/** propagate the given binary variable/column using the root reduced cost stored in the SCIP internal data structers
* and check if the implictions can be useful. Deppending on that implictions are used or not used during the search to
* strength the reduced costs.
*/
static
SCIP_RETCODE propagateRootRedcostBinvar(
SCIP* scip, /**< SCIP data structure */
SCIP_PROPDATA* propdata, /**< propagator data structure */
SCIP_VAR* var, /**< variable to use for propagation */
SCIP_COL* col, /**< LP column of the variable */
SCIP_Real cutoffbound, /**< the current cutoff bound */
int* nchgbds /**< pointer to count the number of bound changes */
)
{
SCIP_Real rootredcost;
SCIP_Real rootsol;
SCIP_Real rootlpobjval;
assert(SCIPgetDepth(scip) == 0);
/* skip binary variable if it is locally fixed */
if( SCIPvarGetLbLocal(var) > 0.5 || SCIPvarGetUbLocal(var) < 0.5 )
return SCIP_OKAY;
rootredcost = SCIPvarGetBestRootRedcost(var);
rootsol = SCIPvarGetBestRootSol(var);
rootlpobjval = SCIPvarGetBestRootLPObjval(var);
if( SCIPisFeasZero(scip, rootredcost) )
return SCIP_OKAY;
assert(rootlpobjval != SCIP_INVALID); /*lint !e777*/
if( rootsol > 0.5 )
{
assert(!SCIPisFeasPositive(scip, rootredcost));
/* update maximum reduced cost of a single binary variable */
propdata->maxredcost = MAX(propdata->maxredcost, -rootredcost);
if( rootlpobjval - rootredcost > cutoffbound )
{
SCIPdebugMessage("globally fix binary variable <%s> to 1.0\n", SCIPvarGetName(var));
SCIP_CALL( SCIPchgVarLb(scip, var, 1.0) );
(*nchgbds)++;
return SCIP_OKAY;
}
}
else
{
assert(!SCIPisFeasNegative(scip, rootredcost));
/* update maximum reduced cost of a single binary variable */
propdata->maxredcost = MAX(propdata->maxredcost, rootredcost);
if( rootlpobjval + rootredcost > cutoffbound )
{
SCIPdebugMessage("globally fix binary variable <%s> to 0.0\n", SCIPvarGetName(var));
SCIP_CALL( SCIPchgVarUb(scip, var, 0.0) );
(*nchgbds)++;
return SCIP_OKAY;
}
}
/* evaluate if the implications are useful; the implications are seen to be useful if they provide an increase for
* the root reduced costs
*/
if( !propdata->usefullimplics )
{
SCIP_Real lbredcost;
SCIP_Real ubredcost;
lbredcost = SCIPgetVarImplRedcost(scip, var, FALSE);
assert(!SCIPisFeasPositive(scip, lbredcost));
ubredcost = SCIPgetVarImplRedcost(scip, var, TRUE);
assert(!SCIPisFeasNegative(scip, ubredcost));
switch( SCIPcolGetBasisStatus(col) )
{
case SCIP_BASESTAT_LOWER:
ubredcost -= SCIPgetVarRedcost(scip, var);
assert(!SCIPisFeasNegative(scip, ubredcost));
break;
case SCIP_BASESTAT_UPPER:
lbredcost -= SCIPgetVarRedcost(scip, var);
assert(!SCIPisFeasPositive(scip, lbredcost));
break;
case SCIP_BASESTAT_BASIC:
case SCIP_BASESTAT_ZERO:
default:
break;
}
propdata->usefullimplics = (lbredcost < 0.0) || (ubredcost > 0.0);
}
return SCIP_OKAY;
}
/** separate */
static
SCIP_RETCODE sep_flow(
SCIP* scip, /**< SCIP data structure */
SCIP_CONSHDLR* conshdlr, /**< constraint handler */
SCIP_CONSHDLRDATA* conshdlrdata, /**< constraint handler data */
SCIP_CONSDATA* consdata, /**< constraint data */
int maxcuts, /**< maximal number of cuts */
int* ncuts /**< pointer to store number of cuts */
)
{
GRAPH* g;
SCIP_VAR** vars;
SCIP_ROW* row = NULL;
SCIP_Real* xval;
SCIP_Real sum;
int i;
int k;
int j;
int ind;
int layer;
int count = 0;
unsigned int flowsep;
assert(scip != NULL);
assert(conshdlr != NULL);
assert(conshdlrdata != NULL);
vars = SCIPprobdataGetVars(scip);
flowsep = conshdlrdata->flowsep;
/* get the graph */
g = consdata->graph;
assert(g != NULL);
xval = SCIPprobdataGetXval(scip, NULL);
assert(xval != NULL);
for(i = 0; i < g->knots; i++)
{
for(layer = 0; layer < g->layers; layer++)
{
/* continue at root */
if( i == g->source[layer] )
continue;
/* at terminal: input sum == 1
* basically a cut (starcut))
*/
if( g->term[i] == layer )
{
sum = 0.0;
for( k = g->inpbeg[i]; k != EAT_LAST; k = g->ieat[k] )
{
ind = layer * g->edges + k;
sum += (xval != NULL) ? xval[ind] : 0.0;
}
if( !SCIPisFeasEQ(scip, sum, 1.0) )
{
SCIP_Bool infeasible;
SCIP_CALL( SCIPcreateEmptyRowCons(scip, &row, conshdlr, "term", 1.0,
1.0, FALSE, FALSE, TRUE) );
SCIP_CALL( SCIPcacheRowExtensions(scip, row) );
for(k = g->inpbeg[i]; k != EAT_LAST; k = g->ieat[k])
{
ind = layer * g->edges + k;
SCIP_CALL( SCIPaddVarToRow(scip, row, vars[ind], 1.0) );
}
SCIP_CALL( SCIPflushRowExtensions(scip, row) );
SCIP_CALL( SCIPaddCut(scip, NULL, row, FALSE, &infeasible) );
count++;
SCIP_CALL( SCIPreleaseRow(scip, &row) );
if( *ncuts + count >= maxcuts )
goto TERMINATE;
}
}
/* no flows ? */
if( !flowsep )
continue;
/* the value of each outgoing edge needs to be smaller than the sum of the ingoing edges */
for( j = g->outbeg[i]; j != EAT_LAST; j = g->oeat[j] )
{
ind = layer * g->edges + j;
sum = (xval != NULL) ? -xval[ind] : -1.0;
for( k = g->inpbeg[i]; k != EAT_LAST; k = g->ieat[k] )
{
ind = layer * g->edges + k;
sum += (xval != NULL) ? xval[ind] : 0.0;
}
if( SCIPisFeasNegative(scip, sum) )
{
SCIP_Bool infeasible;
SCIP_CALL( SCIPcreateEmptyRowCons(scip, &row, conshdlr, "flow", 0.0, SCIPinfinity(scip),
FALSE, FALSE, TRUE) );
SCIP_CALL( SCIPcacheRowExtensions(scip, row) );
ind = layer * g->edges + j;
SCIP_CALL( SCIPaddVarToRow(scip, row, vars[ind], -1.0) );
for( k = g->inpbeg[i]; k != EAT_LAST; k = g->ieat[k] )
{
ind = layer * g->edges + k;
SCIP_CALL( SCIPaddVarToRow(scip, row, vars[ind], 1.0) );
}
SCIP_CALL( SCIPflushRowExtensions(scip, row) );
SCIP_CALL( SCIPaddCut(scip, NULL, row, FALSE, &infeasible) );
count++;
SCIP_CALL( SCIPreleaseRow(scip, &row) );
if( *ncuts + count >= maxcuts )
goto TERMINATE;
}
}
/* consider only non terminals */
if( g->term[i] == layer )
continue;
/* input of a vertex has to be <= 1.0 */
sum = 0.0;
for( k = g->inpbeg[i]; k != EAT_LAST; k = g->ieat[k] )
{
ind = layer * g->edges + k;
sum += (xval != NULL) ? xval[ind] : 1.0;
}
if( SCIPisFeasGT(scip, sum, 1.0) )
{
SCIP_Bool infeasible;
SCIP_CALL( SCIPcreateEmptyRowCons(scip, &row, conshdlr, "infl", -SCIPinfinity(scip),
1.0, FALSE, FALSE, TRUE) );
SCIP_CALL( SCIPcacheRowExtensions(scip, row) );
for( k = g->inpbeg[i]; k != EAT_LAST; k = g->ieat[k] )
{
ind = layer * g->edges + k;
SCIP_CALL( SCIPaddVarToRow(scip, row, vars[ind], 1.0) );
}
SCIP_CALL( SCIPflushRowExtensions(scip, row) );
SCIP_CALL( SCIPaddCut(scip, NULL, row, FALSE, &infeasible) );
count++;
SCIP_CALL( SCIPreleaseRow(scip, &row) );
if( *ncuts + count >= maxcuts )
goto TERMINATE;
}
/* incoming flow <= outgoing flow */
sum = 0.0;
for( k = g->inpbeg[i]; k != EAT_LAST; k = g->ieat[k] )
{
ind = layer * g->edges + k;
sum -= (xval != NULL) ? xval[ind] : 1.0;
}
for( k = g->outbeg[i]; k != EAT_LAST; k = g->oeat[k] )
{
ind = layer * g->edges + k;
sum += (xval != NULL) ? xval[ind] : 0.0;
}
if( SCIPisFeasNegative(scip, sum) )
{
SCIP_Bool infeasible;
SCIP_CALL( SCIPcreateEmptyRowCons(scip, &row, conshdlr, "bala", 0.0,
(g->locals[layer] == 2) ? 0.0 : SCIPinfinity(scip), FALSE, FALSE, TRUE) );
SCIP_CALL( SCIPcacheRowExtensions(scip, row) );
for( k = g->inpbeg[i]; k != EAT_LAST; k = g->ieat[k] )
{
ind = layer * g->edges + k;
SCIP_CALL( SCIPaddVarToRow(scip, row, vars[ind], -1.0) );
}
for( k = g->outbeg[i]; k != EAT_LAST; k = g->oeat[k] )
{
ind = layer * g->edges + k;
SCIP_CALL( SCIPaddVarToRow(scip, row, vars[ind], 1.0) );
}
SCIP_CALL( SCIPflushRowExtensions(scip, row) );
SCIP_CALL( SCIPaddCut(scip, NULL, row, FALSE, &infeasible) );
count++;
SCIP_CALL( SCIPreleaseRow(scip, &row) );
if( *ncuts + count >= maxcuts )
goto TERMINATE;
}
}
}
TERMINATE:
SCIPdebugMessage("In/Out Separator: %d Inequalities added\n", count);
*ncuts += count;
return SCIP_OKAY;
}
/** propagate the given binary variable/column using the reduced cost */
static
SCIP_RETCODE propagateRedcostBinvar(
SCIP* scip, /**< SCIP data structure */
SCIP_PROPDATA* propdata, /**< propagator data structure */
SCIP_VAR* var, /**< variable to use for propagation */
SCIP_COL* col, /**< LP column of the variable */
SCIP_Real requiredredcost, /**< required reduset cost to be able to fix a binary variable */
int* nchgbds, /**< pointer to count the number of bound changes */
SCIP_Bool* cutoff /**< pointer to store if an cutoff was detected */
)
{
SCIP_Real lbredcost;
SCIP_Real ubredcost;
SCIP_Real redcost;
/* skip binary variable if it is locally fixed */
if( SCIPvarGetLbLocal(var) > 0.5 || SCIPvarGetUbLocal(var) < 0.5 )
return SCIP_OKAY;
/* first use the redcost cost to fix the binary variable */
switch( SCIPcolGetBasisStatus(col) )
{
case SCIP_BASESTAT_LOWER:
redcost = SCIPgetVarRedcost(scip, var);
assert(!SCIPisFeasNegative(scip, redcost));
if( redcost > requiredredcost )
{
SCIPdebugMessage("variable <%s>: fixed 0.0 (requiredredcost <%g>, redcost <%g>)\n",
SCIPvarGetName(var), requiredredcost, redcost);
SCIP_CALL( SCIPchgVarUb(scip, var, 0.0) );
(*nchgbds)++;
return SCIP_OKAY;
}
break;
case SCIP_BASESTAT_UPPER:
redcost = SCIPgetVarRedcost(scip, var);
assert(!SCIPisFeasPositive(scip, redcost));
if( -redcost > requiredredcost )
{
SCIPdebugMessage("variable <%s>: fixed 1.0 (requiredredcost <%g>, redcost <%g>)\n",
SCIPvarGetName(var), requiredredcost, redcost);
SCIP_CALL( SCIPchgVarLb(scip, var, 1.0) );
(*nchgbds)++;
return SCIP_OKAY;
}
break;
case SCIP_BASESTAT_BASIC:
return SCIP_OKAY;
case SCIP_BASESTAT_ZERO:
assert(SCIPisFeasZero(scip, SCIPgetColRedcost(scip, col)));
return SCIP_OKAY;
default:
SCIPerrorMessage("invalid basis state\n");
return SCIP_INVALIDDATA;
}
/* second, if the implications should be used and if the implications are seen to be promising used the implied
* reduced costs to fix the binary variable
*/
if( propdata->useimplics && propdata->usefullimplics )
{
/* collect implied reduced costs if the variable would be fixed to its lower bound */
lbredcost = SCIPgetVarImplRedcost(scip, var, FALSE);
assert(!SCIPisFeasPositive(scip, lbredcost) || SCIPisFeasEQ(scip, SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var)) );
/* collect implied reduced costs if the variable would be fixed to its upper bound */
ubredcost = SCIPgetVarImplRedcost(scip, var, TRUE);
assert(!SCIPisFeasNegative(scip, ubredcost) || SCIPisFeasEQ(scip, SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var)) );
if( -lbredcost > requiredredcost && ubredcost > requiredredcost )
{
SCIPdebugMessage("variable <%s>: cutoff (requiredredcost <%g>, lbredcost <%g>, ubredcost <%g>)\n",
SCIPvarGetName(var), requiredredcost, lbredcost, ubredcost);
(*cutoff) = TRUE;
}
else if( -lbredcost > requiredredcost )
{
SCIPdebugMessage("variable <%s>: fixed 1.0 (requiredredcost <%g>, redcost <%g>, lbredcost <%g>)\n",
SCIPvarGetName(var), requiredredcost, redcost, lbredcost);
SCIP_CALL( SCIPchgVarLb(scip, var, 1.0) );
(*nchgbds)++;
}
else if( ubredcost > requiredredcost )
{
SCIPdebugMessage("variable <%s>: fixed 0.0 (requiredredcost <%g>, redcost <%g>, ubredcost <%g>)\n",
SCIPvarGetName(var), requiredredcost, redcost, ubredcost);
SCIP_CALL( SCIPchgVarUb(scip, var, 0.0) );
(*nchgbds)++;
}
/* update maximum reduced cost of a single binary variable */
propdata->maxredcost = MAX3(propdata->maxredcost, -lbredcost, ubredcost);
}
return SCIP_OKAY;
}
/** propagate the given none binary variable/column using the reduced cost */
static
SCIP_RETCODE propagateRedcostVar(
SCIP* scip, /**< SCIP data structure */
SCIP_VAR* var, /**< variable to use for propagation */
SCIP_COL* col, /**< LP column of the variable */
SCIP_Real lpobjval, /**< objective value of the current LP */
SCIP_Real cutoffbound, /**< the current cutoff bound */
int* nchgbds /**< pointer to count the number of bound changes */
)
{
SCIP_Real redcost;
switch( SCIPcolGetBasisStatus(col) )
{
case SCIP_BASESTAT_LOWER:
redcost = SCIPgetColRedcost(scip, col);
assert(!SCIPisFeasNegative(scip, redcost) || SCIPisFeasEQ(scip, SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var)) );
if( SCIPisFeasPositive(scip, redcost) )
{
SCIP_Real oldlb;
SCIP_Real oldub;
oldlb = SCIPvarGetLbLocal(var);
oldub = SCIPvarGetUbLocal(var);
assert(SCIPisEQ(scip, oldlb, SCIPcolGetLb(col)));
assert(SCIPisEQ(scip, oldub, SCIPcolGetUb(col)));
if( SCIPisFeasLT(scip, oldlb, oldub) )
{
SCIP_Real newub;
SCIP_Bool strengthen;
/* calculate reduced cost based bound */
newub = (cutoffbound - lpobjval) / redcost + oldlb;
/* check, if new bound is good enough:
* - integer variables: take all possible strengthenings
* - continuous variables: strengthening must cut part of the variable's dynamic range, and
* at least 20% of the current domain
*/
if( SCIPvarIsIntegral(var) )
{
newub = SCIPadjustedVarUb(scip, var, newub);
strengthen = (newub < oldub - 0.5);
}
else
strengthen = (newub < SCIPcolGetMaxPrimsol(col) && newub <= 0.2 * oldlb + 0.8 * oldub);
if( strengthen )
{
/* strengthen upper bound */
SCIPdebugMessage("redcost strengthening upper bound: <%s> [%g,%g] -> [%g,%g] (ub=%g, lb=%g, redcost=%g)\n",
SCIPvarGetName(var), oldlb, oldub, oldlb, newub, cutoffbound, lpobjval, redcost);
SCIP_CALL( SCIPchgVarUb(scip, var, newub) );
(*nchgbds)++;
}
}
}
break;
case SCIP_BASESTAT_BASIC:
break;
case SCIP_BASESTAT_UPPER:
redcost = SCIPgetColRedcost(scip, col);
assert(!SCIPisFeasPositive(scip, redcost) || SCIPisFeasEQ(scip, SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var)) );
if( SCIPisFeasNegative(scip, redcost) )
{
SCIP_Real oldlb;
SCIP_Real oldub;
oldlb = SCIPvarGetLbLocal(var);
oldub = SCIPvarGetUbLocal(var);
assert(SCIPisEQ(scip, oldlb, SCIPcolGetLb(col)));
assert(SCIPisEQ(scip, oldub, SCIPcolGetUb(col)));
if( SCIPisFeasLT(scip, oldlb, oldub) )
{
SCIP_Real newlb;
SCIP_Bool strengthen;
/* calculate reduced cost based bound */
newlb = (cutoffbound - lpobjval) / redcost + oldub;
/* check, if new bound is good enough:
* - integer variables: take all possible strengthenings
* - continuous variables: strengthening must cut part of the variable's dynamic range, and
* at least 20% of the current domain
*/
if( SCIPvarIsIntegral(var) )
{
newlb = SCIPadjustedVarLb(scip, var, newlb);
strengthen = (newlb > oldlb + 0.5);
}
else
strengthen = (newlb > SCIPcolGetMinPrimsol(col) && newlb >= 0.8 * oldlb + 0.2 * oldub);
/* check, if new bound is good enough: at least 20% strengthening for continuous variables */
if( strengthen )
{
/* strengthen lower bound */
SCIPdebugMessage("redcost strengthening lower bound: <%s> [%g,%g] -> [%g,%g] (ub=%g, lb=%g, redcost=%g)\n",
SCIPvarGetName(var), oldlb, oldub, newlb, oldub, cutoffbound, lpobjval, redcost);
SCIP_CALL( SCIPchgVarLb(scip, var, newlb) );
(*nchgbds)++;
}
}
}
break;
case SCIP_BASESTAT_ZERO:
assert(SCIPisFeasZero(scip, SCIPgetColRedcost(scip, col)));
break;
default:
SCIPerrorMessage("invalid basis state\n");
return SCIP_INVALIDDATA;
}
return SCIP_OKAY;
}
/** returns a score value for the given variable based on the active constraints that the variable appears in */
static
SCIP_Real getNActiveConsScore(
SCIP* scip, /**< SCIP data structure */
SCIP_VAR* var, /**< variable to get the score value for */
SCIP_Real* downscore, /**< pointer to store the score for branching downwards */
SCIP_Real* upscore /**< pointer to store the score for branching upwards */
)
{
SCIP_COL* col;
SCIP_ROW** rows;
SCIP_Real* vals;
int nrows;
int r;
int nactrows;
SCIP_Real downcoefsum;
SCIP_Real upcoefsum;
SCIP_Real score;
assert(downscore != NULL);
assert(upscore != NULL);
*downscore = 0.0;
*upscore = 0.0;
if( SCIPvarGetStatus(var) != SCIP_VARSTATUS_COLUMN )
return 0.0;
col = SCIPvarGetCol(var);
assert(col != NULL);
rows = SCIPcolGetRows(col);
vals = SCIPcolGetVals(col);
nrows = SCIPcolGetNLPNonz(col);
nactrows = 0;
downcoefsum = 0.0;
upcoefsum = 0.0;
for( r = 0; r < nrows; ++r )
{
SCIP_Real activity;
SCIP_Real lhs;
SCIP_Real rhs;
SCIP_Real dualsol;
/* calculate number of active constraint sides, i.e., count equations as two */
lhs = SCIProwGetLhs(rows[r]);
rhs = SCIProwGetRhs(rows[r]);
activity = SCIPgetRowLPActivity(scip, rows[r]);
dualsol = SCIProwGetDualsol(rows[r]);
if( SCIPisFeasEQ(scip, activity, lhs) )
{
SCIP_Real coef;
nactrows++;
coef = vals[r] / SCIProwGetNorm(rows[r]);
if( SCIPisFeasPositive(scip, dualsol) )
{
if( coef > 0.0 )
downcoefsum += coef;
else
upcoefsum -= coef;
}
}
else if( SCIPisFeasEQ(scip, activity, rhs) )
{
SCIP_Real coef;
nactrows++;
coef = vals[r] / SCIProwGetNorm(rows[r]);
if( SCIPisFeasNegative(scip, dualsol) )
{
if( coef > 0.0 )
upcoefsum += coef;
else
downcoefsum -= coef;
}
}
}
score = 1e-3*nactrows + (downcoefsum + 1e-6) * (upcoefsum + 1e-6);
*downscore = -downcoefsum;
*upscore = -upcoefsum;
return score;
}
/** transforms given solution of the master problem into solution of the original problem
* @todo think about types of epsilons used in this method
*/
SCIP_RETCODE GCGrelaxTransformMastersolToOrigsol(
SCIP* scip, /**< SCIP data structure */
SCIP_SOL* mastersol, /**< solution of the master problem, or NULL for current LP solution */
SCIP_SOL** origsol /**< pointer to store the new created original problem's solution */
)
{
SCIP* masterprob;
int npricingprobs;
int* blocknrs;
SCIP_Real* blockvalue;
SCIP_Real increaseval;
SCIP_VAR** mastervars;
SCIP_Real* mastervals;
int nmastervars;
SCIP_VAR** vars;
int nvars;
SCIP_Real feastol;
int i;
int j;
assert(scip != NULL);
assert(origsol != NULL);
masterprob = GCGrelaxGetMasterprob(scip);
npricingprobs = GCGrelaxGetNPricingprobs(scip);
assert( !SCIPisInfinity(scip, SCIPgetSolOrigObj(masterprob, mastersol)) );
SCIP_CALL( SCIPcreateSol(scip, origsol, GCGrelaxGetProbingheur(scip)) );
SCIP_CALL( SCIPallocBufferArray(scip, &blockvalue, npricingprobs) );
SCIP_CALL( SCIPallocBufferArray(scip, &blocknrs, npricingprobs) );
/* get variables of the master problem and their solution values */
SCIP_CALL( SCIPgetVarsData(masterprob, &mastervars, &nmastervars, NULL, NULL, NULL, NULL) );
assert(mastervars != NULL);
assert(nmastervars >= 0);
SCIP_CALL( SCIPallocBufferArray(scip, &mastervals, nmastervars) );
SCIP_CALL( SCIPgetSolVals(masterprob, mastersol, nmastervars, mastervars, mastervals) );
/* initialize the block values for the pricing problems */
for( i = 0; i < npricingprobs; i++ )
{
blockvalue[i] = 0.0;
blocknrs[i] = 0;
}
/* loop over all given master variables */
for( i = 0; i < nmastervars; i++ )
{
SCIP_VAR** origvars;
int norigvars;
SCIP_Real* origvals;
SCIP_Bool isray;
int blocknr;
origvars = GCGmasterVarGetOrigvars(mastervars[i]);
norigvars = GCGmasterVarGetNOrigvars(mastervars[i]);
origvals = GCGmasterVarGetOrigvals(mastervars[i]);
blocknr = GCGvarGetBlock(mastervars[i]);
isray = GCGmasterVarIsRay(mastervars[i]);
assert(GCGvarIsMaster(mastervars[i]));
assert(!SCIPisFeasNegative(scip, mastervals[i]));
/** @todo handle infinite master solution values */
assert(!SCIPisInfinity(scip, mastervals[i]));
/* first of all, handle variables representing rays */
if( isray )
{
assert(blocknr >= 0);
/* we also want to take into account variables representing rays, that have a small value (between normal and feas eps),
* so we do no feas comparison here */
if( SCIPisPositive(scip, mastervals[i]) )
{
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
if( SCIPisZero(scip, origvals[j]) )
break;
assert(!SCIPisZero(scip, origvals[j]));
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done later) */
if( GCGvarIsLinking(origvars[j]) )
continue;
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[j]), origvals[j] * mastervals[i], SCIPvarGetName(mastervars[i]));
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[j], origvals[j] * mastervals[i]) );
}
}
mastervals[i] = 0.0;
continue;
}
/* handle the variables with value >= 1 to get integral values in original solution */
while( SCIPisFeasGE(scip, mastervals[i], 1.0) )
{
/* variable was directly transferred to the master problem (only in linking conss or linking variable) */
/** @todo this may be the wrong place for this case, handle it before the while loop
* and remove the similar case in the next while loop */
if( blocknr == -1 )
{
assert(norigvars == 1);
assert(origvals[0] == 1.0);
/* increase the corresponding value */
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[0]), origvals[0] * mastervals[i], SCIPvarGetName(mastervars[i]));
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[0], origvals[0] * mastervals[i]) );
mastervals[i] = 0.0;
}
else
{
assert(blocknr >= 0);
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
SCIP_VAR* pricingvar;
int norigpricingvars;
SCIP_VAR** origpricingvars;
if( SCIPisZero(scip, origvals[j]) )
break;
assert(!SCIPisZero(scip, origvals[j]));
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done above) */
if( GCGvarIsLinking(origvars[j]) )
continue;
pricingvar = GCGoriginalVarGetPricingVar(origvars[j]);
assert(GCGvarIsPricing(pricingvar));
norigpricingvars = GCGpricingVarGetNOrigvars(pricingvar);
origpricingvars = GCGpricingVarGetOrigvars(pricingvar);
/* just in case a variable has a value higher than the number of blocks, it represents */
if( norigpricingvars <= blocknrs[blocknr] )
{
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[norigpricingvars-1]), mastervals[i] * origvals[j], SCIPvarGetName(mastervars[i]));
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[norigpricingvars-1], mastervals[i] * origvals[j]) );
mastervals[i] = 1.0;
}
/* this should be default */
else
{
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[blocknrs[blocknr]]), origvals[j], SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[blocknrs[blocknr]], origvals[j]) );
}
}
mastervals[i] = mastervals[i] - 1.0;
blocknrs[blocknr]++;
}
}
}
/* loop over all given master variables */
for( i = 0; i < nmastervars; i++ )
{
SCIP_VAR** origvars;
int norigvars;
SCIP_Real* origvals;
int blocknr;
origvars = GCGmasterVarGetOrigvars(mastervars[i]);
norigvars = GCGmasterVarGetNOrigvars(mastervars[i]);
origvals = GCGmasterVarGetOrigvals(mastervars[i]);
blocknr = GCGvarGetBlock(mastervars[i]);
if( SCIPisFeasZero(scip, mastervals[i]) )
{
continue;
}
assert(SCIPisFeasGE(scip, mastervals[i], 0.0) && SCIPisFeasLT(scip, mastervals[i], 1.0));
while( SCIPisFeasPositive(scip, mastervals[i]) )
{
assert(GCGvarIsMaster(mastervars[i]));
assert(!GCGmasterVarIsRay(mastervars[i]));
if( blocknr == -1 )
{
assert(norigvars == 1);
assert(origvals[0] == 1.0);
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[0]), origvals[0] * mastervals[i], SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[0], origvals[0] * mastervals[i]) );
mastervals[i] = 0.0;
}
else
{
increaseval = MIN(mastervals[i], 1.0 - blockvalue[blocknr]);
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
SCIP_VAR* pricingvar;
int norigpricingvars;
SCIP_VAR** origpricingvars;
if( SCIPisZero(scip, origvals[j]) )
continue;
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done above) */
if( GCGvarIsLinking(origvars[j]) )
continue;
pricingvar = GCGoriginalVarGetPricingVar(origvars[j]);
assert(GCGvarIsPricing(pricingvar));
norigpricingvars = GCGpricingVarGetNOrigvars(pricingvar);
origpricingvars = GCGpricingVarGetOrigvars(pricingvar);
if( norigpricingvars <= blocknrs[blocknr] )
{
increaseval = mastervals[i];
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[norigpricingvars-1]), origvals[j] * increaseval, SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[norigpricingvars-1], origvals[j] * increaseval) );
}
else
{
/* increase the corresponding value */
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[blocknrs[blocknr]]), origvals[j] * increaseval, SCIPvarGetName(mastervars[i]) );
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[blocknrs[blocknr]], origvals[j] * increaseval) );
}
}
mastervals[i] = mastervals[i] - increaseval;
if( SCIPisFeasZero(scip, mastervals[i]) )
{
mastervals[i] = 0.0;
}
blockvalue[blocknr] += increaseval;
/* if the value assigned to the block is equal to 1, this block is full and we take the next block */
if( SCIPisFeasGE(scip, blockvalue[blocknr], 1.0) )
{
blockvalue[blocknr] = 0.0;
blocknrs[blocknr]++;
}
}
}
}
SCIPfreeBufferArray(scip, &mastervals);
SCIPfreeBufferArray(scip, &blocknrs);
SCIPfreeBufferArray(scip, &blockvalue);
/* if the solution violates one of its bounds by more than feastol
* and less than 10*feastol, round it and print a warning
*/
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPgetRealParam(scip, "numerics/feastol", &feastol) );
for( i = 0; i < nvars; ++i )
{
SCIP_Real solval;
SCIP_Real lb;
SCIP_Real ub;
solval = SCIPgetSolVal(scip, *origsol, vars[i]);
lb = SCIPvarGetLbLocal(vars[i]);
ub = SCIPvarGetUbLocal(vars[i]);
if( SCIPisFeasGT(scip, solval, ub) && EPSEQ(solval, ub, 10 * feastol) )
{
SCIP_CALL( SCIPsetSolVal(scip, *origsol, vars[i], ub) );
SCIPwarningMessage(scip, "Variable %s rounded from %g to %g in relaxation solution\n",
SCIPvarGetName(vars[i]), solval, ub);
}
else if( SCIPisFeasLT(scip, solval, lb) && EPSEQ(solval, lb, 10 * feastol) )
{
SCIP_CALL( SCIPsetSolVal(scip, *origsol, vars[i], lb) );
SCIPwarningMessage(scip, "Variable %s rounded from %g to %g in relaxation solution\n",
SCIPvarGetName(vars[i]), solval, lb);
}
}
return SCIP_OKAY;
}
/** when a variable is shifted, the activities and slacks of all rows it appears in have to be updated */
static
SCIP_RETCODE updateSlacks(
SCIP* scip, /**< pointer to current SCIP data structure */
SCIP_SOL* sol, /**< working solution */
SCIP_VAR* var, /**< pointer to variable to be modified */
SCIP_Real shiftvalue, /**< the value by which the variable is shifted */
SCIP_Real* upslacks, /**< upslacks of all rows the variable appears in */
SCIP_Real* downslacks, /**< downslacks of all rows the variable appears in */
SCIP_Real* activities, /**< activities of the LP rows */
SCIP_VAR** slackvars, /**< the slack variables for equality rows */
SCIP_Real* slackcoeffs, /**< the slack variable coefficients */
int nslacks /**< size of the arrays */
)
{
SCIP_COL* col; /* the corresponding column of variable var */
SCIP_ROW** rows; /* pointer to the nonzero coefficient rows for variable var */
int nrows; /* the number of nonzeros */
SCIP_Real* colvals; /* array to store the nonzero coefficients */
int i;
assert(scip != NULL);
assert(sol != NULL);
assert(var != NULL);
assert(upslacks != NULL);
assert(downslacks != NULL);
assert(activities != NULL);
assert(nslacks >= 0);
col = SCIPvarGetCol(var);
assert(col != NULL);
rows = SCIPcolGetRows(col);
nrows = SCIPcolGetNLPNonz(col);
colvals = SCIPcolGetVals(col);
assert(nrows == 0 || (rows != NULL && colvals != NULL));
/* go through all rows the shifted variable appears in */
for( i = 0; i < nrows; ++i )
{
int rowpos;
rowpos = SCIProwGetLPPos(rows[i]);
assert(-1 <= rowpos && rowpos < nslacks);
/* if the row is in the LP, update its activity, up and down slack */
if( rowpos >= 0 )
{
SCIP_Real val;
val = colvals[i] * shiftvalue;
/* if the row is an equation, we update its slack variable instead of its activities */
if( SCIPisFeasEQ(scip, SCIProwGetLhs(rows[i]), SCIProwGetRhs(rows[i])) )
{
SCIP_Real slackvarshiftval;
SCIP_Real slackvarsolval;
assert(slackvars[rowpos] != NULL);
assert(!SCIPisFeasZero(scip, slackcoeffs[rowpos]));
slackvarsolval = SCIPgetSolVal(scip, sol, slackvars[rowpos]);
slackvarshiftval = -val / slackcoeffs[rowpos];
assert(SCIPisFeasGE(scip, slackvarsolval + slackvarshiftval, SCIPvarGetLbGlobal(slackvars[rowpos])));
assert(SCIPisFeasLE(scip, slackvarsolval + slackvarshiftval, SCIPvarGetUbGlobal(slackvars[rowpos])));
SCIP_CALL( SCIPsetSolVal(scip, sol, slackvars[rowpos], slackvarsolval + slackvarshiftval) );
}
else if( !SCIPisInfinity(scip, -activities[rowpos]) && !SCIPisInfinity(scip, activities[rowpos]) )
activities[rowpos] += val;
/* the slacks of the row now can be updated independently of its type */
if( !SCIPisInfinity(scip, upslacks[rowpos]) )
upslacks[rowpos] -= val;
if( !SCIPisInfinity(scip, -downslacks[rowpos]) )
downslacks[rowpos] += val;
assert(!SCIPisFeasNegative(scip, upslacks[rowpos]));
assert(!SCIPisFeasNegative(scip, downslacks[rowpos]));
}
}
return SCIP_OKAY;
}
/** returns a score value for the given variable based on the active constraints that the variable appears in */
static
SCIP_Real getNActiveConsScore(
SCIP* scip, /**< SCIP data structure */
SCIP_SOL* sol, /**< working solution */
SCIP_VAR* var, /**< variable to get the score value for */
SCIP_Real* downscore, /**< pointer to store the score for branching downwards */
SCIP_Real* upscore /**< pointer to store the score for branching upwards */
)
{
SCIP_COL* col;
SCIP_ROW** rows;
SCIP_Real* vals;
int nrows;
int r;
int nactrows;
SCIP_Real nlprows;
SCIP_Real downcoefsum;
SCIP_Real upcoefsum;
SCIP_Real score;
assert(downscore != NULL);
assert(upscore != NULL);
*downscore = 0.0;
*upscore = 0.0;
if( SCIPvarGetStatus(var) != SCIP_VARSTATUS_COLUMN )
return 0.0;
col = SCIPvarGetCol(var);
assert(col != NULL);
rows = SCIPcolGetRows(col);
vals = SCIPcolGetVals(col);
nrows = SCIPcolGetNLPNonz(col);
nactrows = 0;
downcoefsum = 0.0;
upcoefsum = 0.0;
for( r = 0; r < nrows; ++r )
{
SCIP_ROW* row;
SCIP_Real activity;
SCIP_Real lhs;
SCIP_Real rhs;
SCIP_Real dualsol;
row = rows[r];
/* calculate number of active constraint sides, i.e., count equations as two */
lhs = SCIProwGetLhs(row);
rhs = SCIProwGetRhs(row);
/* @todo this is suboptimal because activity is calculated by looping over all nonzeros of this row, need to
* store LP activities instead (which cannot be retrieved if no LP was solved at this node)
*/
activity = SCIPgetRowSolActivity(scip, row, sol);
dualsol = SCIProwGetDualsol(row);
if( SCIPisFeasEQ(scip, activity, lhs) )
{
SCIP_Real coef;
nactrows++;
coef = vals[r] / SCIProwGetNorm(row);
if( SCIPisFeasPositive(scip, dualsol) )
{
if( coef > 0.0 )
downcoefsum += coef;
else
upcoefsum -= coef;
}
}
else if( SCIPisFeasEQ(scip, activity, rhs) )
{
SCIP_Real coef;
nactrows++;
coef = vals[r] / SCIProwGetNorm(row);
if( SCIPisFeasNegative(scip, dualsol) )
{
if( coef > 0.0 )
upcoefsum += coef;
else
downcoefsum -= coef;
}
}
}
/* use the number of LP rows for normalization */
nlprows = (SCIP_Real)SCIPgetNLPRows(scip);
upcoefsum /= nlprows;
downcoefsum /= nlprows;
/* calculate the score using SCIP's branch score. Pass NULL as variable to not have the var branch factor influence
* the result
*/
score = nactrows / nlprows + SCIPgetBranchScore(scip, NULL, downcoefsum, upcoefsum);
assert(score <= 3.0);
assert(score >= 0.0);
*downscore = downcoefsum;
*upscore = upcoefsum;
return score;
}
/** 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);
}
/** 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;
}
