPH* conflictgraph;
SCIP_ROW** rows;
SCIP_COL** cols;
SCIP_Real* cutcoefs = NULL;
SCIP_Real* simplexcoefs1 = NULL;
SCIP_Real* simplexcoefs2 = NULL;
SCIP_Real* coef = NULL;
SCIP_Real* binvrow = NULL;
SCIP_Real* rowsmaxval = NULL;
SCIP_Real* violationarray = NULL;
int* fixings1 = NULL;
int* fixings2 = NULL;
int* basisind = NULL;
int* basisrow = NULL;
int* varrank = NULL;
int* edgearray = NULL;
int nedges;
int ndisjcuts;
int nrelevantedges;
int nsos1vars;
int nconss;
int maxcuts;
int ncalls;
int depth;
int ncols;
int nrows;
int ind;
int j;
int i;
assert( sepa != NULL );
assert( strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0 );
assert( scip != NULL );
assert( result != NULL );
*result = SCIP_DIDNOTRUN;
/* only generate disjunctive cuts if we are not close to terminating */
if ( SCIPisStopped(scip) )
return SCIP_OKAY;
/* only generate disjunctive cuts if an optimal LP solution is at hand */
if ( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only generate disjunctive cuts if the LP solution is basic */
if ( ! SCIPisLPSolBasic(scip) )
return SCIP_OKAY;
/* get LP data */
SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
/* return if LP has no columns or no rows */
if ( ncols == 0 || nrows == 0 )
return SCIP_OKAY;
assert( cols != NULL );
assert( rows != NULL );
/* get sepa data */
sepadata = SCIPsepaGetData(sepa);
assert( sepadata != NULL );
/* get constraint handler */
conshdlr = sepadata->conshdlr;
if ( conshdlr == NULL )
return SCIP_OKAY;
/* get number of constraints */
nconss = SCIPconshdlrGetNConss(conshdlr);
if ( nconss == 0 )
return SCIP_OKAY;
/* check for maxdepth < depth, maxinvcutsroot = 0 and maxinvcuts = 0 */
depth = SCIPgetDepth(scip);
if ( ( sepadata->maxdepth >= 0 && sepadata->maxdepth < depth )
|| ( depth == 0 && sepadata->maxinvcutsroot == 0 )
|| ( depth > 0 && sepadata->maxinvcuts == 0 ) )
return SCIP_OKAY;
/* only call the cut separator a given number of times at each node */
ncalls = SCIPsepaGetNCallsAtNode(sepa);
if ( (depth == 0 && sepadata->maxroundsroot >= 0 && ncalls >= sepadata->maxroundsroot)
|| (depth > 0 && sepadata->maxrounds >= 0 && ncalls >= sepadata->maxrounds) )
return SCIP_OKAY;
/* get conflict graph and number of conflict graph edges (note that the digraph arcs were added in both directions) */
conflictgraph = SCIPgetConflictgraphSOS1(conshdlr);
nedges = (int)SCIPceil(scip, (SCIP_Real)SCIPdigraphGetNArcs(conflictgraph)/2);
/* if too many conflict graph edges, the separator can be slow: delay it until no other cuts have been found */
if ( sepadata->maxconfsdelay >= 0 && nedges >= sepadata->maxconfsdelay )
{
int ncutsfound;
ncutsfound = SCIPgetNCutsFound(scip);
if ( ncutsfound > sepadata->lastncutsfound || ! SCIPsepaWasLPDelayed(sepa) )
{
sepadata->lastncutsfound = ncutsfound;
*result = SCIP_DELAYED;
return SCIP_OKAY;
}
}
/* check basis status */
for (j = 0; j < ncols; ++j)
{
if ( SCIPcolGetBasisStatus(cols[j]) == SCIP_BASESTAT_ZERO )
return SCIP_OKAY;
}
/* get number of SOS1 variables */
nsos1vars = SCIPgetNSOS1Vars(conshdlr);
/* allocate buffer arrays */
SCIP_CALL( SCIPallocBufferArray(scip, &edgearray, nedges) );
SCIP_CALL( SCIPallocBufferArray(scip, &fixings1, nedges) );
SCIP_CALL( SCIPallocBufferArray(scip, &fixings2, nedges) );
SCIP_CALL( SCIPallocBufferArray(scip, &violationarray, nedges) );
/* get all violated conflicts {i, j} in the conflict graph and sort them based on the degree of a violation value */
nrelevantedges = 0;
for (j = 0; j < nsos1vars; ++j)
{
SCIP_VAR* var;
var = SCIPnodeGetVarSOS1(conflictgraph, j);
if ( SCIPvarIsActive(var) && ! SCIPisFeasZero(scip, SCIPcolGetPrimsol(SCIPvarGetCol(var))) && SCIPcolGetBasisStatus(SCIPvarGetCol(var)) == SCIP_BASESTAT_BASIC )
{
int* succ;
int nsucc;
/* get successors and number of successors */
nsucc = SCIPdigraphGetNSuccessors(conflictgraph, j);
succ = SCIPdigraphGetSuccessors(conflictgraph, j);
for (i = 0; i < nsucc; ++i)
{
SCIP_VAR* varsucc;
int succind;
succind = succ[i];
varsucc = SCIPnodeGetVarSOS1(conflictgraph, succind);
if ( SCIPvarIsActive(varsucc) && succind < j && ! SCIPisFeasZero(scip, SCIPgetSolVal(scip, NULL, varsucc) ) &&
SCIPcolGetBasisStatus(SCIPvarGetCol(varsucc)) == SCIP_BASESTAT_BASIC )
{
fixings1[nrelevantedges] = j;
fixings2[nrelevantedges] = succind;
edgearray[nrelevantedges] = nrelevantedges;
violationarray[nrelevantedges++] = SCIPgetSolVal(scip, NULL, var) * SCIPgetSolVal(scip, NULL, varsucc);
}
}
}
}
/* sort violation score values */
if ( nrelevantedges > 0)
SCIPsortDownRealInt(violationarray, edgearray, nrelevantedges);
else
{
SCIPfreeBufferArrayNull(scip, &violationarray);
SCIPfreeBufferArrayNull(scip, &fixings2);
SCIPfreeBufferArrayNull(scip, &fixings1);
SCIPfreeBufferArrayNull(scip, &edgearray);
return SCIP_OKAY;
}
SCIPfreeBufferArrayNull(scip, &violationarray);
/* compute maximal number of cuts */
if ( SCIPgetDepth(scip) == 0 )
maxcuts = MIN(sepadata->maxinvcutsroot, nrelevantedges);
else
maxcuts = MIN(sepadata->maxinvcuts, nrelevantedges);
assert( maxcuts > 0 );
/* allocate buffer arrays */
SCIP_CALL( SCIPallocBufferArray(scip, &varrank, ncols) );
SCIP_CALL( SCIPallocBufferArray(scip, &rowsmaxval, nrows) );
SCIP_CALL( SCIPallocBufferArray(scip, &basisrow, ncols) );
SCIP_CALL( SCIPallocBufferArray(scip, &binvrow, nrows) );
SCIP_CALL( SCIPallocBufferArray(scip, &coef, ncols) );
SCIP_CALL( SCIPallocBufferArray(scip, &simplexcoefs1, ncols) );
SCIP_CALL( SCIPallocBufferArray(scip, &simplexcoefs2, ncols) );
SCIP_CALL( SCIPallocBufferArray(scip, &cutcoefs, ncols) );
SCIP_CALL( SCIPallocBufferArray(scip, &basisind, nrows) );
/* get basis indices */
SCIP_CALL( SCIPgetLPBasisInd(scip, basisind) );
/* create vector "basisrow" with basisrow[column of non-slack basis variable] = corresponding row of B^-1;
* compute maximum absolute value of nonbasic row coefficients */
for (j = 0; j < nrows; ++j)
{
SCIP_COL** rowcols;
SCIP_Real* rowvals;
SCIP_ROW* row;
SCIP_Real val;
SCIP_Real max = 0.0;
int nnonz;
/* fill basisrow vector */
ind = basisind[j];
if ( ind >= 0 )
basisrow[ind] = j;
/* compute maximum absolute value of nonbasic row coefficients */
row = rows[j];
assert( row != NULL );
rowvals = SCIProwGetVals(row);
nnonz = SCIProwGetNNonz(row);
rowcols = SCIProwGetCols(row);
for (i = 0; i < nnonz; ++i)
{
if ( SCIPcolGetBasisStatus(rowcols[i]) == SCIP_BASESTAT_LOWER || SCIPcolGetBasisStatus(rowcols[i]) == SCIP_BASESTAT_UPPER )
{
val = REALABS(rowvals[i]);
if ( SCIPisFeasGT(scip, val, max) )
max = REALABS(val);
}
}
/* handle slack variable coefficient and save maximum value */
rowsmaxval[j] = MAX(max, 1.0);
}
/* initialize variable ranks with -1 */
for (j = 0; j < ncols; ++j)
varrank[j] = -1;
/* free buffer array */
SCIPfreeBufferArrayNull(scip, &basisind);
/* for the most promising disjunctions: try to generate disjunctive cuts */
ndisjcuts = 0;
for (i = 0; i < maxcuts; ++i)
{
SCIP_Bool madeintegral;
SCIP_Real cutlhs1;
SCIP_Real cutlhs2;
SCIP_Real bound1;
SCIP_Real bound2;
SCIP_ROW* row = NULL;
SCIP_VAR* var;
SCIP_COL* col;
int nonbasicnumber;
int cutrank = 0;
int edgenumber;
int rownnonz;
edgenumber = edgearray[i];
/* determine first simplex row */
var = SCIPnodeGetVarSOS1(conflictgraph, fixings1[edgenumber]);
col = SCIPvarGetCol(var);
ind = SCIPcolGetLPPos(col);
assert( ind >= 0 );
assert( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_BASIC );
/* get the 'ind'th row of B^-1 and B^-1 \cdot A */
SCIP_CALL( SCIPgetLPBInvRow(scip, basisrow[ind], binvrow, NULL, NULL) );
SCIP_CALL( SCIPgetLPBInvARow(scip, basisrow[ind], binvrow, coef, NULL, NULL) );
/* get the simplex-coefficients of the non-basic variables */
SCIP_CALL( getSimplexCoefficients(scip, rows, nrows, cols, ncols, coef, binvrow, simplexcoefs1, &nonbasicnumber) );
/* get rank of variable if not known already */
if ( varrank[ind] < 0 )
varrank[ind] = getVarRank(scip, binvrow, rowsmaxval, sepadata->maxweightrange, rows, nrows);
cutrank = MAX(cutrank, varrank[ind]);
/* get right hand side and bound of simplex talbeau row */
cutlhs1 = SCIPcolGetPrimsol(col);
if ( SCIPisFeasPositive(scip, cutlhs1) )
bound1 = SCIPcolGetUb(col);
else
bound1 = SCIPcolGetLb(col);
/* determine second simplex row */
var = SCIPnodeGetVarSOS1(conflictgraph, fixings2[edgenumber]);
col = SCIPvarGetCol(var);
ind = SCIPcolGetLPPos(col);
assert( ind >= 0 );
assert( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_BASIC );
/* get the 'ind'th row of B^-1 and B^-1 \cdot A */
SCIP_CALL( SCIPgetLPBInvRow(scip, basisrow[ind], binvrow, NULL, NULL) );
SCIP_CALL( SCIPgetLPBInvARow(scip, basisrow[ind], binvrow, coef, NULL, NULL) );
/* get the simplex-coefficients of the non-basic variables */
SCIP_CALL( getSimplexCoefficients(scip, rows, nrows, cols, ncols, coef, binvrow, simplexcoefs2, &nonbasicnumber) );
/* get rank of variable if not known already */
if ( varrank[ind] < 0 )
varrank[ind] = getVarRank(scip, binvrow, rowsmaxval, sepadata->maxweightrange, rows, nrows);
cutrank = MAX(cutrank, varrank[ind]);
/* get right hand side and bound of simplex talbeau row */
cutlhs2 = SCIPcolGetPrimsol(col);
if ( SCIPisFeasPositive(scip, cutlhs2) )
bound2 = SCIPcolGetUb(col);
else
bound2 = SCIPcolGetLb(col);
/* add coefficients to cut */
SCIP_CALL( generateDisjCutSOS1(scip, sepa, rows, nrows, cols, ncols, ndisjcuts, TRUE, sepadata->strengthen, cutlhs1, cutlhs2, bound1, bound2, simplexcoefs1, simplexcoefs2, cutcoefs, &row, &madeintegral) );
if ( row == NULL )
continue;
/* raise cutrank for present cut */
++cutrank;
/* check if there are numerical evidences */
if ( ( madeintegral && ( sepadata->maxrankintegral == -1 || cutrank <= sepadata->maxrankintegral ) )
|| ( ! madeintegral && ( sepadata->maxrank == -1 || cutrank <= sepadata->maxrank ) ) )
{
/* possibly add cut to LP if it is useful; in case the lhs of the cut is minus infinity (due to scaling) the cut is useless */
rownnonz = SCIProwGetNNonz(row);
if ( rownnonz > 0 && ! SCIPisInfinity(scip, -SCIProwGetLhs(row)) && ! SCIProwIsInLP(row) && SCIPisCutEfficacious(scip, NULL, row) )
{
SCIP_Bool infeasible;
/* set cut rank */
SCIProwChgRank(row, cutrank);
/* add cut */
SCIP_CALL( SCIPaddCut(scip, NULL, row, FALSE, &infeasible) );
SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );
if ( infeasible )
{
*result = SCIP_CUTOFF;
break;
}
++ndisjcuts;
}
}
/* release row */
SCIP_CALL( SCIPreleaseRow(scip, &row) );
}
/* save total number of cuts found so far */
sepadata->lastncutsfound = SCIPgetNCutsFound(scip);
/* evaluate the result of the separation */
if ( *result != SCIP_CUTOFF )
{
if ( ndisjcuts > 0 )
*result = SCIP_SEPARATED;
else
*result = SCIP_DIDNOTFIND;
}
SCIPdebugMessage("Number of found disjunctive cuts: %d.\n", ndisjcuts);
/* free buffer arrays */
SCIPfreeBufferArrayNull(scip, &cutcoefs);
SCIPfreeBufferArrayNull(scip, &simplexcoefs2);
SCIPfreeBufferArrayNull(scip, &simplexcoefs1);
SCIPfreeBufferArrayNull(scip, &coef);
SCIPfreeBufferArrayNull(scip, &binvrow);
SCIPfreeBufferArrayNull(scip, &basisrow);
SCIPfreeBufferArrayNull(scip, &fixings2);
SCIPfreeBufferArrayNull(scip, &fixings1);
SCIPfreeBufferArrayNull(scip, &edgearray);
SCIPfreeBufferArrayNull(scip, &rowsmaxval);
SCIPfreeBufferArrayNull(scip, &varrank);
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;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecShifting) /*lint --e{715}*/
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_SOL* sol;
SCIP_VAR** lpcands;
SCIP_Real* lpcandssol;
SCIP_ROW** lprows;
SCIP_Real* activities;
SCIP_ROW** violrows;
SCIP_Real* nincreases;
SCIP_Real* ndecreases;
int* violrowpos;
int* nfracsinrow;
SCIP_Real increaseweight;
SCIP_Real obj;
SCIP_Real bestshiftval;
SCIP_Real minobj;
int nlpcands;
int nlprows;
int nvars;
int nfrac;
int nviolrows;
int nprevviolrows;
int minnviolrows;
int nnonimprovingshifts;
int c;
int r;
SCIP_Longint nlps;
SCIP_Longint ncalls;
SCIP_Longint nsolsfound;
SCIP_Longint nnodes;
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
assert(SCIPhasCurrentNodeLP(scip));
*result = SCIP_DIDNOTRUN;
/* only call heuristic, if an optimal LP solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call heuristic, if the LP objective value is smaller than the cutoff bound */
if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
return SCIP_OKAY;
/* get heuristic data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* don't call heuristic, if we have already processed the current LP solution */
nlps = SCIPgetNLPs(scip);
if( nlps == heurdata->lastlp )
return SCIP_OKAY;
heurdata->lastlp = nlps;
/* don't call heuristic, if it was not successful enough in the past */
ncalls = SCIPheurGetNCalls(heur);
nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + SCIPheurGetNSolsFound(heur);
nnodes = SCIPgetNNodes(scip);
if( nnodes % ((ncalls/100)/(nsolsfound+1)+1) != 0 )
return SCIP_OKAY;
/* get fractional variables, that should be integral */
/* todo check if heuristic should include implicit integer variables for its calculations */
SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, NULL) );
nfrac = nlpcands;
/* only call heuristic, if LP solution is fractional */
if( nfrac == 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
/* get LP rows */
SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );
SCIPdebugMessage("executing shifting heuristic: %d LP rows, %d fractionals\n", nlprows, nfrac);
/* get memory for activities, violated rows, and row violation positions */
nvars = SCIPgetNVars(scip);
SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &violrows, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &violrowpos, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &nfracsinrow, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &nincreases, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &ndecreases, nvars) );
BMSclearMemoryArray(nfracsinrow, nlprows);
BMSclearMemoryArray(nincreases, nvars);
BMSclearMemoryArray(ndecreases, nvars);
/* get the activities for all globally valid rows;
* the rows should be feasible, but due to numerical inaccuracies in the LP solver, they can be violated
*/
nviolrows = 0;
for( r = 0; r < nlprows; ++r )
{
SCIP_ROW* row;
row = lprows[r];
assert(SCIProwGetLPPos(row) == r);
if( !SCIProwIsLocal(row) )
{
activities[r] = SCIPgetRowActivity(scip, row);
if( SCIPisFeasLT(scip, activities[r], SCIProwGetLhs(row))
|| SCIPisFeasGT(scip, activities[r], SCIProwGetRhs(row)) )
{
violrows[nviolrows] = row;
violrowpos[r] = nviolrows;
nviolrows++;
}
else
violrowpos[r] = -1;
}
}
/* calc the current number of fractional variables in rows */
for( c = 0; c < nlpcands; ++c )
addFracCounter(nfracsinrow, nlprows, lpcands[c], +1);
/* get the working solution from heuristic's local data */
sol = heurdata->sol;
assert(sol != NULL);
/* copy the current LP solution to the working solution */
SCIP_CALL( SCIPlinkLPSol(scip, sol) );
/* calculate the minimal objective value possible after rounding fractional variables */
minobj = SCIPgetSolTransObj(scip, sol);
assert(minobj < SCIPgetCutoffbound(scip));
for( c = 0; c < nlpcands; ++c )
{
obj = SCIPvarGetObj(lpcands[c]);
bestshiftval = obj > 0.0 ? SCIPfeasFloor(scip, lpcandssol[c]) : SCIPfeasCeil(scip, lpcandssol[c]);
minobj += obj * (bestshiftval - lpcandssol[c]);
}
/* try to shift remaining variables in order to become/stay feasible */
nnonimprovingshifts = 0;
minnviolrows = INT_MAX;
increaseweight = 1.0;
while( (nfrac > 0 || nviolrows > 0) && nnonimprovingshifts < MAXSHIFTINGS )
{
SCIP_VAR* shiftvar;
SCIP_Real oldsolval;
SCIP_Real newsolval;
SCIP_Bool oldsolvalisfrac;
int probindex;
SCIPdebugMessage("shifting heuristic: nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g), cutoff=%g\n",
nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj),
SCIPretransformObj(scip, SCIPgetCutoffbound(scip)));
nprevviolrows = nviolrows;
/* choose next variable to process:
* - if a violated row exists, shift a variable decreasing the violation, that has least impact on other rows
* - otherwise, shift a variable, that has strongest devastating impact on rows in opposite direction
*/
shiftvar = NULL;
oldsolval = 0.0;
newsolval = 0.0;
if( nviolrows > 0 && (nfrac == 0 || nnonimprovingshifts < MAXSHIFTINGS-1) )
{
SCIP_ROW* row;
int rowidx;
int rowpos;
int direction;
rowidx = -1;
rowpos = -1;
row = NULL;
if( nfrac > 0 )
{
for( rowidx = nviolrows-1; rowidx >= 0; --rowidx )
{
row = violrows[rowidx];
rowpos = SCIProwGetLPPos(row);
assert(violrowpos[rowpos] == rowidx);
if( nfracsinrow[rowpos] > 0 )
break;
}
}
if( rowidx == -1 )
{
rowidx = SCIPgetRandomInt(0, nviolrows-1, &heurdata->randseed);
row = violrows[rowidx];
rowpos = SCIProwGetLPPos(row);
assert(0 <= rowpos && rowpos < nlprows);
assert(violrowpos[rowpos] == rowidx);
assert(nfracsinrow[rowpos] == 0);
}
assert(violrowpos[rowpos] == rowidx);
SCIPdebugMessage("shifting heuristic: try to fix violated row <%s>: %g <= %g <= %g\n",
SCIProwGetName(row), SCIProwGetLhs(row), activities[rowpos], SCIProwGetRhs(row));
SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );
/* get direction in which activity must be shifted */
assert(SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row))
|| SCIPisFeasGT(scip, activities[rowpos], SCIProwGetRhs(row)));
direction = SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row)) ? +1 : -1;
/* search a variable that can shift the activity in the necessary direction */
SCIP_CALL( selectShifting(scip, sol, row, activities[rowpos], direction,
nincreases, ndecreases, increaseweight, &shiftvar, &oldsolval, &newsolval) );
}
if( shiftvar == NULL && nfrac > 0 )
{
SCIPdebugMessage("shifting heuristic: search rounding variable and try to stay feasible\n");
SCIP_CALL( selectEssentialRounding(scip, sol, minobj, lpcands, nlpcands, &shiftvar, &oldsolval, &newsolval) );
}
/* check, whether shifting was possible */
if( shiftvar == NULL || SCIPisEQ(scip, oldsolval, newsolval) )
{
SCIPdebugMessage("shifting heuristic: -> didn't find a shifting variable\n");
break;
}
SCIPdebugMessage("shifting heuristic: -> shift var <%s>[%g,%g], type=%d, oldval=%g, newval=%g, obj=%g\n",
SCIPvarGetName(shiftvar), SCIPvarGetLbGlobal(shiftvar), SCIPvarGetUbGlobal(shiftvar), SCIPvarGetType(shiftvar),
oldsolval, newsolval, SCIPvarGetObj(shiftvar));
/* update row activities of globally valid rows */
SCIP_CALL( updateActivities(scip, activities, violrows, violrowpos, &nviolrows, nlprows,
shiftvar, oldsolval, newsolval) );
if( nviolrows >= nprevviolrows )
nnonimprovingshifts++;
else if( nviolrows < minnviolrows )
{
minnviolrows = nviolrows;
nnonimprovingshifts = 0;
}
/* store new solution value and decrease fractionality counter */
SCIP_CALL( SCIPsetSolVal(scip, sol, shiftvar, newsolval) );
/* update fractionality counter and minimal objective value possible after shifting remaining variables */
oldsolvalisfrac = !SCIPisFeasIntegral(scip, oldsolval)
&& (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER);
obj = SCIPvarGetObj(shiftvar);
if( (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER)
&& oldsolvalisfrac )
{
assert(SCIPisFeasIntegral(scip, newsolval));
nfrac--;
nnonimprovingshifts = 0;
minnviolrows = INT_MAX;
addFracCounter(nfracsinrow, nlprows, shiftvar, -1);
/* the rounding was already calculated into the minobj -> update only if rounding in "wrong" direction */
if( obj > 0.0 && newsolval > oldsolval )
minobj += obj;
else if( obj < 0.0 && newsolval < oldsolval )
minobj -= obj;
}
else
{
/* update minimal possible objective value */
minobj += obj * (newsolval - oldsolval);
}
/* update increase/decrease arrays */
if( !oldsolvalisfrac )
{
probindex = SCIPvarGetProbindex(shiftvar);
assert(0 <= probindex && probindex < nvars);
increaseweight *= WEIGHTFACTOR;
if( newsolval < oldsolval )
ndecreases[probindex] += increaseweight;
else
nincreases[probindex] += increaseweight;
if( increaseweight >= 1e+09 )
{
int i;
for( i = 0; i < nvars; ++i )
{
nincreases[i] /= increaseweight;
ndecreases[i] /= increaseweight;
}
increaseweight = 1.0;
}
}
SCIPdebugMessage("shifting heuristic: -> nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n",
nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj));
}
/* check, if the new solution is feasible */
if( nfrac == 0 && nviolrows == 0 )
{
SCIP_Bool stored;
/* check solution for feasibility, and add it to solution store if possible
* neither integrality nor feasibility of LP rows has to be checked, because this is already
* done in the shifting heuristic itself; however, we better check feasibility of LP rows,
* because of numerical problems with activity updating
*/
SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, FALSE, TRUE, &stored) );
if( stored )
{
SCIPdebugMessage("found feasible shifted solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) ) );
*result = SCIP_FOUNDSOL;
}
}
/* free memory buffers */
SCIPfreeBufferArray(scip, &ndecreases);
SCIPfreeBufferArray(scip, &nincreases);
SCIPfreeBufferArray(scip, &nfracsinrow);
SCIPfreeBufferArray(scip, &violrowpos);
SCIPfreeBufferArray(scip, &violrows);
SCIPfreeBufferArray(scip, &activities);
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(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;
}
/** generates the direction of the shooting ray as the average of the normalized non-basic vars and rows */
static
SCIP_RETCODE generateAverageNBRay(
SCIP* scip, /**< SCIP data structure */
SCIP_Real* raydirection, /**< shooting ray */
int* fracspace, /**< index set of fractional variables */
SCIP_VAR** subspacevars, /**< pointer to fractional space variables */
int nsubspacevars /**< dimension of fractional space */
)
{
SCIP_ROW** rows;
SCIP_COL** cols;
int nrows;
int ncols;
int i;
assert(scip != NULL);
assert(raydirection != NULL);
assert(fracspace != NULL);
assert(subspacevars != NULL);
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
SCIP_CALL( SCIPgetLPColsData(scip, &cols, &ncols) );
/* add up non-basic variables */
for( i = nsubspacevars - 1; i >= 0; --i )
{
SCIP_Real solval;
solval = SCIPvarGetLPSol(subspacevars[i]);
if( SCIPisFeasEQ(scip, solval, SCIPvarGetLbLocal(subspacevars[i])) )
raydirection[i] = +1.0;
else if( SCIPisFeasEQ(scip, solval, SCIPvarGetUbLocal(subspacevars[i])) )
raydirection[i] = -1.0;
else
raydirection[i] = 0.0;
}
/* add up non-basic rows */
for( i = nrows - 1; i >= 0; --i )
{
SCIP_Real dualsol;
SCIP_Real factor;
SCIP_Real* coeffs;
SCIP_Real rownorm;
int j;
int nnonz;
dualsol = SCIProwGetDualsol(rows[i]);
if( SCIPisFeasPositive(scip, dualsol) )
factor = 1.0;
else if( SCIPisFeasNegative(scip, dualsol) )
factor = -1.0;
else
continue;
/* get the row's data */
coeffs = SCIProwGetVals(rows[i]);
cols = SCIProwGetCols(rows[i]);
nnonz = SCIProwGetNNonz(rows[i]);
rownorm = 0.0;
for( j = nnonz - 1; j >= 0; --j )
{
SCIP_VAR* var;
var = SCIPcolGetVar(cols[j]);
if( fracspace[SCIPvarGetProbindex(var)] >= 0 )
rownorm += coeffs[j] * coeffs[j];
}
if( SCIPisFeasZero(scip,rownorm) )
continue;
else
{
assert(rownorm > 0);
rownorm = SQRT(rownorm);
}
for( j = nnonz - 1; j >= 0; --j )
{
SCIP_VAR* var;
int f;
var = SCIPcolGetVar(cols[j]);
f = fracspace[SCIPvarGetProbindex(var)];
if( f >= 0 )
{
raydirection[f] += factor * coeffs[j] / rownorm;
assert(SCIP_REAL_MIN <= raydirection[f] && raydirection[f] <= SCIP_REAL_MAX);
}
}
}
return SCIP_OKAY;
}
/** generates the direction of the shooting ray as the average of the extreme rays of the basic cone */
static
SCIP_RETCODE generateAverageRay(
SCIP* scip, /**< SCIP data structure */
SCIP_Real* raydirection, /**< shooting ray */
SCIP_VAR** subspacevars, /**< pointer to fractional space variables */
int nsubspacevars, /**< dimension of fractional space */
SCIP_Bool weighted /**< should the rays be weighted? */
)
{
SCIP_ROW** rows;
SCIP_Real** tableaurows;
SCIP_Real* rownorm;
SCIP_Real rowweight;
int nrows;
int i;
int j;
assert(scip != NULL);
assert(raydirection != NULL);
assert(subspacevars != NULL);
/* get data */
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
/* allocate memory */
SCIP_CALL( SCIPallocBufferArray(scip, &tableaurows, nsubspacevars) );
for( j = nsubspacevars - 1; j >= 0; --j )
{
/*lint --e{866}*/
SCIP_CALL( SCIPallocBufferArray(scip, &tableaurows[j], nrows) );
}
SCIP_CALL( SCIPallocBufferArray(scip, &rownorm, nrows) );
for( i = nrows - 1; i >= 0; --i )
rownorm[i] = 0;
/* get the relevant columns of the simplex tableau */
for( j = nsubspacevars-1; j >= 0; --j )
{
assert(SCIPcolGetLPPos(SCIPvarGetCol(subspacevars[j])) >= 0);
SCIP_CALL( SCIPgetLPBInvACol(scip, SCIPcolGetLPPos(SCIPvarGetCol(subspacevars[j])), tableaurows[j]) );
for( i = nrows - 1; i >= 0; --i )
rownorm[i] += tableaurows[j][i] * tableaurows[j][i];
}
/* take average over all rows of the tableau */
for( i = nrows - 1; i >= 0; --i )
{
if( SCIPisFeasZero(scip, rownorm[i]) )
continue;
else
rownorm[i] = SQRT(rownorm[i]);
rowweight = 0.0;
if( weighted )
{
rowweight = SCIProwGetDualsol(rows[i]);
if( SCIPisFeasZero(scip, rowweight) )
continue;
}
else
rowweight = 1.0;
for( j = nsubspacevars - 1; j >= 0; --j )
{
raydirection[j] += tableaurows[j][i] / (rownorm[i] * rowweight);
assert(SCIP_REAL_MIN <= raydirection[j] && raydirection[j] <= SCIP_REAL_MAX);
}
}
/* free memory */
SCIPfreeBufferArray(scip, &rownorm);
for( j = nsubspacevars - 1; j >= 0; --j )
{
SCIPfreeBufferArray(scip, &tableaurows[j]);
}
SCIPfreeBufferArray(scip, &tableaurows);
return SCIP_OKAY;
}
