/** 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;
}
/** finds a continuous slack variable for an equation row, NULL if none exists */
static
void rowFindSlackVar(
SCIP* scip, /**< pointer to current SCIP data structure */
SCIP_ROW* row, /**< the row for which a slack variable is searched */
SCIP_VAR** varpointer, /**< pointer to store the slack variable */
SCIP_Real* coeffpointer /**< pointer to store the coefficient of the slack variable */
)
{
int v;
SCIP_COL** rowcols;
SCIP_Real* rowvals;
int nrowvals;
assert(row != NULL);
assert(varpointer != NULL);
assert(coeffpointer != NULL);
rowcols = SCIProwGetCols(row);
rowvals = SCIProwGetVals(row);
nrowvals = SCIProwGetNNonz(row);
assert(nrowvals == 0 || rowvals != NULL);
assert(nrowvals == 0 || rowcols != NULL);
/* iterate over the row variables. Stop after the first unfixed continuous variable was found. */
for( v = nrowvals - 1; v >= 0; --v )
{
SCIP_VAR* colvar;
assert(rowcols[v] != NULL);
if( SCIPcolGetLPPos(rowcols[v]) == -1 )
continue;
colvar = SCIPcolGetVar(rowcols[v]);
if( SCIPvarGetType(colvar) == SCIP_VARTYPE_CONTINUOUS
&& !SCIPisFeasEQ(scip, SCIPvarGetLbGlobal(colvar), SCIPvarGetUbGlobal(colvar))
&& SCIPcolGetNLPNonz(rowcols[v]) == 1 )
{
SCIPdebugMessage(" slack variable for row %s found: %s\n", SCIProwGetName(row), SCIPvarGetName(colvar));
*coeffpointer = rowvals[v];
*varpointer = colvar;
return;
}
}
*varpointer = NULL;
*coeffpointer = 0.0;
SCIPdebugMessage("No slack variable for row %s found. \n", SCIProwGetName(row));
}
/** 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;
}
/** reduced cost propagation method for an LP solution */
static
SCIP_DECL_PROPEXEC(propExecRedcost)
{ /*lint --e{715}*/
SCIP_PROPDATA* propdata;
SCIP_COL** cols;
SCIP_Real requiredredcost;
SCIP_Real cutoffbound;
SCIP_Real lpobjval;
SCIP_Bool propbinvars;
SCIP_Bool cutoff;
int nchgbds;
int ncols;
int c;
*result = SCIP_DIDNOTRUN;
/* in case we have a zero objective function, we skip the reduced cost propagator */
if( SCIPgetNObjVars(scip) == 0 )
return SCIP_OKAY;
/* propagator can only be applied during solving stage */
if( SCIPgetStage(scip) < SCIP_STAGE_SOLVING )
return SCIP_OKAY;
/* we cannot apply reduced cost fixing, if we want to solve exactly */
/**@todo implement reduced cost fixing with interval arithmetics */
if( SCIPisExactSolve(scip) )
return SCIP_OKAY;
/* only call propagator, if the current node has an LP */
if( !SCIPhasCurrentNodeLP(scip) )
return SCIP_OKAY;
/* only call propagator, if an optimal LP solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call propagator, if the current LP is a valid relaxation */
if( !SCIPisLPRelax(scip) )
return SCIP_OKAY;
/* we cannot apply reduced cost strengthening, if no simplex basis is available */
if( !SCIPisLPSolBasic(scip) )
return SCIP_OKAY;
/* get current cutoff bound */
cutoffbound = SCIPgetCutoffbound(scip);
/* reduced cost strengthening can only be applied, if we have a finite cutoff */
if( SCIPisInfinity(scip, cutoffbound) )
return SCIP_OKAY;
/* get LP columns */
cols = SCIPgetLPCols(scip);
ncols = SCIPgetNLPCols(scip);
/* do nothing if the LP has no columns (is empty) */
if( ncols == 0 )
return SCIP_OKAY;
/* get propagator data */
propdata = SCIPpropGetData(prop);
assert(propdata != NULL);
/* chack if all integral variables are fixed and the continuous variables should not be propagated */
if( !propdata->continuous && SCIPgetNPseudoBranchCands(scip) == 0 )
return SCIP_OKAY;
/* get LP objective value */
lpobjval = SCIPgetLPObjval(scip);
/* check if binary variables should be propagated */
propbinvars = (SCIPgetDepth(scip) == 0) || (cutoffbound - lpobjval < 5 * propdata->maxredcost);
/* skip the propagator if the problem has only binary variables and those should not be propagated */
if( !propbinvars && SCIPgetNVars(scip) == SCIPgetNBinVars(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
cutoff = FALSE;
nchgbds = 0;
/* compute the required reduced cost which are needed for a binary variable to be fixed */
requiredredcost = cutoffbound - lpobjval;
SCIPdebugMessage("lpobjval <%g>, cutoffbound <%g>, max reduced <%g>, propgate binary %u, use implics %u\n",
lpobjval, cutoffbound, propdata->maxredcost, propbinvars, propdata->usefullimplics);
/* check reduced costs for non-basic columns */
for( c = 0; c < ncols && !cutoff; ++c )
{
SCIP_VAR* var;
var = SCIPcolGetVar(cols[c]);
/* skip continuous variables in case the corresponding parameter is set */
if( !propdata->continuous && !SCIPvarIsIntegral(var) )
continue;
if( SCIPvarIsBinary(var) )
{
if( propbinvars )
{
if( SCIPgetDepth(scip) == 0 )
{
SCIP_CALL( propagateRootRedcostBinvar(scip, propdata, var, cols[c], cutoffbound, &nchgbds) );
}
else
{
SCIP_CALL( propagateRedcostBinvar(scip, propdata, var, cols[c], requiredredcost, &nchgbds, &cutoff) );
}
}
}
else
{
SCIP_CALL( propagateRedcostVar(scip, var, cols[c], lpobjval, cutoffbound, &nchgbds) );
}
}
if( cutoff )
{
*result = SCIP_CUTOFF;
SCIPdebugMessage("node %"SCIP_LONGINT_FORMAT": detected cutoff\n",
SCIPnodeGetNumber(SCIPgetCurrentNode(scip)));
}
else if( nchgbds > 0 )
{
*result = SCIP_REDUCEDDOM;
SCIPdebugMessage("node %"SCIP_LONGINT_FORMAT": %d bound changes (max redcost <%g>)\n",
SCIPnodeGetNumber(SCIPgetCurrentNode(scip)) , nchgbds, propdata->maxredcost);
}
return SCIP_OKAY;
}
/** applies a cut that is a bound change directly as bound change instead of adding it as row to the LP */
static
SCIP_RETCODE sepastoreApplyBdchg(
SCIP_SEPASTORE* sepastore, /**< separation storage */
BMS_BLKMEM* blkmem, /**< block memory */
SCIP_SET* set, /**< global SCIP settings */
SCIP_STAT* stat, /**< problem statistics */
SCIP_TREE* tree, /**< branch and bound tree */
SCIP_LP* lp, /**< LP data */
SCIP_BRANCHCAND* branchcand, /**< branching candidate storage */
SCIP_EVENTQUEUE* eventqueue, /**< event queue */
SCIP_ROW* cut, /**< cut with a single variable */
SCIP_Bool* cutoff /**< pointer to store whether an empty domain was created */
)
{
SCIP_COL** cols;
SCIP_Real* vals;
SCIP_VAR* var;
SCIP_Real lhs;
SCIP_Real rhs;
assert(sepastore != NULL);
assert(!SCIProwIsModifiable(cut));
assert(SCIProwGetNNonz(cut) == 1);
assert(cutoff != NULL);
*cutoff = FALSE;
/* get the single variable and its coefficient of the cut */
cols = SCIProwGetCols(cut);
assert(cols != NULL);
var = SCIPcolGetVar(cols[0]);
vals = SCIProwGetVals(cut);
assert(vals != NULL);
assert(!SCIPsetIsZero(set, vals[0]));
/* if the coefficient is nearly zero, we better ignore this cut for numerical reasons */
if( SCIPsetIsFeasZero(set, vals[0]) )
return SCIP_OKAY;
/* get the left hand side of the cut and convert it to a bound */
lhs = SCIProwGetLhs(cut);
if( !SCIPsetIsInfinity(set, -lhs) )
{
lhs -= SCIProwGetConstant(cut);
if( vals[0] > 0.0 )
{
/* coefficient is positive -> lhs corresponds to lower bound */
SCIP_CALL( sepastoreApplyLb(sepastore, blkmem, set, stat, tree, lp, branchcand, eventqueue,
var, lhs/vals[0], cutoff) );
}
else
{
/* coefficient is negative -> lhs corresponds to upper bound */
SCIP_CALL( sepastoreApplyUb(sepastore, blkmem, set, stat, tree, lp, branchcand, eventqueue,
var, lhs/vals[0], cutoff) );
}
}
/* get the right hand side of the cut and convert it to a bound */
rhs = SCIProwGetRhs(cut);
if( !SCIPsetIsInfinity(set, rhs) )
{
rhs -= SCIProwGetConstant(cut);
if( vals[0] > 0.0 )
{
/* coefficient is positive -> rhs corresponds to upper bound */
SCIP_CALL( sepastoreApplyUb(sepastore, blkmem, set, stat, tree, lp, branchcand, eventqueue,
var, rhs/vals[0], cutoff) );
}
else
{
/* coefficient is negative -> rhs corresponds to lower bound */
SCIP_CALL( sepastoreApplyLb(sepastore, blkmem, set, stat, tree, lp, branchcand, eventqueue,
var, rhs/vals[0], cutoff) );
}
}
/* count the bound change as applied cut */
if( !sepastore->initiallp )
sepastore->ncutsapplied++;
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;
}
/** calculates the initial mean and variance of the row activity normal distribution.
*
* The mean value \f$ \mu \f$ is given by \f$ \mu = \sum_i=1^n c_i * (lb_i +ub_i) / 2 \f$ where
* \f$n \f$ is the number of variables, and \f$ c_i, lb_i, ub_i \f$ are the variable coefficient and
* bounds, respectively. With the same notation, the variance \f$ \sigma^2 \f$ is given by
* \f$ \sigma^2 = \sum_i=1^n c_i^2 * \sigma^2_i \f$, with the variance being
* \f$ \sigma^2_i = ((ub_i - lb_i + 1)^2 - 1) / 12 \f$ for integer variables and
* \f$ \sigma^2_i = (ub_i - lb_i)^2 / 12 \f$ for continuous variables.
*/
static
void rowCalculateGauss(
SCIP* scip, /**< SCIP data structure */
SCIP_HEURDATA* heurdata, /**< the heuristic rule data */
SCIP_ROW* row, /**< the row for which the gaussian normal distribution has to be calculated */
SCIP_Real* mu, /**< pointer to store the mean value of the gaussian normal distribution */
SCIP_Real* sigma2, /**< pointer to store the variance value of the gaussian normal distribution */
int* rowinfinitiesdown, /**< pointer to store the number of variables with infinite bounds to DECREASE activity */
int* rowinfinitiesup /**< pointer to store the number of variables with infinite bounds to INCREASE activity */
)
{
SCIP_COL** rowcols;
SCIP_Real* rowvals;
int nrowvals;
int c;
assert(scip != NULL);
assert(row != NULL);
assert(mu != NULL);
assert(sigma2 != NULL);
assert(rowinfinitiesup != NULL);
assert(rowinfinitiesdown != NULL);
rowcols = SCIProwGetCols(row);
rowvals = SCIProwGetVals(row);
nrowvals = SCIProwGetNNonz(row);
assert(nrowvals == 0 || rowcols != NULL);
assert(nrowvals == 0 || rowvals != NULL);
*mu = SCIProwGetConstant(row);
*sigma2 = 0.0;
*rowinfinitiesdown = 0;
*rowinfinitiesup = 0;
/* loop over nonzero row coefficients and sum up the variable contributions to mu and sigma2 */
for( c = 0; c < nrowvals; ++c )
{
SCIP_VAR* colvar;
SCIP_Real colval;
SCIP_Real colvarlb;
SCIP_Real colvarub;
SCIP_Real squarecoeff;
SCIP_Real varvariance;
SCIP_Real varmean;
int varindex;
assert(rowcols[c] != NULL);
colvar = SCIPcolGetVar(rowcols[c]);
assert(colvar != NULL);
colval = rowvals[c];
colvarlb = SCIPvarGetLbLocal(colvar);
colvarub = SCIPvarGetUbLocal(colvar);
varmean = 0.0;
varvariance = 0.0;
varindex = SCIPvarGetProbindex(colvar);
assert((heurdata->currentlbs[varindex] == SCIP_INVALID)
== (heurdata->currentubs[varindex] == SCIP_INVALID)); /*lint !e777 doesn't like comparing floats for equality */
/* variable bounds need to be watched from now on */
if( heurdata->currentlbs[varindex] == SCIP_INVALID ) /*lint !e777 doesn't like comparing floats for equality */
heurdataUpdateCurrentBounds(scip, heurdata, colvar);
assert(!SCIPisInfinity(scip, colvarlb));
assert(!SCIPisInfinity(scip, -colvarub));
assert(SCIPisFeasLE(scip, colvarlb, colvarub));
/* variables with infinite bounds are skipped for the calculation of the variance; they need to
* be accounted for by the counters for infinite row activity decrease and increase and they
* are used to shift the row activity mean in case they have one nonzero, but finite bound */
if( SCIPisInfinity(scip, -colvarlb) || SCIPisInfinity(scip, colvarub) )
{
if( SCIPisInfinity(scip, colvarub) )
{
/* an infinite upper bound gives the row an infinite maximum activity or minimum activity, if the coefficient is
* positive or negative, resp.
*/
if( colval < 0.0 )
++(*rowinfinitiesdown);
else
++(*rowinfinitiesup);
}
/* an infinite lower bound gives the row an infinite maximum activity or minimum activity, if the coefficient is
* negative or positive, resp.
*/
if( SCIPisInfinity(scip, -colvarlb) )
{
if( colval > 0.0 )
++(*rowinfinitiesdown);
else
++(*rowinfinitiesup);
}
}
SCIPvarCalcDistributionParameters(scip, colvarlb, colvarub, SCIPvarGetType(colvar), &varmean, &varvariance);
/* actual values are updated; the contribution of the variable to mu is the arithmetic mean of its bounds */
*mu += colval * varmean;
/* the variance contribution of a variable is c^2 * (u - l)^2 / 12.0 for continuous and c^2 * ((u - l + 1)^2 - 1) / 12.0 for integer */
squarecoeff = SQUARED(colval);
*sigma2 += squarecoeff * varvariance;
assert(!SCIPisFeasNegative(scip, *sigma2));
}
SCIPdebug( SCIPprintRow(scip, row, NULL) );
SCIPdebugMessage(" Row %s has a mean value of %g at a sigma2 of %g \n", SCIProwGetName(row), *mu, *sigma2);
}
/** computes a disjunctive cut inequality based on two simplex taubleau rows */
static
SCIP_RETCODE generateDisjCutSOS1(
SCIP* scip, /**< SCIP pointer */
SCIP_SEPA* sepa, /**< separator */
SCIP_ROW** rows, /**< LP rows */
int nrows, /**< number of LP rows */
SCIP_COL** cols, /**< LP columns */
int ncols, /**< number of LP columns */
int ndisjcuts, /**< number of disjunctive cuts found so far */
SCIP_Bool scale, /**< should cut be scaled */
SCIP_Bool strengthen, /**< should cut be strengthened if integer variables are present */
SCIP_Real cutlhs1, /**< left hand side of the first simplex row */
SCIP_Real cutlhs2, /**< left hand side of the second simplex row */
SCIP_Real bound1, /**< bound of first simplex row */
SCIP_Real bound2, /**< bound of second simplex row */
SCIP_Real* simplexcoefs1, /**< simplex coefficients of first row */
SCIP_Real* simplexcoefs2, /**< simplex coefficients of second row */
SCIP_Real* cutcoefs, /**< pointer to store cut coefficients (length: nscipvars) */
SCIP_ROW** row, /**< pointer to store disjunctive cut inequality */
SCIP_Bool* madeintegral /**< pointer to store whether cut has been scaled to integral values */
)
{
char cutname[SCIP_MAXSTRLEN];
SCIP_COL** rowcols;
SCIP_COL* col;
SCIP_Real* rowvals;
SCIP_Real lhsrow;
SCIP_Real rhsrow;
SCIP_Real cutlhs;
SCIP_Real sgn;
SCIP_Real lb;
SCIP_Real ub;
int nonbasicnumber = 0;
int rownnonz;
int ind;
int r;
int c;
assert( scip != NULL );
assert( row != NULL );
assert( rows != NULL );
assert( cols != NULL );
assert( simplexcoefs1 != NULL );
assert( simplexcoefs2 != NULL );
assert( cutcoefs != NULL );
assert( sepa != NULL );
assert( madeintegral != NULL );
*madeintegral = FALSE;
/* check signs */
if ( SCIPisFeasPositive(scip, cutlhs1) == SCIPisFeasPositive(scip, cutlhs2) )
sgn = 1.0;
else
sgn = -1.0;
/* check bounds */
if ( SCIPisInfinity(scip, REALABS(bound1)) || SCIPisInfinity(scip, REALABS(bound2)) )
strengthen = FALSE;
/* compute left hand side of row (a later update is possible, see below) */
cutlhs = sgn * cutlhs1 * cutlhs2;
/* add cut-coefficients of the non-basic non-slack variables */
for (c = 0; c < ncols; ++c)
{
col = cols[c];
assert( col != NULL );
ind = SCIPcolGetLPPos(col);
assert( ind >= 0 );
if ( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_LOWER )
{
lb = SCIPcolGetLb(col);
/* for integer variables we may obtain stronger coefficients */
if ( strengthen && SCIPcolIsIntegral(col) )
{
SCIP_Real mval;
SCIP_Real mvalfloor;
SCIP_Real mvalceil;
mval = (cutlhs2 * simplexcoefs1[nonbasicnumber] - cutlhs1 * simplexcoefs2[nonbasicnumber]) / (cutlhs2 * bound1 + cutlhs1 * bound2);
mvalfloor = SCIPfloor(scip, mval);
mvalceil = SCIPceil(scip, mval);
cutcoefs[ind] = MIN(sgn * cutlhs2 * (simplexcoefs1[nonbasicnumber] - mvalfloor * bound1), sgn * cutlhs1 * (simplexcoefs2[nonbasicnumber] + mvalceil * bound2));
assert( SCIPisFeasLE(scip, cutcoefs[ind], MAX(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber])) );
}
else
cutcoefs[ind] = MAX(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber]);
cutlhs += cutcoefs[ind] * lb;
++nonbasicnumber;
}
else if ( SCIPcolGetBasisStatus(col) == SCIP_BASESTAT_UPPER )
{
ub = SCIPcolGetUb(col);
/* for integer variables we may obtain stronger coefficients */
if ( strengthen && SCIPcolIsIntegral(col) )
{
SCIP_Real mval;
SCIP_Real mvalfloor;
SCIP_Real mvalceil;
mval = (cutlhs2 * simplexcoefs1[nonbasicnumber] - cutlhs1 * simplexcoefs2[nonbasicnumber]) / (cutlhs2 * bound1 + cutlhs1 * bound2);
mvalfloor = SCIPfloor(scip, -mval);
mvalceil = SCIPceil(scip, -mval);
cutcoefs[ind] = MAX(sgn * cutlhs2 * (simplexcoefs1[nonbasicnumber] + mvalfloor * bound1), sgn * cutlhs1 * (simplexcoefs2[nonbasicnumber] - mvalceil * bound2));
assert( SCIPisFeasLE(scip, -cutcoefs[ind], -MIN(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber])) );
}
else
cutcoefs[ind] = MIN(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber]);
cutlhs += cutcoefs[ind] * ub;
++nonbasicnumber;
}
else
{
assert( SCIPcolGetBasisStatus(col) != SCIP_BASESTAT_ZERO );
cutcoefs[ind] = 0.0;
}
}
/* add cut-coefficients of the non-basic slack variables */
for (r = 0; r < nrows; ++r)
{
rhsrow = SCIProwGetRhs(rows[r]) - SCIProwGetConstant(rows[r]);
lhsrow = SCIProwGetLhs(rows[r]) - SCIProwGetConstant(rows[r]);
assert( SCIProwGetBasisStatus(rows[r]) != SCIP_BASESTAT_ZERO );
assert( SCIPisFeasZero(scip, lhsrow - rhsrow) || SCIPisNegative(scip, lhsrow - rhsrow) );
assert( SCIProwIsInLP(rows[r]) );
if ( SCIProwGetBasisStatus(rows[r]) != SCIP_BASESTAT_BASIC )
{
SCIP_Real cutcoef;
if ( SCIProwGetBasisStatus(rows[r]) == SCIP_BASESTAT_UPPER )
{
assert( SCIPisFeasZero(scip, SCIPgetRowLPActivity(scip, rows[r]) - SCIProwGetRhs(rows[r])) );
cutcoef = MAX(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber]);
cutlhs -= cutcoef * rhsrow;
++nonbasicnumber;
}
else /* SCIProwGetBasisStatus(rows[r]) == SCIP_BASESTAT_LOWER */
{
assert( SCIProwGetBasisStatus(rows[r]) == SCIP_BASESTAT_LOWER );
assert( SCIPisFeasZero(scip, SCIPgetRowLPActivity(scip, rows[r]) - SCIProwGetLhs(rows[r])) );
cutcoef = MIN(sgn * cutlhs2 * simplexcoefs1[nonbasicnumber], sgn * cutlhs1 * simplexcoefs2[nonbasicnumber]);
cutlhs -= cutcoef * lhsrow;
++nonbasicnumber;
}
rownnonz = SCIProwGetNNonz(rows[r]);
rowvals = SCIProwGetVals(rows[r]);
rowcols = SCIProwGetCols(rows[r]);
for (c = 0; c < rownnonz; ++c)
{
ind = SCIPcolGetLPPos(rowcols[c]);
/* if column is not in LP, then return without generating cut */
if ( ind < 0 )
{
*row = NULL;
return SCIP_OKAY;
}
cutcoefs[ind] -= cutcoef * rowvals[c];
}
}
}
/* create cut */
(void) SCIPsnprintf(cutname, SCIP_MAXSTRLEN, "%s_%d_%d", SCIPsepaGetName(sepa), SCIPgetNLPs(scip), ndisjcuts);
if ( SCIPgetDepth(scip) == 0 )
SCIP_CALL( SCIPcreateEmptyRowSepa(scip, row, sepa, cutname, cutlhs, SCIPinfinity(scip), FALSE, FALSE, TRUE) );
else
SCIP_CALL( SCIPcreateEmptyRowSepa(scip, row, sepa, cutname, cutlhs, SCIPinfinity(scip), TRUE, FALSE, TRUE) );
SCIP_CALL( SCIPcacheRowExtensions(scip, *row) );
for (c = 0; c < ncols; ++c)
{
ind = SCIPcolGetLPPos(cols[c]);
assert( ind >= 0 );
if ( ! SCIPisFeasZero(scip, cutcoefs[ind]) )
{
SCIP_CALL( SCIPaddVarToRow(scip, *row, SCIPcolGetVar(cols[c]), cutcoefs[ind] ) );
}
}
SCIP_CALL( SCIPflushRowExtensions(scip, *row) );
/* try to scale the cut to integral values
* @todo find better but still stable disjunctive cut settings
*/
if ( scale )
{
int maxdepth;
int depth;
SCIP_Longint maxdnom;
SCIP_Real maxscale;
depth = SCIPgetDepth(scip);
assert( depth >= 0 );
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;
}
SCIP_CALL( SCIPmakeRowIntegral(scip, *row, -SCIPepsilon(scip), SCIPsumepsilon(scip), maxdnom, maxscale, TRUE, madeintegral) );
}
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;
* rounding in a direction is forbidden, if this forces the objective value over the upper bound
*/
static
SCIP_RETCODE selectRounding(
SCIP* scip, /**< SCIP data structure */
SCIP_SOL* sol, /**< primal solution */
SCIP_Real minobj, /**< minimal objective value possible after rounding remaining fractional vars */
SCIP_ROW* row, /**< LP row */
int direction, /**< should the activity be increased (+1) or decreased (-1)? */
SCIP_VAR** roundvar, /**< pointer to store the rounding variable, returns NULL if impossible */
SCIP_Real* oldsolval, /**< pointer to store old (fractional) solution value of rounding variable */
SCIP_Real* newsolval /**< pointer to store new (rounded) solution value of rounding variable */
)
{
SCIP_COL* col;
SCIP_VAR* var;
SCIP_Real val;
SCIP_COL** rowcols;
SCIP_Real* rowvals;
SCIP_Real solval;
SCIP_Real roundval;
SCIP_Real obj;
SCIP_Real deltaobj;
SCIP_Real bestdeltaobj;
SCIP_VARTYPE vartype;
int nrowcols;
int nlocks;
int minnlocks;
int c;
assert(direction == +1 || direction == -1);
assert(roundvar != NULL);
assert(oldsolval != NULL);
assert(newsolval != NULL);
/* get row entries */
rowcols = SCIProwGetCols(row);
rowvals = SCIProwGetVals(row);
nrowcols = SCIProwGetNLPNonz(row);
/* select rounding variable */
minnlocks = INT_MAX;
bestdeltaobj = SCIPinfinity(scip);
*roundvar = NULL;
for( c = 0; c < nrowcols; ++c )
{
col = rowcols[c];
var = SCIPcolGetVar(col);
vartype = SCIPvarGetType(var);
if( vartype == SCIP_VARTYPE_BINARY || vartype == SCIP_VARTYPE_INTEGER )
{
solval = SCIPgetSolVal(scip, sol, var);
if( !SCIPisFeasIntegral(scip, solval) )
{
val = rowvals[c];
obj = SCIPvarGetObj(var);
if( direction * val < 0.0 )
{
/* rounding down */
nlocks = SCIPvarGetNLocksDown(var);
if( nlocks <= minnlocks )
{
roundval = SCIPfeasFloor(scip, solval);
deltaobj = obj * (roundval - solval);
if( (nlocks < minnlocks || deltaobj < bestdeltaobj) && minobj - obj < SCIPgetCutoffbound(scip) )
{
minnlocks = nlocks;
bestdeltaobj = deltaobj;
*roundvar = var;
*oldsolval = solval;
*newsolval = roundval;
}
}
}
else
{
/* rounding up */
assert(direction * val > 0.0);
nlocks = SCIPvarGetNLocksUp(var);
if( nlocks <= minnlocks )
{
roundval = SCIPfeasCeil(scip, solval);
deltaobj = obj * (roundval - solval);
if( (nlocks < minnlocks || deltaobj < bestdeltaobj) && minobj + obj < SCIPgetCutoffbound(scip) )
{
minnlocks = nlocks;
bestdeltaobj = deltaobj;
*roundvar = var;
*oldsolval = solval;
*newsolval = roundval;
}
}
}
}
}
}
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;
}
/** 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(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;
}