/** checks the consistency of the origbranch constraints in the problem */
void GCGconsOrigbranchCheckConsistency(
SCIP* scip /**< SCIP data structure */
)
{
#ifdef CHECKCONSISTENCY
SCIP_CONSHDLR* conshdlr;
#ifndef NDEBUG
SCIP_CONS** conss;
int nconss;
int i;
SCIP_CONSDATA* consdata;
#endif
assert(scip != NULL);
conshdlr = SCIPfindConshdlr(scip, CONSHDLR_NAME);
if( conshdlr == NULL )
{
SCIPerrorMessage("origbranch constraint handler not found\n");
return;
}
#ifndef NDEBUG
conss = SCIPconshdlrGetConss(conshdlr);
nconss = SCIPconshdlrGetNConss(conshdlr);
for( i = 0; i < nconss; i++ )
{
consdata = SCIPconsGetData(conss[i]);
assert(consdata != NULL);
assert(consdata->node != NULL);
assert((consdata->parentcons == NULL) == (SCIPnodeGetDepth(consdata->node) == 0));
assert(consdata->parentcons == NULL || SCIPconsGetData(consdata->parentcons)->child1cons == conss[i]
|| SCIPconsGetData(consdata->parentcons)->child2cons == conss[i]
|| ( SCIPinProbing(scip) && SCIPconsGetData(consdata->parentcons)->probingtmpcons == conss[i]));
assert(consdata->child1cons == NULL || SCIPconsGetData(consdata->child1cons)->parentcons == conss[i]);
assert(consdata->child2cons == NULL || SCIPconsGetData(consdata->child2cons)->parentcons == conss[i]);
assert(consdata->probingtmpcons == NULL || SCIPinProbing(scip));
assert(consdata->probingtmpcons == NULL || SCIPconsGetData(consdata->probingtmpcons)->parentcons == conss[i]);
assert(consdata->mastercons == NULL ||
GCGconsMasterbranchGetOrigcons(consdata->mastercons) == conss[i]);
}
#endif
#endif
}
/** execution method of propagator */
static
SCIP_DECL_PROPEXEC(propExecDualfix)
{ /*lint --e{715}*/
int nfixedvars;
SCIP_Bool cutoff;
SCIP_Bool unbounded;
assert(prop != NULL);
assert(strcmp(SCIPpropGetName(prop), PROP_NAME) == 0);
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
/** @warning Don't run in probing or in repropagation since this can lead to wrong conclusion
*
* do not run if propagation w.r.t. current objective is not allowed
*/
if( SCIPinProbing(scip) || SCIPinRepropagation(scip) || !SCIPallowDualReds(scip) )
return SCIP_OKAY;
cutoff = FALSE;
unbounded = FALSE;
nfixedvars = 0;
SCIP_CALL( performDualfix(scip, &nfixedvars, &unbounded, &cutoff) );
/* evaluate propagation result */
if( cutoff )
*result = SCIP_CUTOFF;
else if( unbounded )
*result = SCIP_UNBOUNDED;
else if( nfixedvars > 0 )
*result = SCIP_REDUCEDDOM;
else
*result = SCIP_DIDNOTFIND;
return SCIP_OKAY;
}
/** perform randomized rounding of the given solution. Domain propagation is optionally applied after every rounding
* step
*/
static
SCIP_RETCODE performRandRounding(
SCIP* scip, /**< SCIP main data structure */
SCIP_HEURDATA* heurdata, /**< heuristic data */
SCIP_SOL* sol, /**< solution to round */
SCIP_VAR** cands, /**< candidate variables */
int ncands, /**< number of candidates */
SCIP_Bool propagate, /**< should the rounding be propagated? */
SCIP_RESULT* result /**< pointer to store the result of the heuristic call */
)
{
int c;
SCIP_Bool stored;
SCIP_VAR** permutedcands;
SCIP_Bool cutoff;
assert(heurdata != NULL);
/* start probing tree before rounding begins */
if( propagate )
{
SCIP_CALL( SCIPstartProbing(scip) );
SCIPenableVarHistory(scip);
}
/* copy and permute the candidate array */
SCIP_CALL( SCIPduplicateBufferArray(scip, &permutedcands, cands, ncands) );
assert(permutedcands != NULL);
SCIPpermuteArray((void **)permutedcands, 0, ncands, &heurdata->randseed);
cutoff = FALSE;
/* loop over candidates and perform randomized rounding and optionally probing. */
for (c = 0; c < ncands && !cutoff; ++c)
{
SCIP_VAR* var;
SCIP_Real oldsolval;
SCIP_Real newsolval;
SCIP_Bool mayrounddown;
SCIP_Bool mayroundup;
SCIP_Longint ndomreds;
SCIP_Real lb;
SCIP_Real ub;
SCIP_Real ceilval;
SCIP_Real floorval;
/* get next variable from permuted candidate array */
var = permutedcands[c];
oldsolval = SCIPgetSolVal(scip, sol, var);
lb = SCIPvarGetLbLocal(var);
ub = SCIPvarGetUbLocal(var);
assert( ! SCIPisFeasIntegral(scip, oldsolval) );
assert( SCIPvarGetStatus(var) == SCIP_VARSTATUS_COLUMN );
mayrounddown = SCIPvarMayRoundDown(var);
mayroundup = SCIPvarMayRoundUp(var);
ceilval = SCIPfeasCeil(scip, oldsolval);
floorval = SCIPfeasFloor(scip, oldsolval);
SCIPdebugMessage("rand rounding heuristic: var <%s>, val=%g, rounddown=%u, roundup=%u\n",
SCIPvarGetName(var), oldsolval, mayrounddown, mayroundup);
/* abort if rounded ceil and floor value lie outside the variable domain. Otherwise, check if
* bounds allow only one rounding direction, anyway */
if( lb > ceilval + 0.5 || ub < floorval - 0.5 )
{
cutoff = TRUE;
break;
}
else if( SCIPisFeasEQ(scip, lb, ceilval) )
{
/* only rounding up possible */
assert(SCIPisFeasGE(scip, ub, ceilval));
newsolval = ceilval;
}
else if( SCIPisFeasEQ(scip, ub, floorval) )
{
/* only rounding down possible */
assert(SCIPisFeasLE(scip,lb, floorval));
newsolval = floorval;
}
else if( !heurdata->usesimplerounding || !(mayroundup || mayrounddown) )
{
/* the standard randomized rounding */
SCIP_Real randnumber;
randnumber = SCIPgetRandomReal(0.0, 1.0, &heurdata->randseed);
if( randnumber <= oldsolval - floorval )
newsolval = ceilval;
else
newsolval = floorval;
}
/* choose rounding direction, if possible, or use the only direction guaranteed to be feasible */
else if( mayrounddown && mayroundup )
{
/* we can round in both directions: round in objective function direction */
if ( SCIPvarGetObj(var) >= 0.0 )
newsolval = floorval;
else
newsolval = ceilval;
}
else if( mayrounddown )
newsolval = floorval;
else
{
assert(mayroundup);
newsolval = ceilval;
}
assert(SCIPisFeasLE(scip, lb, newsolval));
assert(SCIPisFeasGE(scip, ub, newsolval));
/* if propagation is enabled, fix the candidate variable to its rounded value and propagate the solution */
if( propagate )
{
SCIP_Bool lbadjust;
SCIP_Bool ubadjust;
lbadjust = SCIPisGT(scip, newsolval, lb);
ubadjust = SCIPisLT(scip, newsolval, ub);
assert( lbadjust || ubadjust || SCIPisFeasEQ(scip, lb, ub));
/* enter a new probing node if the variable was not already fixed before */
if( lbadjust || ubadjust )
{
SCIP_RETCODE retcode;
if( SCIPisStopped(scip) )
break;
retcode = SCIPnewProbingNode(scip);
if( retcode == SCIP_MAXDEPTHLEVEL )
break;
SCIP_CALL( retcode );
/* tighten the bounds to fix the variable for the probing node */
if( lbadjust )
{
SCIP_CALL( SCIPchgVarLbProbing(scip, var, newsolval) );
}
if( ubadjust )
{
SCIP_CALL( SCIPchgVarUbProbing(scip, var, newsolval) );
}
/* call propagation routines for the reduced problem */
SCIP_CALL( SCIPpropagateProbing(scip, heurdata->maxproprounds, &cutoff, &ndomreds) );
}
}
/* store new solution value */
SCIP_CALL( SCIPsetSolVal(scip, sol, var, newsolval) );
}
/* if no cutoff was detected, the solution is a candidate to be checked for feasibility */
if( !cutoff && ! SCIPisStopped(scip) )
{
if( SCIPallColsInLP(scip) )
{
/* check solution for feasibility, and add it to solution store if possible
* neither integrality nor feasibility of LP rows has to be checked, because all fractional
* variables were already moved in feasible direction to the next integer
*/
SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, FALSE, TRUE, &stored) );
}
else
{
/* if there are variables which are not present in the LP, e.g., for
* column generation, we need to check their bounds
*/
SCIP_CALL( SCIPtrySol(scip, sol, FALSE, TRUE, 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;
}
}
assert( !propagate || SCIPinProbing(scip) );
/* exit probing mode and free locally allocated memory */
if( propagate )
{
SCIP_CALL( SCIPendProbing(scip) );
}
SCIPfreeBufferArray(scip, &permutedcands);
return SCIP_OKAY;
}
/** execution method of presolver */
static
SCIP_DECL_PRESOLEXEC(presolExecDualagg)
{ /*lint --e{715}*/
SCIPMILPMATRIX* matrix;
SCIP_Bool initialized;
SCIP_Bool complete;
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
if( (SCIPgetStage(scip) != SCIP_STAGE_PRESOLVING) || SCIPinProbing(scip) || SCIPisNLPEnabled(scip) )
return SCIP_OKAY;
if( SCIPisStopped(scip) || SCIPgetNActivePricers(scip) > 0 )
return SCIP_OKAY;
if( SCIPgetNBinVars(scip) == 0 )
return SCIP_OKAY;
if( !SCIPallowDualReds(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
matrix = NULL;
SCIP_CALL( SCIPmatrixCreate(scip, &matrix, &initialized, &complete) );
/* we only work on pure MIPs currently */
if( initialized && complete )
{
AGGRTYPE* aggtypes;
SCIP_VAR** binvars;
int nvaragg;
int ncols;
ncols = SCIPmatrixGetNColumns(matrix);
nvaragg = 0;
SCIP_CALL( SCIPallocBufferArray(scip, &aggtypes, ncols) );
BMSclearMemoryArray(aggtypes, ncols);
SCIP_CALL( SCIPallocBufferArray(scip, &binvars, ncols) );
SCIPdebug( BMSclearMemoryArray(binvars, ncols) );
/* search for aggregations */
SCIP_CALL( findUplockAggregations(scip, matrix, &nvaragg, aggtypes, binvars) );
SCIP_CALL( findDownlockAggregations(scip, matrix, &nvaragg, aggtypes, binvars) );
/* apply aggregations, if we found any */
if( nvaragg > 0 )
{
int v;
for( v = 0; v < ncols; v++ )
{
if( aggtypes[v] != NOAGG )
{
SCIP_Bool infeasible;
SCIP_Bool redundant;
SCIP_Bool aggregated;
SCIP_Real ub;
SCIP_Real lb;
ub = SCIPmatrixGetColUb(matrix, v);
lb = SCIPmatrixGetColLb(matrix, v);
/* aggregate variable */
assert(binvars[v] != NULL);
if( aggtypes[v] == BIN0UBOUND )
{
SCIP_CALL( SCIPaggregateVars(scip, SCIPmatrixGetVar(matrix, v), binvars[v], 1.0, ub-lb,
ub, &infeasible, &redundant, &aggregated) );
}
else
{
assert(aggtypes[v] == BIN0LBOUND);
SCIP_CALL( SCIPaggregateVars(scip, SCIPmatrixGetVar(matrix, v), binvars[v], 1.0, lb-ub,
lb, &infeasible, &redundant, &aggregated) );
}
/* infeasible aggregation */
if( infeasible )
{
SCIPdebugMessage(" -> infeasible aggregation\n");
*result = SCIP_CUTOFF;
return SCIP_OKAY;
}
if( aggregated )
(*naggrvars)++;
}
}
/* set result pointer */
if( (*naggrvars) > 0 )
*result = SCIP_SUCCESS;
}
SCIPfreeBufferArray(scip, &binvars);
SCIPfreeBufferArray(scip, &aggtypes);
}
SCIPmatrixFree(scip, &matrix);
return SCIP_OKAY;
}
/** creates and captures a origbranch constraint */
SCIP_RETCODE GCGcreateConsOrigbranch(
SCIP* scip, /**< SCIP data structure */
SCIP_CONS** cons, /**< pointer to hold the created constraint */
const char* name, /**< name of constraint */
SCIP_NODE* node, /**< the node to which this origbranch constraint belongs */
SCIP_CONS* parentcons, /**< origbranch constraint associated with the father node */
SCIP_BRANCHRULE* branchrule, /**< the branching rule that created the b&b node the constraint belongs to */
GCG_BRANCHDATA* branchdata /**< branching data storing information about the branching restrictions at the
* corresponding node */
)
{
SCIP_CONSHDLR* conshdlr;
SCIP_CONSDATA* consdata;
assert(scip != NULL);
assert((parentcons == NULL) == (node == NULL));
/* find the origbranch constraint handler */
conshdlr = SCIPfindConshdlr(scip, CONSHDLR_NAME);
if( conshdlr == NULL )
{
SCIPerrorMessage("origbranch constraint handler not found\n");
return SCIP_PLUGINNOTFOUND;
}
/* create constraint data */
SCIP_CALL( SCIPallocBlockMemory(scip, &consdata) );
/* initialize the fields in the constraint data */
consdata->parentcons = parentcons;
consdata->node = node;
consdata->child1cons = NULL;
consdata->child2cons = NULL;
consdata->probingtmpcons = NULL;
consdata->mastercons = NULL;
consdata->branchrule = branchrule;
consdata->branchdata = branchdata;
consdata->npropbounds = 0;
consdata->maxpropbounds = 0;
consdata->propvars = NULL;
consdata->propboundtypes = NULL;
consdata->propbounds = NULL;
SCIPdebugMessage("Creating branch orig constraint: <%s>.\n", name);
/* create constraint */
SCIP_CALL( SCIPcreateCons(scip, cons, name, conshdlr, consdata, FALSE, FALSE, FALSE, FALSE, FALSE,
TRUE, FALSE, FALSE, FALSE, TRUE) );
/* store the pointer to the new constraint in the origbranch constraint of the parent node */
if( parentcons != NULL )
{
SCIP_CONSDATA* parentdata;
parentdata = SCIPconsGetData(parentcons);
assert(parentdata != NULL);
if( parentdata->child1cons == NULL )
{
parentdata->child1cons = *cons;
}
else
{
assert(parentdata->child2cons == NULL || SCIPinProbing(scip));
/* store the second child in case we are in probing and have to overwrite it */
if( SCIPinProbing(scip) )
{
assert(parentdata->probingtmpcons == NULL);
parentdata->probingtmpcons = parentdata->child2cons;
}
parentdata->child2cons = *cons;
}
}
return SCIP_OKAY;
}
/** frees specific constraint data */
static
SCIP_DECL_CONSDELETE(consDeleteOrigbranch)
{ /*lint --e{715}*/
SCIP_CONSDATA* parentdata;
assert(scip != NULL);
assert(conshdlr != NULL);
assert(cons != NULL);
assert(consdata != NULL);
assert(strcmp(SCIPconshdlrGetName(conshdlr), CONSHDLR_NAME) == 0);
assert(*consdata != NULL);
SCIPdebugMessage("Deleting branch orig constraint: <%s>.\n", SCIPconsGetName(cons));
/* set the origcons pointer of the corresponding mastercons to NULL */
if( (*consdata)->mastercons != NULL )
GCGconsMasterbranchSetOrigcons((*consdata)->mastercons, NULL);
/* set the pointer in the parent constraint to NULL */
if( (*consdata)->parentcons != NULL )
{
parentdata = SCIPconsGetData((*consdata)->parentcons);
if( parentdata->child1cons == cons )
parentdata->child1cons = NULL;
else if( parentdata->probingtmpcons == cons )
{
assert(SCIPinProbing(scip));
parentdata->probingtmpcons = NULL;
}
else
{
assert(parentdata->child2cons == cons);
parentdata->child2cons = NULL;
if( SCIPinProbing(scip) )
{
parentdata->child2cons = parentdata->probingtmpcons;
parentdata->probingtmpcons = NULL;
}
}
}
/* no child nodes may exist */
assert((*consdata)->child1cons == NULL);
assert((*consdata)->child2cons == NULL);
/* delete branchdata, if no mastercons is linked, which would still need the branchdata
* otherwise, the mastercons deletes the branchdata when it is deleted itself */
if( (*consdata)->mastercons == NULL && (*consdata)->branchdata != NULL )
{
SCIP_CALL( GCGrelaxBranchDataDelete(scip, (*consdata)->branchrule, &(*consdata)->branchdata) );
}
/* free propagation domain changes arrays */
if( (*consdata)->maxpropbounds > 0 )
{
SCIPfreeMemoryArray(scip, &((*consdata)->propvars));
SCIPfreeMemoryArray(scip, &((*consdata)->propboundtypes));
SCIPfreeMemoryArray(scip, &((*consdata)->propbounds));
}
/* free constraint data */
SCIPfreeBlockMemory(scip, consdata);
return SCIP_OKAY;
}
/** process a variable from the queue of changed variables */
static
SCIP_RETCODE varProcessBoundChanges(
SCIP* scip, /**< SCIP data structure */
SCIP_HEURDATA* heurdata, /**< heuristic data */
SCIP_VAR* var /**< the variable whose bound changes need to be processed */
)
{
SCIP_ROW** colrows;
SCIP_COL* varcol;
SCIP_Real* colvals;
SCIP_Real oldmean;
SCIP_Real newmean;
SCIP_Real oldvariance;
SCIP_Real newvariance;
SCIP_Real oldlb;
SCIP_Real newlb;
SCIP_Real oldub;
SCIP_Real newub;
SCIP_VARTYPE vartype;
int ncolrows;
int r;
int varindex;
/* ensure that this is a probing bound change */
assert(SCIPinProbing(scip));
assert(var != NULL);
varcol = SCIPvarGetCol(var);
assert(varcol != NULL);
colrows = SCIPcolGetRows(varcol);
colvals = SCIPcolGetVals(varcol);
ncolrows = SCIPcolGetNNonz(varcol);
varindex = SCIPvarGetProbindex(var);
oldlb = heurdata->currentlbs[varindex];
oldub = heurdata->currentubs[varindex];
/* skip update if the variable has never been subject of previously calculated row activities */
assert((oldlb == SCIP_INVALID) == (oldub == SCIP_INVALID)); /*lint !e777 doesn't like comparing floats for equality */
if( oldlb == SCIP_INVALID ) /*lint !e777 */
return SCIP_OKAY;
newlb = SCIPvarGetLbLocal(var);
newub = SCIPvarGetUbLocal(var);
/* skip update if the bound change events have cancelled out */
if( SCIPisFeasEQ(scip, oldlb, newlb) && SCIPisFeasEQ(scip, oldub, newub) )
return SCIP_OKAY;
/* calculate old and new variable distribution mean and variance */
oldvariance = 0.0;
newvariance = 0.0;
oldmean = 0.0;
newmean = 0.0;
vartype = SCIPvarGetType(var);
SCIPvarCalcDistributionParameters(scip, oldlb, oldub, vartype, &oldmean, &oldvariance);
SCIPvarCalcDistributionParameters(scip, newlb, newub, vartype, &newmean, &newvariance);
/* loop over all rows of this variable and update activity distribution */
for( r = 0; r < ncolrows; ++r )
{
int rowpos;
assert(colrows[r] != NULL);
rowpos = SCIProwGetIndex(colrows[r]);
assert(rowpos >= 0);
SCIP_CALL( heurdataEnsureArraySize(scip, heurdata, rowpos) );
/* only consider rows for which activity distribution was already calculated */
if( heurdata->rowmeans[rowpos] != SCIP_INVALID ) /*lint !e777 doesn't like comparing floats for equality */
{
SCIP_Real coeff;
SCIP_Real coeffsquared;
assert(heurdata->rowvariances[rowpos] != SCIP_INVALID
&& SCIPisFeasGE(scip, heurdata->rowvariances[rowpos], 0.0)); /*lint !e777 */
coeff = colvals[r];
coeffsquared = SQUARED(coeff);
/* update variable contribution to row activity distribution */
heurdata->rowmeans[rowpos] += coeff * (newmean - oldmean);
heurdata->rowvariances[rowpos] += coeffsquared * (newvariance - oldvariance);
heurdata->rowvariances[rowpos] = MAX(0.0, heurdata->rowvariances[rowpos]);
/* account for changes of the infinite contributions to row activities */
if( coeff > 0.0 )
{
/* if the coefficient is positive, upper bounds affect activity up */
if( SCIPisInfinity(scip, newub) && !SCIPisInfinity(scip, oldub) )
++heurdata->rowinfinitiesup[rowpos];
else if( !SCIPisInfinity(scip, newub) && SCIPisInfinity(scip, oldub) )
--heurdata->rowinfinitiesup[rowpos];
if( SCIPisInfinity(scip, newlb) && !SCIPisInfinity(scip, oldlb) )
++heurdata->rowinfinitiesdown[rowpos];
else if( !SCIPisInfinity(scip, newlb) && SCIPisInfinity(scip, oldlb) )
--heurdata->rowinfinitiesdown[rowpos];
}
else if( coeff < 0.0 )
{
if( SCIPisInfinity(scip, newub) && !SCIPisInfinity(scip, oldub) )
++heurdata->rowinfinitiesdown[rowpos];
else if( !SCIPisInfinity(scip, newub) && SCIPisInfinity(scip, oldub) )
--heurdata->rowinfinitiesdown[rowpos];
if( SCIPisInfinity(scip, newlb) && !SCIPisInfinity(scip, oldlb) )
++heurdata->rowinfinitiesup[rowpos];
else if( !SCIPisInfinity(scip, newlb) && SCIPisInfinity(scip, oldlb) )
--heurdata->rowinfinitiesup[rowpos];
}
assert(heurdata->rowinfinitiesdown[rowpos] >= 0);
assert(heurdata->rowinfinitiesup[rowpos] >= 0);
}
}
/* store the new local bounds in the data */
heurdataUpdateCurrentBounds(scip, heurdata, var);
return SCIP_OKAY;
}
