/** find variable aggregations for downlock case */
static
SCIP_RETCODE findDownlockAggregations(
SCIP* scip, /**< SCIP main data structure */
SCIPMILPMATRIX* matrix, /**< constraint matrix */
int* nvaragg, /**< number of redundant variables */
AGGRTYPE* aggtypes, /**< type of aggregations (in same order as variables in matrix) */
SCIP_VAR** binvars /**< pointers to the binary variables (in same order as variables in matrix) */
)
{
int nvars;
int i;
assert(scip != NULL);
assert(matrix != NULL);
assert(nvaragg != NULL);
assert(aggtypes != NULL);
assert(binvars != NULL);
nvars = SCIPmatrixGetNColumns(matrix);
for( i = 0; i < nvars; i++ )
{
/* column has only one downlock which keeps it from being fixed by duality fixing;
* only handle variable if it was not yet aggregated due to a single uplock
*/
if( SCIPmatrixGetColNDownlocks(matrix, i) == 1 &&
SCIPisGE(scip, SCIPvarGetObj(SCIPmatrixGetVar(matrix, i)), 0.0) &&
aggtypes[i] == NOAGG )
{
SCIP_Real lb;
SCIP_Real ub;
lb = SCIPmatrixGetColLb(matrix, i);
ub = SCIPmatrixGetColUb(matrix, i);
assert(lb == SCIPvarGetLbGlobal(SCIPmatrixGetVar(matrix, i))); /*lint !e777*/
assert(ub == SCIPvarGetUbGlobal(SCIPmatrixGetVar(matrix, i))); /*lint !e777*/
/* the variable needs to have finite bounds to allow an agregation */
if( !SCIPisInfinity(scip, -lb) && !SCIPisInfinity(scip, ub) )
{
int binvaridx;
AGGRTYPE aggtype;
getBinVarIdxInDownlockRow(scip, matrix, i, &binvaridx, &aggtype);
if( binvaridx >= 0 )
{
aggtypes[i] = aggtype;
binvars[i] = SCIPmatrixGetVar(matrix, binvaridx);
(*nvaragg)++;
}
}
}
}
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));
}
/** 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;
}
/** perform dual presolving */
static
SCIP_RETCODE performDualfix(
SCIP* scip, /**< SCIP data structure */
int* nfixedvars, /**< pointer to store number of fixed variables */
SCIP_Bool* unbounded, /**< pointer to store if an unboundness was detected */
SCIP_Bool* cutoff /**< pointer to store if a cutoff was detected */
)
{
SCIP_VAR** vars;
int nvars;
int v;
/* get active problem variables */
vars = SCIPgetVars(scip);
nvars = SCIPgetNVars(scip);
/* look for fixable variables
* loop backwards, since a variable fixing can change the current and the subsequent slots in the vars array
*/
for( v = nvars - 1; v >= 0; --v )
{
SCIP_VAR* var;
SCIP_Real bound;
SCIP_Real obj;
SCIP_Bool infeasible;
SCIP_Bool fixed;
var = vars[v];
assert(var != NULL);
/* don't perform dual presolving operations on deleted variables */
if( SCIPvarIsDeleted(var) )
continue;
/* ignore already fixed variables (use feasibility tolerance since this is used in SCIPfixVar() */
if( SCIPisFeasEQ(scip, SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var)) )
continue;
obj = SCIPvarGetObj(var);
/* if the objective coefficient of the variable is 0 and it may be rounded both
* up and down, then fix it to the closest feasible value to 0 */
if( SCIPisZero(scip, obj) && SCIPvarMayRoundDown(var) && SCIPvarMayRoundUp(var) )
{
SCIP_Real roundbound;
bound = SCIPvarGetLbGlobal(var);
if( SCIPisLT(scip, bound, 0.0) )
{
if( SCIPisLE(scip, 0.0, SCIPvarGetUbGlobal(var)) )
bound = 0.0;
else
{
/* try to take an integer value, only for polishing */
roundbound = SCIPfloor(scip, SCIPvarGetUbGlobal(var));
if( roundbound < bound )
bound = SCIPvarGetUbGlobal(var);
else
bound = roundbound;
}
}
else
{
/* try to take an integer value, only for polishing */
roundbound = SCIPceil(scip, bound);
if( roundbound < SCIPvarGetUbGlobal(var) )
bound = roundbound;
}
SCIPdebugMessage("fixing variable <%s> with objective 0 to %g\n", SCIPvarGetName(var), bound);
}
else
{
/* if it is always possible to round variable in direction of objective value, fix it to its proper bound */
if( SCIPvarMayRoundDown(var) && !SCIPisNegative(scip, obj) )
{
bound = SCIPvarGetLbGlobal(var);
if ( SCIPisInfinity(scip, -bound) )
{
/* variable can be fixed to -infinity */
if ( SCIPgetStage(scip) > SCIP_STAGE_PRESOLVING )
{
/* Fixing variables to infinity is not allowed after presolving, since LP-solvers cannot handle this
* consistently. We thus have to ignore this (should better be handled in presolving). */
continue;
}
if ( SCIPisZero(scip, obj) && SCIPvarGetNLocksUp(var) == 1 )
{
/* Variable is only contained in one constraint: we hope that the corresponding constraint handler is
* clever enough to set/aggregate the variable to something more useful than -infinity and do nothing
* here. */
continue;
}
}
SCIPdebugMessage("fixing variable <%s> with objective %g and %d uplocks to lower bound %g\n",
SCIPvarGetName(var), SCIPvarGetObj(var), SCIPvarGetNLocksUp(var), bound);
}
else if( SCIPvarMayRoundUp(var) && !SCIPisPositive(scip, obj) )
{
bound = SCIPvarGetUbGlobal(var);
if ( SCIPisInfinity(scip, bound) )
{
/* variable can be fixed to infinity */
if ( SCIPgetStage(scip) > SCIP_STAGE_PRESOLVING )
{
/* Fixing variables to infinity is not allowed after presolving, since LP-solvers cannot handle this
* consistently. We thus have to ignore this (should better be handled in presolving). */
continue;
}
if ( SCIPisZero(scip, obj) && SCIPvarGetNLocksDown(var) == 1 )
{
/* Variable is only contained in one constraint: we hope that the corresponding constraint handler is
* clever enough to set/aggregate the variable to something more useful than +infinity and do nothing
* here */
continue;
}
}
SCIPdebugMessage("fixing variable <%s> with objective %g and %d downlocks to upper bound %g\n",
SCIPvarGetName(var), SCIPvarGetObj(var), SCIPvarGetNLocksDown(var), bound);
}
else
continue;
}
if( SCIPisInfinity(scip, REALABS(bound)) && !SCIPisZero(scip, obj) )
{
SCIPdebugMessage(" -> unbounded fixing\n");
SCIPverbMessage(scip, SCIP_VERBLEVEL_NORMAL, NULL,
"problem infeasible or unbounded: variable <%s> with objective %.15g can be made infinitely %s\n",
SCIPvarGetName(var), SCIPvarGetObj(var), bound < 0.0 ? "small" : "large");
*unbounded = TRUE;
return SCIP_OKAY;
}
/* apply the fixing */
SCIPdebugMessage("apply fixing of variable %s to %g\n", SCIPvarGetName(var), bound);
SCIP_CALL( SCIPfixVar(scip, var, bound, &infeasible, &fixed) );
if( infeasible )
{
SCIPdebugMessage(" -> infeasible fixing\n");
*cutoff = TRUE;
return SCIP_OKAY;
}
assert(fixed || (SCIPgetStage(scip) == SCIP_STAGE_SOLVING && SCIPisFeasEQ(scip, bound, SCIPvarGetLbLocal(var))
&& SCIPisFeasEQ(scip, bound, SCIPvarGetUbLocal(var))));
(*nfixedvars)++;
}
return SCIP_OKAY;
}
/** creates the objective value inequality and the objective value variable, if not yet existing */
static
SCIP_RETCODE createObjRow(
SCIP* scip, /**< SCIP data structure */
SCIP_SEPA* sepa, /**< separator */
SCIP_SEPADATA* sepadata /**< separator data */
)
{
assert(sepadata != NULL);
if( sepadata->objrow == NULL )
{
SCIP_VAR** vars;
SCIP_Real obj;
SCIP_Real intobjval;
int nvars;
int v;
SCIP_Bool attendobjvarbound;
attendobjvarbound = FALSE;
/* create and add objective value variable */
if( sepadata->objvar == NULL )
{
SCIP_CALL( SCIPcreateVar(scip, &sepadata->objvar, "objvar", -SCIPinfinity(scip), SCIPinfinity(scip), 0.0,
SCIP_VARTYPE_IMPLINT, FALSE, TRUE, NULL, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPaddVar(scip, sepadata->objvar) );
SCIP_CALL( SCIPaddVarLocks(scip, sepadata->objvar, +1, +1) );
}
else
attendobjvarbound = TRUE;
/* get problem variables */
vars = SCIPgetOrigVars(scip);
nvars = SCIPgetNOrigVars(scip);
/* create objective value inequality */
if( SCIPgetObjsense(scip) == SCIP_OBJSENSE_MINIMIZE )
{
if( attendobjvarbound )
intobjval = SCIPceil(scip, SCIPgetDualbound(scip)) - SCIPvarGetLbGlobal(sepadata->objvar);
else
intobjval = SCIPceil(scip, SCIPgetDualbound(scip));
SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &sepadata->objrow, sepa, "objrow", intobjval, SCIPinfinity(scip),
FALSE, !SCIPallVarsInProb(scip), TRUE) );
sepadata->setoff = intobjval;
}
else
{
if( attendobjvarbound )
intobjval = SCIPceil(scip, SCIPgetDualbound(scip)) - SCIPvarGetUbGlobal(sepadata->objvar);
else
intobjval = SCIPfloor(scip, SCIPgetDualbound(scip));
SCIP_CALL( SCIPcreateEmptyRowSepa(scip, &sepadata->objrow, sepa, "objrow", -SCIPinfinity(scip), intobjval,
FALSE, !SCIPallVarsInProb(scip), TRUE) );
sepadata->setoff = intobjval;
}
SCIP_CALL( SCIPcacheRowExtensions(scip, sepadata->objrow) );
for( v = 0; v < nvars; ++v )
{
obj = SCIPvarGetObj(vars[v]);
if( !SCIPisZero(scip, obj) )
{
SCIP_CALL( SCIPaddVarToRow(scip, sepadata->objrow, vars[v], obj) );
}
}
SCIP_CALL( SCIPaddVarToRow(scip, sepadata->objrow, sepadata->objvar, -1.0) );
SCIP_CALL( SCIPflushRowExtensions(scip, sepadata->objrow) );
SCIPdebugMessage("created objective value row: ");
SCIPdebug( SCIP_CALL( SCIPprintRow(scip, sepadata->objrow, NULL) ) );
}
return SCIP_OKAY;
}
/** main procedure of the zeroobj heuristic, creates and solves a sub-SCIP */
SCIP_RETCODE SCIPapplyZeroobj(
SCIP* scip, /**< original SCIP data structure */
SCIP_HEUR* heur, /**< heuristic data structure */
SCIP_RESULT* result, /**< result data structure */
SCIP_Real minimprove, /**< factor by which zeroobj should at least improve the incumbent */
SCIP_Longint nnodes /**< node limit for the subproblem */
)
{
SCIP* subscip; /* the subproblem created by zeroobj */
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_VAR** vars; /* original problem's variables */
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_HEURDATA* heurdata; /* heuristic's private data structure */
SCIP_EVENTHDLR* eventhdlr; /* event handler for LP events */
SCIP_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real timelimit; /* time limit for zeroobj subproblem */
SCIP_Real memorylimit; /* memory limit for zeroobj subproblem */
SCIP_Real large;
int nvars; /* number of original problem's variables */
int i;
SCIP_Bool success;
SCIP_Bool valid;
SCIP_RETCODE retcode;
SCIP_SOL** subsols;
int nsubsols;
assert(scip != NULL);
assert(heur != NULL);
assert(result != NULL);
assert(nnodes >= 0);
assert(0.0 <= minimprove && minimprove <= 1.0);
*result = SCIP_DIDNOTRUN;
/* only call heuristic once at the root */
if( SCIPgetDepth(scip) <= 0 && SCIPheurGetNCalls(heur) > 0 )
return SCIP_OKAY;
/* get heuristic data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* only call the heuristic if we do not have an incumbent */
if( SCIPgetNSolsFound(scip) > 0 && heurdata->onlywithoutsol )
return SCIP_OKAY;
/* check whether there is enough time and memory left */
timelimit = 0.0;
memorylimit = 0.0;
SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
if( !SCIPisInfinity(scip, timelimit) )
timelimit -= SCIPgetSolvingTime(scip);
SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
/* substract the memory already used by the main SCIP and the estimated memory usage of external software */
if( !SCIPisInfinity(scip, memorylimit) )
{
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
}
/* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
/* get variable data */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* initialize the subproblem */
SCIP_CALL( SCIPcreate(&subscip) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
/* different methods to create sub-problem: either copy LP relaxation or the CIP with all constraints */
valid = FALSE;
/* copy complete SCIP instance */
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "zeroobj", TRUE, FALSE, TRUE, &valid) );
SCIPdebugMessage("Copying the SCIP instance was %s complete.\n", valid ? "" : "not ");
/* create event handler for LP events */
eventhdlr = NULL;
SCIP_CALL( SCIPincludeEventhdlrBasic(subscip, &eventhdlr, EVENTHDLR_NAME, EVENTHDLR_DESC, eventExecZeroobj, NULL) );
if( eventhdlr == NULL )
{
SCIPerrorMessage("event handler for "HEUR_NAME" heuristic not found.\n");
return SCIP_PLUGINNOTFOUND;
}
/* determine large value to set variables to */
large = SCIPinfinity(scip);
if( !SCIPisInfinity(scip, 0.1 / SCIPfeastol(scip)) )
large = 0.1 / SCIPfeastol(scip);
/* get variable image and change to 0.0 in sub-SCIP */
for( i = 0; i < nvars; i++ )
{
SCIP_Real adjustedbound;
SCIP_Real lb;
SCIP_Real ub;
SCIP_Real inf;
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
SCIP_CALL( SCIPchgVarObj(subscip, subvars[i], 0.0) );
lb = SCIPvarGetLbGlobal(subvars[i]);
ub = SCIPvarGetUbGlobal(subvars[i]);
inf = SCIPinfinity(subscip);
/* adjust infinite bounds in order to avoid that variables with non-zero objective
* get fixed to infinite value in zeroobj subproblem
*/
if( SCIPisInfinity(subscip, ub ) )
{
adjustedbound = MAX(large, lb+large);
adjustedbound = MIN(adjustedbound, inf);
SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], adjustedbound) );
}
if( SCIPisInfinity(subscip, -lb ) )
{
adjustedbound = MIN(-large, ub-large);
adjustedbound = MAX(adjustedbound, -inf);
SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], adjustedbound) );
}
}
/* free hash map */
SCIPhashmapFree(&varmapfw);
/* do not abort subproblem on CTRL-C */
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
/* disable output to console */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
/* set limits for the subproblem */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nnodes) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
SCIP_CALL( SCIPsetIntParam(subscip, "limits/solutions", 1) );
/* forbid recursive call of heuristics and separators solving sub-SCIPs */
SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
/* disable expensive techniques that merely work on the dual bound */
/* disable cutting plane separation */
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
/* disable expensive presolving */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );
if( !SCIPisParamFixed(subscip, "presolving/maxrounds") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "presolving/maxrounds", 50) );
}
/* use best dfs node selection */
if( SCIPfindNodesel(subscip, "dfs") != NULL && !SCIPisParamFixed(subscip, "nodeselection/dfs/stdpriority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/dfs/stdpriority", INT_MAX/4) );
}
/* use inference branching */
if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "branching/leastinf/priority", INT_MAX/4) );
}
/* employ a limit on the number of enforcement rounds in the quadratic constraint handler; this fixes the issue that
* sometimes the quadratic constraint handler needs hundreds or thousands of enforcement rounds to determine the
* feasibility status of a single node without fractional branching candidates by separation (namely for uflquad
* instances); however, the solution status of the sub-SCIP might get corrupted by this; hence no deductions shall be
* made for the original SCIP
*/
if( SCIPfindConshdlr(subscip, "quadratic") != NULL && !SCIPisParamFixed(subscip, "constraints/quadratic/enfolplimit") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "constraints/quadratic/enfolplimit", 10) );
}
/* disable feaspump and fracdiving */
if( !SCIPisParamFixed(subscip, "heuristics/feaspump/freq") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "heuristics/feaspump/freq", -1) );
}
if( !SCIPisParamFixed(subscip, "heuristics/fracdiving/freq") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "heuristics/fracdiving/freq", -1) );
}
/* restrict LP iterations */
SCIP_CALL( SCIPsetLongintParam(subscip, "lp/iterlim", 2*heurdata->maxlpiters / MAX(1,nnodes)) );
SCIP_CALL( SCIPsetLongintParam(subscip, "lp/rootiterlim", heurdata->maxlpiters) );
#ifdef SCIP_DEBUG
/* for debugging zeroobj, enable MIP output */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 5) );
SCIP_CALL( SCIPsetIntParam(subscip, "display/freq", 100000000) );
#endif
/* if there is already a solution, add an objective cutoff */
if( SCIPgetNSols(scip) > 0 )
{
SCIP_Real upperbound;
SCIP_CONS* origobjcons;
#ifndef NDEBUG
int nobjvars;
nobjvars = 0;
#endif
cutoff = SCIPinfinity(scip);
assert( !SCIPisInfinity(scip,SCIPgetUpperbound(scip)) );
upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
{
cutoff = (1-minimprove)*SCIPgetUpperbound(scip) + minimprove*SCIPgetLowerbound(scip);
}
else
{
if( SCIPgetUpperbound(scip) >= 0 )
cutoff = ( 1 - minimprove ) * SCIPgetUpperbound ( scip );
else
cutoff = ( 1 + minimprove ) * SCIPgetUpperbound ( scip );
}
cutoff = MIN(upperbound, cutoff);
SCIP_CALL( SCIPcreateConsLinear(subscip, &origobjcons, "objbound_of_origscip", 0, NULL, NULL, -SCIPinfinity(subscip), cutoff,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE) );
for( i = 0; i < nvars; ++i)
{
if( !SCIPisFeasZero(subscip, SCIPvarGetObj(vars[i])) )
{
SCIP_CALL( SCIPaddCoefLinear(subscip, origobjcons, subvars[i], SCIPvarGetObj(vars[i])) );
#ifndef NDEBUG
nobjvars++;
#endif
}
}
SCIP_CALL( SCIPaddCons(subscip, origobjcons) );
SCIP_CALL( SCIPreleaseCons(subscip, &origobjcons) );
assert(nobjvars == SCIPgetNObjVars(scip));
}
/* catch LP events of sub-SCIP */
SCIP_CALL( SCIPtransformProb(subscip) );
SCIP_CALL( SCIPcatchEvent(subscip, SCIP_EVENTTYPE_NODESOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, NULL) );
SCIPdebugMessage("solving subproblem: nnodes=%"SCIP_LONGINT_FORMAT"\n", nnodes);
retcode = SCIPsolve(subscip);
/* drop LP events of sub-SCIP */
SCIP_CALL( SCIPdropEvent(subscip, SCIP_EVENTTYPE_NODESOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, -1) );
/* errors in solving the subproblem should not kill the overall solving process;
* hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage(scip, "Error while solving subproblem in zeroobj heuristic; sub-SCIP terminated with code <%d>\n",retcode);
}
/* check, whether a solution was found;
* due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
*/
nsubsols = SCIPgetNSols(subscip);
subsols = SCIPgetSols(subscip);
success = FALSE;
for( i = 0; i < nsubsols && (!success || heurdata->addallsols); ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
if( success )
*result = SCIP_FOUNDSOL;
}
#ifdef SCIP_DEBUG
SCIP_CALL( SCIPprintStatistics(subscip, NULL) );
#endif
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/** presolving execution method */
static
SCIP_DECL_PRESOLEXEC(presolExecBoundshift)
{ /*lint --e{715}*/
SCIP_PRESOLDATA* presoldata;
SCIP_VAR** scipvars;
SCIP_VAR** vars;
int nbinvars;
int nvars;
int v;
assert(scip != NULL);
assert(presol != NULL);
assert(strcmp(SCIPpresolGetName(presol), PRESOL_NAME) == 0);
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
/* get presolver data */
presoldata = SCIPpresolGetData(presol);
assert(presoldata != NULL);
/* get the problem variables */
scipvars = SCIPgetVars(scip);
nbinvars = SCIPgetNBinVars(scip);
nvars = SCIPgetNVars(scip) - nbinvars;
if( nvars == 0 )
return SCIP_OKAY;
if( SCIPdoNotAggr(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
/* copy the integer variables into an own array, since adding new integer variables affects the left-most slots in
* the array and thereby interferes with our search loop
*/
SCIP_CALL( SCIPduplicateBufferArray(scip, &vars, &scipvars[nbinvars], nvars) );
/* scan the integer, implicit, and continuous variables for possible conversion */
for( v = nvars - 1; v >= 0; --v )
{
SCIP_VAR* var = vars[v];
SCIP_Real lb;
SCIP_Real ub;
assert(SCIPvarGetType(var) != SCIP_VARTYPE_BINARY);
/* get current variable's bounds */
lb = SCIPvarGetLbGlobal(var);
ub = SCIPvarGetUbGlobal(var);
assert( SCIPisLE(scip, lb, ub) );
if( SCIPisEQ(scip, lb, ub) )
continue;
if( presoldata->integer && !SCIPisIntegral(scip, ub - lb) )
continue;
/* check if bounds are shiftable */
if( !SCIPisEQ(scip, lb, 0.0) && /* lower bound != 0.0 */
SCIPisLT(scip, ub, SCIPinfinity(scip)) && /* upper bound != infinity */
SCIPisGT(scip, lb, -SCIPinfinity(scip)) && /* lower bound != -infinity */
#if 0
SCIPisLT(scip, ub - lb, SCIPinfinity(scip)) && /* interval length less than SCIPinfinity(scip) */
#endif
SCIPisLT(scip, ub - lb, (SCIP_Real) presoldata->maxshift) ) /* less than max shifting */
{
SCIP_VAR* newvar;
char newvarname[SCIP_MAXSTRLEN];
SCIP_Bool infeasible;
SCIP_Bool redundant;
SCIP_Bool aggregated;
SCIPdebugMessage("convert range <%s>[%g,%g] to [%g,%g]\n", SCIPvarGetName(var), lb, ub, 0.0, (ub - lb) );
/* create new variable */
(void) SCIPsnprintf(newvarname, SCIP_MAXSTRLEN, "%s_shift", SCIPvarGetName(var));
SCIP_CALL( SCIPcreateVar(scip, &newvar, newvarname, 0.0, (ub - lb), 0.0, SCIPvarGetType(var),
SCIPvarIsInitial(var), SCIPvarIsRemovable(var), NULL, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPaddVar(scip, newvar) );
/* aggregate old variable with new variable */
if( presoldata->flipping )
{
if( REALABS(ub) < REALABS(lb) )
{
SCIP_CALL( SCIPaggregateVars(scip, var, newvar, 1.0, 1.0, ub, &infeasible, &redundant, &aggregated) );
}
else
{
SCIP_CALL( SCIPaggregateVars(scip, var, newvar, 1.0, -1.0, lb, &infeasible, &redundant, &aggregated) );
}
}
else
{
SCIP_CALL( SCIPaggregateVars(scip, var, newvar, 1.0, -1.0, lb, &infeasible, &redundant, &aggregated) );
}
assert(!infeasible);
assert(redundant);
assert(aggregated);
SCIPdebugMessage("var <%s> with bounds [%f,%f] has obj %f\n",
SCIPvarGetName(newvar),SCIPvarGetLbGlobal(newvar),SCIPvarGetUbGlobal(newvar),SCIPvarGetObj(newvar));
/* release variable */
SCIP_CALL( SCIPreleaseVar(scip, &newvar) );
/* take care of statistic */
(*naggrvars)++;
*result = SCIP_SUCCESS;
}
}
/* free temporary memory */
SCIPfreeBufferArray(scip, &vars);
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecZirounding)
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_SOL* sol;
SCIP_VAR** lpcands;
SCIP_VAR** zilpcands;
SCIP_VAR** slackvars;
SCIP_Real* upslacks;
SCIP_Real* downslacks;
SCIP_Real* activities;
SCIP_Real* slackvarcoeffs;
SCIP_Bool* rowneedsslackvar;
SCIP_ROW** rows;
SCIP_Real* lpcandssol;
SCIP_Real* solarray;
SCIP_Longint nlps;
int currentlpcands;
int nlpcands;
int nimplfracs;
int i;
int c;
int nslacks;
int nroundings;
SCIP_RETCODE retcode;
SCIP_Bool improvementfound;
SCIP_Bool numericalerror;
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
assert(result != NULL);
assert(SCIPhasCurrentNodeLP(scip));
*result = SCIP_DIDNOTRUN;
/* do not call heuristic of node was already detected to be infeasible */
if( nodeinfeasible )
return SCIP_OKAY;
/* only call heuristic if an optimal LP-solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call heuristic, if the LP objective value is smaller than the cutoff bound */
if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
return SCIP_OKAY;
/* get heuristic data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* Do not call heuristic if deactivation check is enabled and percentage of found solutions in relation
* to number of calls falls below heurdata->stoppercentage */
if( heurdata->stopziround && SCIPheurGetNCalls(heur) >= heurdata->minstopncalls
&& SCIPheurGetNSolsFound(heur)/(SCIP_Real)SCIPheurGetNCalls(heur) < heurdata->stoppercentage )
return SCIP_OKAY;
/* assure that heuristic has not already been called after the last LP had been solved */
nlps = SCIPgetNLPs(scip);
if( nlps == heurdata->lastlp )
return SCIP_OKAY;
heurdata->lastlp = nlps;
/* get fractional variables */
SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, &nimplfracs) );
nlpcands = nlpcands + nimplfracs;
/* make sure that there is at least one fractional variable that should be integral */
if( nlpcands == 0 )
return SCIP_OKAY;
assert(nlpcands > 0);
assert(lpcands != NULL);
assert(lpcandssol != NULL);
/* get LP rows data */
rows = SCIPgetLPRows(scip);
nslacks = SCIPgetNLPRows(scip);
/* cannot do anything if LP is empty */
if( nslacks == 0 )
return SCIP_OKAY;
assert(rows != NULL);
assert(nslacks > 0);
/* get the working solution from heuristic's local data */
sol = heurdata->sol;
assert(sol != NULL);
*result = SCIP_DIDNOTFIND;
solarray = NULL;
zilpcands = NULL;
retcode = SCIP_OKAY;
/* copy the current LP solution to the working solution and allocate memory for local data */
SCIP_CALL( SCIPlinkLPSol(scip, sol) );
SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &solarray, nlpcands), TERMINATE);
SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &zilpcands, nlpcands), TERMINATE);
/* copy necessary data to local arrays */
BMScopyMemoryArray(solarray, lpcandssol, nlpcands);
BMScopyMemoryArray(zilpcands, lpcands, nlpcands);
/* allocate buffer data arrays */
SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &slackvars, nslacks), TERMINATE);
SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &upslacks, nslacks), TERMINATE);
SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &downslacks, nslacks), TERMINATE);
SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &slackvarcoeffs, nslacks), TERMINATE);
SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &rowneedsslackvar, nslacks), TERMINATE);
SCIP_CALL_TERMINATE(retcode, SCIPallocBufferArray(scip, &activities, nslacks), TERMINATE);
BMSclearMemoryArray(slackvars, nslacks);
BMSclearMemoryArray(slackvarcoeffs, nslacks);
BMSclearMemoryArray(rowneedsslackvar, nslacks);
numericalerror = FALSE;
nroundings = 0;
/* loop over fractional variables and involved LP rows to find all rows which require a slack variable */
for( c = 0; c < nlpcands; ++c )
{
SCIP_VAR* cand;
SCIP_ROW** candrows;
int r;
int ncandrows;
cand = zilpcands[c];
assert(cand != NULL);
assert(SCIPcolGetLPPos(SCIPvarGetCol(cand)) >= 0);
candrows = SCIPcolGetRows(SCIPvarGetCol(cand));
ncandrows = SCIPcolGetNLPNonz(SCIPvarGetCol(cand));
assert(candrows == NULL || ncandrows > 0);
for( r = 0; r < ncandrows; ++r )
{
int rowpos;
assert(candrows != NULL); /* to please flexelint */
assert(candrows[r] != NULL);
rowpos = SCIProwGetLPPos(candrows[r]);
if( rowpos >= 0 && SCIPisFeasEQ(scip, SCIProwGetLhs(candrows[r]), SCIProwGetRhs(candrows[r])) )
{
rowneedsslackvar[rowpos] = TRUE;
SCIPdebugMessage(" Row %s needs slack variable for variable %s\n", SCIProwGetName(candrows[r]), SCIPvarGetName(cand));
}
}
}
/* calculate row slacks for every every row that belongs to the current LP and ensure, that the current solution
* has no violated constraint -- if any constraint is violated, i.e. a slack is significantly smaller than zero,
* this will cause the termination of the heuristic because Zirounding does not provide feasibility recovering
*/
for( i = 0; i < nslacks; ++i )
{
SCIP_ROW* row;
SCIP_Real lhs;
SCIP_Real rhs;
row = rows[i];
assert(row != NULL);
lhs = SCIProwGetLhs(row);
rhs = SCIProwGetRhs(row);
/* get row activity */
activities[i] = SCIPgetRowActivity(scip, row);
assert(SCIPisFeasLE(scip, lhs, activities[i]) && SCIPisFeasLE(scip, activities[i], rhs));
/* in special case if LHS or RHS is (-)infinity slacks have to be initialized as infinity */
if( SCIPisInfinity(scip, -lhs) )
downslacks[i] = SCIPinfinity(scip);
else
downslacks[i] = activities[i] - lhs;
if( SCIPisInfinity(scip, rhs) )
upslacks[i] = SCIPinfinity(scip);
else
upslacks[i] = rhs - activities[i];
SCIPdebugMessage("lhs:%5.2f <= act:%5.2g <= rhs:%5.2g --> down: %5.2g, up:%5.2g\n", lhs, activities[i], rhs, downslacks[i], upslacks[i]);
/* row is an equation. Try to find a slack variable in the row, i.e.,
* a continuous variable which occurs only in this row. If no such variable exists,
* there is no hope for an IP-feasible solution in this round
*/
if( SCIPisFeasEQ(scip, lhs, rhs) && rowneedsslackvar[i] )
{
/* @todo: This is only necessary for rows containing fractional variables. */
rowFindSlackVar(scip, row, &(slackvars[i]), &(slackvarcoeffs[i]));
if( slackvars[i] == NULL )
{
SCIPdebugMessage("No slack variable found for equation %s, terminating ZI Round heuristic\n", SCIProwGetName(row));
goto TERMINATE;
}
else
{
SCIP_Real ubslackvar;
SCIP_Real lbslackvar;
SCIP_Real solvalslackvar;
SCIP_Real coeffslackvar;
SCIP_Real ubgap;
SCIP_Real lbgap;
assert(SCIPvarGetType(slackvars[i]) == SCIP_VARTYPE_CONTINUOUS);
solvalslackvar = SCIPgetSolVal(scip, sol, slackvars[i]);
ubslackvar = SCIPvarGetUbGlobal(slackvars[i]);
lbslackvar = SCIPvarGetLbGlobal(slackvars[i]);
coeffslackvar = slackvarcoeffs[i];
assert(!SCIPisFeasZero(scip, coeffslackvar));
ubgap = ubslackvar - solvalslackvar;
lbgap = solvalslackvar - lbslackvar;
if( SCIPisFeasZero(scip, ubgap) )
ubgap = 0.0;
if( SCIPisFeasZero(scip, lbgap) )
lbgap = 0.0;
if( SCIPisFeasPositive(scip, coeffslackvar) )
{
if( !SCIPisInfinity(scip, lbslackvar) )
upslacks[i] += coeffslackvar * lbgap;
else
upslacks[i] = SCIPinfinity(scip);
if( !SCIPisInfinity(scip, ubslackvar) )
downslacks[i] += coeffslackvar * ubgap;
else
downslacks[i] = SCIPinfinity(scip);
}
else
{
if( !SCIPisInfinity(scip, ubslackvar) )
upslacks[i] -= coeffslackvar * ubgap;
else
upslacks[i] = SCIPinfinity(scip);
if( !SCIPisInfinity(scip, lbslackvar) )
downslacks[i] -= coeffslackvar * lbgap;
else
downslacks[i] = SCIPinfinity(scip);
}
SCIPdebugMessage(" Slack variable for row %s at pos %d: %g <= %s = %g <= %g; Coeff %g, upslack = %g, downslack = %g \n",
SCIProwGetName(row), SCIProwGetLPPos(row), lbslackvar, SCIPvarGetName(slackvars[i]), solvalslackvar, ubslackvar, coeffslackvar,
upslacks[i], downslacks[i]);
}
}
/* due to numerical inaccuracies, the rows might be feasible, even if the slacks are
* significantly smaller than zero -> terminate
*/
if( SCIPisFeasLT(scip, upslacks[i], 0.0) || SCIPisFeasLT(scip, downslacks[i], 0.0) )
goto TERMINATE;
}
assert(nslacks == 0 || (upslacks != NULL && downslacks != NULL && activities != NULL));
/* initialize number of remaining variables and flag to enter the main loop */
currentlpcands = nlpcands;
improvementfound = TRUE;
/* iterate over variables as long as there are fractional variables left */
while( currentlpcands > 0 && improvementfound && (heurdata->maxroundingloops == -1 || nroundings < heurdata->maxroundingloops) )
{ /*lint --e{850}*/
improvementfound = FALSE;
nroundings++;
SCIPdebugMessage("zirounding enters while loop for %d time with %d candidates left. \n", nroundings, currentlpcands);
/* check for every remaining fractional variable if a shifting decreases ZI-value of the variable */
for( c = 0; c < currentlpcands; ++c )
{
SCIP_VAR* var;
SCIP_Real oldsolval;
SCIP_Real upperbound;
SCIP_Real lowerbound;
SCIP_Real up;
SCIP_Real down;
SCIP_Real ziup;
SCIP_Real zidown;
SCIP_Real zicurrent;
SCIP_Real shiftval;
DIRECTION direction;
/* get values from local data */
oldsolval = solarray[c];
var = zilpcands[c];
assert(!SCIPisFeasIntegral(scip, oldsolval));
assert(SCIPvarGetStatus(var) == SCIP_VARSTATUS_COLUMN);
/* calculate bounds for variable and make sure that there are no numerical inconsistencies */
upperbound = SCIPinfinity(scip);
lowerbound = SCIPinfinity(scip);
calculateBounds(scip, var, oldsolval, &upperbound, &lowerbound, upslacks, downslacks, nslacks, &numericalerror);
if( numericalerror )
goto TERMINATE;
/* calculate the possible values after shifting */
up = oldsolval + upperbound;
down = oldsolval - lowerbound;
/* if the variable is integer or implicit binary, do not shift further than the nearest integer */
if( SCIPvarGetType(var) != SCIP_VARTYPE_BINARY)
{
SCIP_Real ceilx;
SCIP_Real floorx;
ceilx = SCIPfeasCeil(scip, oldsolval);
floorx = SCIPfeasFloor(scip, oldsolval);
up = MIN(up, ceilx);
down = MAX(down, floorx);
}
/* calculate necessary values */
ziup = getZiValue(scip, up);
zidown = getZiValue(scip, down);
zicurrent = getZiValue(scip, oldsolval);
/* calculate the shifting direction that reduces ZI-value the most,
* if both directions improve ZI-value equally, take the direction which improves the objective
*/
if( SCIPisFeasLT(scip, zidown, zicurrent) || SCIPisFeasLT(scip, ziup, zicurrent) )
{
if( SCIPisFeasEQ(scip,ziup, zidown) )
direction = SCIPisFeasGE(scip, SCIPvarGetObj(var), 0.0) ? DIRECTION_DOWN : DIRECTION_UP;
else if( SCIPisFeasLT(scip, zidown, ziup) )
direction = DIRECTION_DOWN;
else
direction = DIRECTION_UP;
/* once a possible shifting direction and value have been found, variable value is updated */
shiftval = (direction == DIRECTION_UP ? up - oldsolval : down - oldsolval);
/* this improves numerical stability in some cases */
if( direction == DIRECTION_UP )
shiftval = MIN(shiftval, upperbound);
else
shiftval = MIN(shiftval, lowerbound);
/* update the solution */
solarray[c] = direction == DIRECTION_UP ? up : down;
SCIP_CALL( SCIPsetSolVal(scip, sol, var, solarray[c]) );
/* update the rows activities and slacks */
SCIP_CALL( updateSlacks(scip, sol, var, shiftval, upslacks,
downslacks, activities, slackvars, slackvarcoeffs, nslacks) );
SCIPdebugMessage("zirounding update step : %d var index, oldsolval=%g, shiftval=%g\n",
SCIPvarGetIndex(var), oldsolval, shiftval);
/* since at least one improvement has been found, heuristic will enter main loop for another time because the improvement
* might affect many LP rows and their current slacks and thus make further rounding steps possible */
improvementfound = TRUE;
}
/* if solution value of variable has become feasibly integral due to rounding step,
* variable is put at the end of remaining candidates array so as not to be considered in future loops
*/
if( SCIPisFeasIntegral(scip, solarray[c]) )
{
zilpcands[c] = zilpcands[currentlpcands - 1];
solarray[c] = solarray[currentlpcands - 1];
currentlpcands--;
/* counter is decreased if end of candidates array has not been reached yet */
if( c < currentlpcands )
c--;
}
else if( nroundings == heurdata->maxroundingloops - 1 )
goto TERMINATE;
}
}
/* in case that no candidate is left for rounding after the final main loop
* the found solution has to be checked for feasibility in the original problem
*/
if( currentlpcands == 0 )
{
SCIP_Bool stored;
SCIP_CALL(SCIPtrySol(scip, sol, FALSE, FALSE, TRUE, FALSE, &stored));
if( stored )
{
#ifdef SCIP_DEBUG
SCIPdebugMessage("found feasible rounded solution:\n");
SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) );
#endif
SCIPstatisticMessage(" ZI Round solution value: %g \n", SCIPgetSolOrigObj(scip, sol));
*result = SCIP_FOUNDSOL;
}
}
/* free memory for all locally allocated data */
TERMINATE:
SCIPfreeBufferArrayNull(scip, &activities);
SCIPfreeBufferArrayNull(scip, &rowneedsslackvar);
SCIPfreeBufferArrayNull(scip, &slackvarcoeffs);
SCIPfreeBufferArrayNull(scip, &downslacks);
SCIPfreeBufferArrayNull(scip, &upslacks);
SCIPfreeBufferArrayNull(scip, &slackvars);
SCIPfreeBufferArrayNull(scip, &zilpcands);
SCIPfreeBufferArrayNull(scip, &solarray);
return retcode;
}
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpRapidlearning)
{/*lint --e{715}*/
SCIP* subscip; /* the subproblem created by rapid learning */
SCIP_SEPADATA* sepadata; /* separator's private data */
SCIP_VAR** vars; /* original problem's variables */
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_HASHMAP* varmapbw; /* mapping of sub-SCIP variables to SCIP variables */
SCIP_CONSHDLR** conshdlrs; /* array of constraint handler's that might that might obtain conflicts */
int* oldnconss; /* number of constraints without rapid learning conflicts */
SCIP_Longint nodelimit; /* node limit for the subproblem */
SCIP_Real timelimit; /* time limit for the subproblem */
SCIP_Real memorylimit; /* memory limit for the subproblem */
int nconshdlrs; /* size of conshdlr and oldnconss array */
int nfixedvars; /* number of variables that could be fixed by rapid learning */
int nvars; /* number of variables */
int restartnum; /* maximal number of conflicts that should be created */
int i; /* counter */
SCIP_Bool success; /* was problem creation / copying constraint successful? */
SCIP_RETCODE retcode; /* used for catching sub-SCIP errors in debug mode */
int nconflicts; /* statistic: number of conflicts applied */
int nbdchgs; /* statistic: number of bound changes applied */
int n1startinfers; /* statistic: number of one side infer values */
int n2startinfers; /* statistic: number of both side infer values */
SCIP_Bool soladded; /* statistic: was a new incumbent found? */
SCIP_Bool dualboundchg; /* statistic: was a new dual bound found? */
SCIP_Bool disabledualreductions; /* TRUE, if dual reductions in sub-SCIP are not valid for original SCIP,
* e.g., because a constraint could not be copied or a primal solution
* could not be copied back
*/
int ndiscvars;
soladded = FALSE;
assert(sepa != NULL);
assert(scip != NULL);
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
ndiscvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip)+SCIPgetNImplVars(scip);
/* only run when still not fixed binary variables exists */
if( ndiscvars == 0 )
return SCIP_OKAY;
/* get separator's data */
sepadata = SCIPsepaGetData(sepa);
assert(sepadata != NULL);
/* only run for integer programs */
if( !sepadata->contvars && ndiscvars != SCIPgetNVars(scip) )
return SCIP_OKAY;
/* only run if there are few enough continuous variables */
if( sepadata->contvars && SCIPgetNContVars(scip) > sepadata->contvarsquot * SCIPgetNVars(scip) )
return SCIP_OKAY;
/* do not run if pricers are present */
if( SCIPgetNActivePricers(scip) > 0 )
return SCIP_OKAY;
/* if the separator should be exclusive to the root node, this prevents multiple calls due to restarts */
if( SCIPsepaGetFreq(sepa) == 0 && SCIPsepaGetNCalls(sepa) > 0)
return SCIP_OKAY;
/* call separator at most once per node */
if( SCIPsepaGetNCallsAtNode(sepa) > 0 )
return SCIP_OKAY;
/* do not call rapid learning, if the problem is too big */
if( SCIPgetNVars(scip) > sepadata->maxnvars || SCIPgetNConss(scip) > sepadata->maxnconss )
return SCIP_OKAY;
if( SCIPisStopped(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* initializing the subproblem */
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
SCIP_CALL( SCIPcreate(&subscip) );
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
success = FALSE;
/* copy the subproblem */
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "rapid", FALSE, FALSE, &success) );
if( sepadata->copycuts )
{
/** copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, FALSE) );
}
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) (size_t) SCIPhashmapGetImage(varmapfw, vars[i]);
SCIPhashmapFree(&varmapfw);
/* this avoids dual presolving */
if( !success )
{
for( i = 0; i < nvars; i++ )
{
SCIP_CALL( SCIPaddVarLocks(subscip, subvars[i], 1, 1 ) );
}
}
SCIPdebugMessage("Copying SCIP was%s successful.\n", success ? "" : " not");
/* mimic an FD solver: DFS, no LP solving, 1-FUIP instead of all-FUIP */
SCIP_CALL( SCIPsetIntParam(subscip, "lp/solvefreq", -1) );
SCIP_CALL( SCIPsetIntParam(subscip, "conflict/fuiplevels", 1) );
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/dfs/stdpriority", INT_MAX/4) );
SCIP_CALL( SCIPsetBoolParam(subscip, "constraints/disableenfops", TRUE) );
SCIP_CALL( SCIPsetIntParam(subscip, "propagating/pseudoobj/freq", -1) );
/* use inference branching */
SCIP_CALL( SCIPsetBoolParam(subscip, "branching/inference/useweightedsum", FALSE) );
/* only create short conflicts */
SCIP_CALL( SCIPsetRealParam(subscip, "conflict/maxvarsfac", 0.05) );
/* set limits for the subproblem */
nodelimit = SCIPgetNLPIterations(scip);
nodelimit = MAX(sepadata->minnodes, nodelimit);
nodelimit = MIN(sepadata->maxnodes, nodelimit);
restartnum = 1000;
/* check whether there is enough time and memory left */
SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
if( !SCIPisInfinity(scip, timelimit) )
timelimit -= SCIPgetSolvingTime(scip);
SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
if( !SCIPisInfinity(scip, memorylimit) )
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
if( timelimit <= 0.0 || memorylimit <= 0.0 )
goto TERMINATE;
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nodelimit/5) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
SCIP_CALL( SCIPsetIntParam(subscip, "limits/restarts", 0) );
SCIP_CALL( SCIPsetIntParam(subscip, "conflict/restartnum", restartnum) );
/* forbid recursive call of heuristics and separators solving subMIPs */
SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
/* disable cutting plane separation */
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
/* disable expensive presolving */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );
/* do not abort subproblem on CTRL-C */
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
#ifndef SCIP_DEBUG
/* disable output to console */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
#endif
/* add an objective cutoff */
SCIP_CALL( SCIPsetObjlimit(subscip, SCIPgetUpperbound(scip)) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapbw, SCIPblkmem(scip), SCIPcalcHashtableSize(5 * nvars)) );
/* store reversing mapping of variables */
SCIP_CALL( SCIPtransformProb(subscip) );
for( i = 0; i < nvars; ++i)
{
SCIP_CALL( SCIPhashmapInsert(varmapbw, SCIPvarGetTransVar(subvars[i]), vars[i]) );
}
/** allocate memory for constraints storage. Each constraint that will be created from now on will be a conflict.
* Therefore, we need to remember oldnconss to get the conflicts from the FD search.
*/
nconshdlrs = 4;
SCIP_CALL( SCIPallocBufferArray(scip, &conshdlrs, nconshdlrs) );
SCIP_CALL( SCIPallocBufferArray(scip, &oldnconss, nconshdlrs) );
/* store number of constraints before rapid learning search */
conshdlrs[0] = SCIPfindConshdlr(subscip, "bounddisjunction");
conshdlrs[1] = SCIPfindConshdlr(subscip, "setppc");
conshdlrs[2] = SCIPfindConshdlr(subscip, "linear");
conshdlrs[3] = SCIPfindConshdlr(subscip, "logicor");
/* redundant constraints might be eliminated in presolving */
SCIP_CALL( SCIPpresolve(subscip));
for( i = 0; i < nconshdlrs; ++i)
{
if( conshdlrs[i] != NULL )
oldnconss[i] = SCIPconshdlrGetNConss(conshdlrs[i]);
}
nfixedvars = SCIPgetNFixedVars(scip);
/* solve the subproblem */
retcode = SCIPsolve(subscip);
/* Errors in solving the subproblem should not kill the overall solving process
* Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage("Error while solving subproblem in rapid learning separator; sub-SCIP terminated with code <%d>\n",retcode);
}
/* abort solving, if limit of applied conflicts is reached */
if( SCIPgetNConflictConssApplied(subscip) >= restartnum )
{
SCIPdebugMessage("finish after %lld successful conflict calls.\n", SCIPgetNConflictConssApplied(subscip));
}
/* if the first 20% of the solution process were successful, proceed */
else if( (sepadata->applyprimalsol && SCIPgetNSols(subscip) > 0 && SCIPisFeasLT(scip, SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip) ) )
|| (sepadata->applybdchgs && SCIPgetNFixedVars(subscip) > nfixedvars)
|| (sepadata->applyconflicts && SCIPgetNConflictConssApplied(subscip) > 0) )
{
SCIPdebugMessage("proceed solving after the first 20%% of the solution process, since:\n");
if( SCIPgetNSols(subscip) > 0 && SCIPisFeasLE(scip, SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip) ) )
{
SCIPdebugMessage(" - there was a better solution (%f < %f)\n",SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip));
}
if( SCIPgetNFixedVars(subscip) > nfixedvars )
{
SCIPdebugMessage(" - there were %d variables fixed\n", SCIPgetNFixedVars(scip)-nfixedvars );
}
if( SCIPgetNConflictConssFound(subscip) > 0 )
{
SCIPdebugMessage(" - there were %lld conflict constraints created\n", SCIPgetNConflictConssApplied(subscip));
}
/* set node limit to 100% */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nodelimit) );
/* solve the subproblem */
retcode = SCIPsolve(subscip);
/* Errors in solving the subproblem should not kill the overall solving process
* Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage("Error while solving subproblem in rapid learning separator; sub-SCIP terminated with code <%d>\n",retcode);
}
}
else
{
SCIPdebugMessage("do not proceed solving after the first 20%% of the solution process.\n");
}
#ifdef SCIP_DEBUG
SCIP_CALL( SCIPprintStatistics(subscip, NULL) );
#endif
disabledualreductions = FALSE;
/* check, whether a solution was found */
if( sepadata->applyprimalsol && SCIPgetNSols(subscip) > 0 && SCIPfindHeur(scip, "trysol") != NULL )
{
SCIP_HEUR* heurtrysol;
SCIP_SOL** subsols;
int nsubsols;
/* check, whether a solution was found;
* due to numerics, it might happen that not all solutions are feasible -> try all solutions until was declared to be feasible
*/
nsubsols = SCIPgetNSols(subscip);
subsols = SCIPgetSols(subscip);
soladded = FALSE;
heurtrysol = SCIPfindHeur(scip, "trysol");
/* sequentially add solutions to trysol heuristic */
for( i = 0; i < nsubsols && !soladded; ++i )
{
SCIPdebugMessage("Try to create new solution by copying subscip solution.\n");
SCIP_CALL( createNewSol(scip, subscip, subvars, heurtrysol, subsols[i], &soladded) );
}
if( !soladded || !SCIPisEQ(scip, SCIPgetSolOrigObj(subscip, subsols[i-1]), SCIPgetSolOrigObj(subscip, subsols[0])) )
disabledualreductions = TRUE;
}
/* if the sub problem was solved completely, we update the dual bound */
dualboundchg = FALSE;
if( sepadata->applysolved && !disabledualreductions
&& (SCIPgetStatus(subscip) == SCIP_STATUS_OPTIMAL || SCIPgetStatus(subscip) == SCIP_STATUS_INFEASIBLE) )
{
/* we need to multiply the dualbound with the scaling factor and add the offset,
* because this information has been disregarded in the sub-SCIP */
SCIPdebugMessage("Update old dualbound %g to new dualbound %g.\n", SCIPgetDualbound(scip), SCIPgetTransObjscale(scip) * SCIPgetDualbound(subscip) + SCIPgetTransObjoffset(scip));
SCIP_CALL( SCIPupdateLocalDualbound(scip, SCIPgetDualbound(subscip) * SCIPgetTransObjscale(scip) + SCIPgetTransObjoffset(scip)) );
dualboundchg = TRUE;
}
/* check, whether conflicts were created */
nconflicts = 0;
if( sepadata->applyconflicts && !disabledualreductions && SCIPgetNConflictConssApplied(subscip) > 0 )
{
SCIP_HASHMAP* consmap;
int hashtablesize;
assert(SCIPgetNConflictConssApplied(subscip) < (SCIP_Longint) INT_MAX);
hashtablesize = (int) SCIPgetNConflictConssApplied(subscip);
assert(hashtablesize < INT_MAX/5);
hashtablesize *= 5;
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&consmap, SCIPblkmem(scip), SCIPcalcHashtableSize(hashtablesize)) );
/* loop over all constraint handlers that might contain conflict constraints */
for( i = 0; i < nconshdlrs; ++i)
{
/* copy constraints that have been created in FD run */
if( conshdlrs[i] != NULL && SCIPconshdlrGetNConss(conshdlrs[i]) > oldnconss[i] )
{
SCIP_CONS** conss;
int c;
int nconss;
nconss = SCIPconshdlrGetNConss(conshdlrs[i]);
conss = SCIPconshdlrGetConss(conshdlrs[i]);
/* loop over all constraints that have been added in sub-SCIP run, these are the conflicts */
for( c = oldnconss[i]; c < nconss; ++c)
{
SCIP_CONS* cons;
SCIP_CONS* conscopy;
cons = conss[c];
assert(cons != NULL);
success = FALSE;
SCIP_CALL( SCIPgetConsCopy(subscip, scip, cons, &conscopy, conshdlrs[i], varmapbw, consmap, NULL,
SCIPconsIsInitial(cons), SCIPconsIsSeparated(cons), SCIPconsIsEnforced(cons), SCIPconsIsChecked(cons),
SCIPconsIsPropagated(cons), TRUE, FALSE, SCIPconsIsDynamic(cons),
SCIPconsIsRemovable(cons), FALSE, TRUE, &success) );
if( success )
{
nconflicts++;
SCIP_CALL( SCIPaddCons(scip, conscopy) );
SCIP_CALL( SCIPreleaseCons(scip, &conscopy) );
}
else
{
SCIPdebugMessage("failed to copy conflict constraint %s back to original SCIP\n", SCIPconsGetName(cons));
}
}
}
}
SCIPhashmapFree(&consmap);
}
/* check, whether tighter global bounds were detected */
nbdchgs = 0;
if( sepadata->applybdchgs && !disabledualreductions )
for( i = 0; i < nvars; ++i )
{
SCIP_Bool infeasible;
SCIP_Bool tightened;
assert(SCIPisLE(scip, SCIPvarGetLbGlobal(vars[i]), SCIPvarGetLbGlobal(subvars[i])));
assert(SCIPisLE(scip, SCIPvarGetLbGlobal(subvars[i]), SCIPvarGetUbGlobal(subvars[i])));
assert(SCIPisLE(scip, SCIPvarGetUbGlobal(subvars[i]), SCIPvarGetUbGlobal(vars[i])));
/* update the bounds of the original SCIP, if a better bound was proven in the sub-SCIP */
SCIP_CALL( SCIPtightenVarUb(scip, vars[i], SCIPvarGetUbGlobal(subvars[i]), FALSE, &infeasible, &tightened) );
if( tightened )
nbdchgs++;
SCIP_CALL( SCIPtightenVarLb(scip, vars[i], SCIPvarGetLbGlobal(subvars[i]), FALSE, &infeasible, &tightened) );
if( tightened )
nbdchgs++;
}
n1startinfers = 0;
n2startinfers = 0;
/* install start values for inference branching */
if( sepadata->applyinfervals && (!sepadata->reducedinfer || soladded || nbdchgs+nconflicts > 0) )
{
for( i = 0; i < nvars; ++i )
{
SCIP_Real downinfer;
SCIP_Real upinfer;
SCIP_Real downvsids;
SCIP_Real upvsids;
SCIP_Real downconflen;
SCIP_Real upconflen;
/* copy downwards branching statistics */
downvsids = SCIPgetVarVSIDS(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);
downconflen = SCIPgetVarAvgConflictlength(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);
downinfer = SCIPgetVarAvgInferences(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);
/* copy upwards branching statistics */
upvsids = SCIPgetVarVSIDS(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);
upconflen = SCIPgetVarAvgConflictlength(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);
upinfer = SCIPgetVarAvgInferences(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);
/* memorize statistics */
if( downinfer+downconflen+downvsids > 0.0 || upinfer+upconflen+upvsids != 0 )
n1startinfers++;
if( downinfer+downconflen+downvsids > 0.0 && upinfer+upconflen+upvsids != 0 )
n2startinfers++;
SCIP_CALL( SCIPinitVarBranchStats(scip, vars[i], 0.0, 0.0, downvsids, upvsids, downconflen, upconflen, downinfer, upinfer, 0.0, 0.0) );
}
}
SCIPdebugPrintf("XXX Rapidlearning added %d conflicts, changed %d bounds, %s primal solution, %s dual bound improvement.\n", nconflicts, nbdchgs, soladded ? "found" : "no",
dualboundchg ? "found" : "no");
SCIPdebugPrintf("YYY Infervalues initialized on one side: %5.2f %% of variables, %5.2f %% on both sides\n",
100.0 * n1startinfers/(SCIP_Real)nvars, 100.0 * n2startinfers/(SCIP_Real)nvars);
/* change result pointer */
if( nconflicts > 0 || dualboundchg )
*result = SCIP_CONSADDED;
else if( nbdchgs > 0 )
*result = SCIP_REDUCEDDOM;
/* free local data */
SCIPfreeBufferArray(scip, &oldnconss);
SCIPfreeBufferArray(scip, &conshdlrs);
SCIPhashmapFree(&varmapbw);
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/** searches and adds implied bound cuts that are violated by the given solution value array */
static
SCIP_RETCODE separateCuts(
SCIP* scip, /**< SCIP data structure */
SCIP_SEPA* sepa, /**< separator */
SCIP_SOL* sol, /**< the solution that should be separated, or NULL for LP solution */
SCIP_Real* solvals, /**< array with solution values of all problem variables */
SCIP_VAR** fracvars, /**< array of fractional variables */
SCIP_Real* fracvals, /**< solution values of fractional variables */
int nfracs, /**< number of fractional variables */
SCIP_Bool* cutoff, /**< whether a cutoff has been detected */
int* ncuts /**< pointer to store the number of generated cuts */
)
{
SCIP_CLIQUE** cliques;
SCIP_SEPADATA* sepadata;
int ncliques;
int i;
assert(solvals != NULL);
assert(fracvars != NULL || nfracs == 0);
assert(fracvals != NULL || nfracs == 0);
assert(cutoff != NULL);
assert(ncuts != NULL);
*cutoff = FALSE;
*ncuts = 0;
sepadata = SCIPsepaGetData(sepa);
assert(sepadata != NULL);
SCIPdebugMessage("searching for implied bound cuts\n");
/* search binary variables for violated implications */
for( i = 0; i < nfracs; i++ )
{
SCIP_BOUNDTYPE* impltypes;
SCIP_Real* implbounds;
SCIP_VAR** implvars;
int nimpl;
int j;
assert(fracvars != NULL);
assert(fracvals != NULL);
/* only process binary variables */
if( SCIPvarGetType(fracvars[i]) != SCIP_VARTYPE_BINARY )
continue;
/* get implications of x == 1 */
nimpl = SCIPvarGetNImpls(fracvars[i], TRUE);
implvars = SCIPvarGetImplVars(fracvars[i], TRUE);
impltypes = SCIPvarGetImplTypes(fracvars[i], TRUE);
implbounds = SCIPvarGetImplBounds(fracvars[i], TRUE);
/*debugMessage("%d implications for <%s>[%g] == 1\n", nimpl, SCIPvarGetName(fracvars[i]), fracvals[i]);*/
/* try to add cuts for implications of x == 1
* x == 1 -> y <= p: y <= ub + x * (p - ub) <==> y + (ub - p) * x <= ub
* x == 1 -> y >= p: y >= lb + x * (p - lb) <==> -y + (p - lb) * x <= -lb
* with lb (ub) global lower (upper) bound of y
*/
for( j = 0; j < nimpl; j++ )
{
SCIP_Real solval;
assert(implvars != NULL);
assert(impltypes != NULL);
assert(implbounds != NULL);
/* consider only implications with active implvar */
if( SCIPvarGetProbindex(implvars[j]) < 0 )
continue;
solval = solvals[SCIPvarGetProbindex(implvars[j])];
if( impltypes[j] == SCIP_BOUNDTYPE_UPPER )
{
SCIP_Real ub;
/* implication x == 1 -> y <= p */
ub = SCIPvarGetUbGlobal(implvars[j]);
/* consider only nonredundant and numerical harmless implications */
if( SCIPisLE(scip, implbounds[j], ub) && (ub - implbounds[j]) * SCIPfeastol(scip) <= RELCUTCOEFMAXRANGE )
{
/* add cut if violated */
SCIP_CALL( addCut(scip, sepa, sol, 1.0, implvars[j], solval, (ub - implbounds[j]), fracvars[i], fracvals[i],
ub, cutoff, ncuts) );
if ( *cutoff )
return SCIP_OKAY;
}
}
else
{
SCIP_Real lb;
/* implication x == 1 -> y >= p */
lb = SCIPvarGetLbGlobal(implvars[j]);
assert(impltypes[j] == SCIP_BOUNDTYPE_LOWER);
/* consider only nonredundant and numerical harmless implications */
if( SCIPisGE(scip, implbounds[j], lb) && (implbounds[j] - lb) * SCIPfeastol(scip) <= RELCUTCOEFMAXRANGE )
{
/* add cut if violated */
SCIP_CALL( addCut(scip, sepa, sol, -1.0, implvars[j], solval, (implbounds[j] - lb), fracvars[i], fracvals[i],
-lb, cutoff, ncuts) );
if ( *cutoff )
return SCIP_OKAY;
}
}
}
/* get implications of x == 0 */
nimpl = SCIPvarGetNImpls(fracvars[i], FALSE);
implvars = SCIPvarGetImplVars(fracvars[i], FALSE);
impltypes = SCIPvarGetImplTypes(fracvars[i], FALSE);
implbounds = SCIPvarGetImplBounds(fracvars[i], FALSE);
/*debugMessage("%d implications for <%s>[%g] == 0\n", nimpl, SCIPvarGetName(fracvars[i]), fracvals[i]);*/
/* try to add cuts for implications of x == 0
* x == 0 -> y <= p: y <= p + x * (ub - p) <==> y + (p - ub) * x <= p
* x == 0 -> y >= p: y >= p + x * (lb - p) <==> -y + (lb - p) * x <= -p
* with lb (ub) global lower (upper) bound of y
*/
for( j = 0; j < nimpl; j++ )
{
SCIP_Real solval;
/* consider only implications with active implvar */
if( SCIPvarGetProbindex(implvars[j]) < 0 )
continue;
solval = solvals[SCIPvarGetProbindex(implvars[j])];
if( impltypes[j] == SCIP_BOUNDTYPE_UPPER )
{
SCIP_Real ub;
/* implication x == 0 -> y <= p */
ub = SCIPvarGetUbGlobal(implvars[j]);
/* consider only nonredundant and numerical harmless implications */
if( SCIPisLE(scip, implbounds[j], ub) && (ub - implbounds[j]) * SCIPfeastol(scip) < RELCUTCOEFMAXRANGE )
{
/* add cut if violated */
SCIP_CALL( addCut(scip, sepa, sol, 1.0, implvars[j], solval, (implbounds[j] - ub), fracvars[i], fracvals[i],
implbounds[j], cutoff, ncuts) );
if ( *cutoff )
return SCIP_OKAY;
}
}
else
{
SCIP_Real lb;
/* implication x == 0 -> y >= p */
lb = SCIPvarGetLbGlobal(implvars[j]);
assert(impltypes[j] == SCIP_BOUNDTYPE_LOWER);
/* consider only nonredundant and numerical harmless implications */
if( SCIPisGE(scip, implbounds[j], lb) && (implbounds[j] - lb) * SCIPfeastol(scip) < RELCUTCOEFMAXRANGE )
{
/* add cut if violated */
SCIP_CALL( addCut(scip, sepa, sol, -1.0, implvars[j], solval, (lb - implbounds[j]), fracvars[i], fracvals[i],
-implbounds[j], cutoff, ncuts) );
if ( *cutoff )
return SCIP_OKAY;
}
}
}
}
/* stop separation here if cliques should not be separated */
if( ! sepadata->usetwosizecliques )
return SCIP_OKAY;
/* prepare clean clique data */
SCIP_CALL( SCIPcleanupCliques(scip, cutoff) );
if( *cutoff )
return SCIP_OKAY;
cliques = SCIPgetCliques(scip);
ncliques = SCIPgetNCliques(scip);
/* loop over cliques of size 2 which are essentially implications and add cuts if they are violated */
for( i = 0; i < ncliques; ++i )
{
SCIP_CLIQUE* clique;
SCIP_VAR** clqvars;
SCIP_Bool* clqvals;
SCIP_Real rhs;
clique = cliques[i];
/* only consider inequality cliques of size 2 */
if( SCIPcliqueGetNVars(clique) != 2 || SCIPcliqueIsEquation(clique) )
continue;
/* get variables and values of the clique */
clqvars = SCIPcliqueGetVars(clique);
clqvals = SCIPcliqueGetValues(clique);
/* clique variables should never be equal after clean up */
assert(clqvars[0] != clqvars[1]);
/* calculate right hand side of clique inequality, which is initially 1 and decreased by 1 for every occurence of
* a negated variable in the clique
*/
rhs = 1.0;
if( ! clqvals[0] )
rhs -= 1.0;
if( ! clqvals[1] )
rhs -= 1.0;
/* Basic clique inequality is
*
* cx * x + (1-cx) (1-x) + cy * y + (1-cy) * (1-y) <= 1,
*
* where x and y are the two binary variables in the clique and cx and cy are their clique values, where a
* clique value of 0 means that the negation of the variable should be part of the inequality.
* Hence, exactly one of the two possible terms for x and y has a nonzero coefficient
*/
SCIP_CALL( addCut(scip, sepa, sol,
clqvals[0] ? 1.0 : -1.0, clqvars[0], SCIPgetSolVal(scip, sol, clqvars[0]),
clqvals[1] ? 1.0 : -1.0, clqvars[1], SCIPgetSolVal(scip, sol, clqvars[1]),
rhs, cutoff, ncuts) );
/* terminate if cutoff was found */
if( *cutoff )
return SCIP_OKAY;
}
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecShifting) /*lint --e{715}*/
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_SOL* sol;
SCIP_VAR** lpcands;
SCIP_Real* lpcandssol;
SCIP_ROW** lprows;
SCIP_Real* activities;
SCIP_ROW** violrows;
SCIP_Real* nincreases;
SCIP_Real* ndecreases;
int* violrowpos;
int* nfracsinrow;
SCIP_Real increaseweight;
SCIP_Real obj;
SCIP_Real bestshiftval;
SCIP_Real minobj;
int nlpcands;
int nlprows;
int nvars;
int nfrac;
int nviolrows;
int nprevviolrows;
int minnviolrows;
int nnonimprovingshifts;
int c;
int r;
SCIP_Longint nlps;
SCIP_Longint ncalls;
SCIP_Longint nsolsfound;
SCIP_Longint nnodes;
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
assert(SCIPhasCurrentNodeLP(scip));
*result = SCIP_DIDNOTRUN;
/* only call heuristic, if an optimal LP solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call heuristic, if the LP objective value is smaller than the cutoff bound */
if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
return SCIP_OKAY;
/* get heuristic data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* don't call heuristic, if we have already processed the current LP solution */
nlps = SCIPgetNLPs(scip);
if( nlps == heurdata->lastlp )
return SCIP_OKAY;
heurdata->lastlp = nlps;
/* don't call heuristic, if it was not successful enough in the past */
ncalls = SCIPheurGetNCalls(heur);
nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + SCIPheurGetNSolsFound(heur);
nnodes = SCIPgetNNodes(scip);
if( nnodes % ((ncalls/100)/(nsolsfound+1)+1) != 0 )
return SCIP_OKAY;
/* get fractional variables, that should be integral */
/* todo check if heuristic should include implicit integer variables for its calculations */
SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, NULL, &nlpcands, NULL, NULL) );
nfrac = nlpcands;
/* only call heuristic, if LP solution is fractional */
if( nfrac == 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
/* get LP rows */
SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );
SCIPdebugMessage("executing shifting heuristic: %d LP rows, %d fractionals\n", nlprows, nfrac);
/* get memory for activities, violated rows, and row violation positions */
nvars = SCIPgetNVars(scip);
SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &violrows, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &violrowpos, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &nfracsinrow, nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &nincreases, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &ndecreases, nvars) );
BMSclearMemoryArray(nfracsinrow, nlprows);
BMSclearMemoryArray(nincreases, nvars);
BMSclearMemoryArray(ndecreases, nvars);
/* get the activities for all globally valid rows;
* the rows should be feasible, but due to numerical inaccuracies in the LP solver, they can be violated
*/
nviolrows = 0;
for( r = 0; r < nlprows; ++r )
{
SCIP_ROW* row;
row = lprows[r];
assert(SCIProwGetLPPos(row) == r);
if( !SCIProwIsLocal(row) )
{
activities[r] = SCIPgetRowActivity(scip, row);
if( SCIPisFeasLT(scip, activities[r], SCIProwGetLhs(row))
|| SCIPisFeasGT(scip, activities[r], SCIProwGetRhs(row)) )
{
violrows[nviolrows] = row;
violrowpos[r] = nviolrows;
nviolrows++;
}
else
violrowpos[r] = -1;
}
}
/* calc the current number of fractional variables in rows */
for( c = 0; c < nlpcands; ++c )
addFracCounter(nfracsinrow, nlprows, lpcands[c], +1);
/* get the working solution from heuristic's local data */
sol = heurdata->sol;
assert(sol != NULL);
/* copy the current LP solution to the working solution */
SCIP_CALL( SCIPlinkLPSol(scip, sol) );
/* calculate the minimal objective value possible after rounding fractional variables */
minobj = SCIPgetSolTransObj(scip, sol);
assert(minobj < SCIPgetCutoffbound(scip));
for( c = 0; c < nlpcands; ++c )
{
obj = SCIPvarGetObj(lpcands[c]);
bestshiftval = obj > 0.0 ? SCIPfeasFloor(scip, lpcandssol[c]) : SCIPfeasCeil(scip, lpcandssol[c]);
minobj += obj * (bestshiftval - lpcandssol[c]);
}
/* try to shift remaining variables in order to become/stay feasible */
nnonimprovingshifts = 0;
minnviolrows = INT_MAX;
increaseweight = 1.0;
while( (nfrac > 0 || nviolrows > 0) && nnonimprovingshifts < MAXSHIFTINGS )
{
SCIP_VAR* shiftvar;
SCIP_Real oldsolval;
SCIP_Real newsolval;
SCIP_Bool oldsolvalisfrac;
int probindex;
SCIPdebugMessage("shifting heuristic: nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g), cutoff=%g\n",
nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj),
SCIPretransformObj(scip, SCIPgetCutoffbound(scip)));
nprevviolrows = nviolrows;
/* choose next variable to process:
* - if a violated row exists, shift a variable decreasing the violation, that has least impact on other rows
* - otherwise, shift a variable, that has strongest devastating impact on rows in opposite direction
*/
shiftvar = NULL;
oldsolval = 0.0;
newsolval = 0.0;
if( nviolrows > 0 && (nfrac == 0 || nnonimprovingshifts < MAXSHIFTINGS-1) )
{
SCIP_ROW* row;
int rowidx;
int rowpos;
int direction;
rowidx = -1;
rowpos = -1;
row = NULL;
if( nfrac > 0 )
{
for( rowidx = nviolrows-1; rowidx >= 0; --rowidx )
{
row = violrows[rowidx];
rowpos = SCIProwGetLPPos(row);
assert(violrowpos[rowpos] == rowidx);
if( nfracsinrow[rowpos] > 0 )
break;
}
}
if( rowidx == -1 )
{
rowidx = SCIPgetRandomInt(0, nviolrows-1, &heurdata->randseed);
row = violrows[rowidx];
rowpos = SCIProwGetLPPos(row);
assert(0 <= rowpos && rowpos < nlprows);
assert(violrowpos[rowpos] == rowidx);
assert(nfracsinrow[rowpos] == 0);
}
assert(violrowpos[rowpos] == rowidx);
SCIPdebugMessage("shifting heuristic: try to fix violated row <%s>: %g <= %g <= %g\n",
SCIProwGetName(row), SCIProwGetLhs(row), activities[rowpos], SCIProwGetRhs(row));
SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );
/* get direction in which activity must be shifted */
assert(SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row))
|| SCIPisFeasGT(scip, activities[rowpos], SCIProwGetRhs(row)));
direction = SCIPisFeasLT(scip, activities[rowpos], SCIProwGetLhs(row)) ? +1 : -1;
/* search a variable that can shift the activity in the necessary direction */
SCIP_CALL( selectShifting(scip, sol, row, activities[rowpos], direction,
nincreases, ndecreases, increaseweight, &shiftvar, &oldsolval, &newsolval) );
}
if( shiftvar == NULL && nfrac > 0 )
{
SCIPdebugMessage("shifting heuristic: search rounding variable and try to stay feasible\n");
SCIP_CALL( selectEssentialRounding(scip, sol, minobj, lpcands, nlpcands, &shiftvar, &oldsolval, &newsolval) );
}
/* check, whether shifting was possible */
if( shiftvar == NULL || SCIPisEQ(scip, oldsolval, newsolval) )
{
SCIPdebugMessage("shifting heuristic: -> didn't find a shifting variable\n");
break;
}
SCIPdebugMessage("shifting heuristic: -> shift var <%s>[%g,%g], type=%d, oldval=%g, newval=%g, obj=%g\n",
SCIPvarGetName(shiftvar), SCIPvarGetLbGlobal(shiftvar), SCIPvarGetUbGlobal(shiftvar), SCIPvarGetType(shiftvar),
oldsolval, newsolval, SCIPvarGetObj(shiftvar));
/* update row activities of globally valid rows */
SCIP_CALL( updateActivities(scip, activities, violrows, violrowpos, &nviolrows, nlprows,
shiftvar, oldsolval, newsolval) );
if( nviolrows >= nprevviolrows )
nnonimprovingshifts++;
else if( nviolrows < minnviolrows )
{
minnviolrows = nviolrows;
nnonimprovingshifts = 0;
}
/* store new solution value and decrease fractionality counter */
SCIP_CALL( SCIPsetSolVal(scip, sol, shiftvar, newsolval) );
/* update fractionality counter and minimal objective value possible after shifting remaining variables */
oldsolvalisfrac = !SCIPisFeasIntegral(scip, oldsolval)
&& (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER);
obj = SCIPvarGetObj(shiftvar);
if( (SCIPvarGetType(shiftvar) == SCIP_VARTYPE_BINARY || SCIPvarGetType(shiftvar) == SCIP_VARTYPE_INTEGER)
&& oldsolvalisfrac )
{
assert(SCIPisFeasIntegral(scip, newsolval));
nfrac--;
nnonimprovingshifts = 0;
minnviolrows = INT_MAX;
addFracCounter(nfracsinrow, nlprows, shiftvar, -1);
/* the rounding was already calculated into the minobj -> update only if rounding in "wrong" direction */
if( obj > 0.0 && newsolval > oldsolval )
minobj += obj;
else if( obj < 0.0 && newsolval < oldsolval )
minobj -= obj;
}
else
{
/* update minimal possible objective value */
minobj += obj * (newsolval - oldsolval);
}
/* update increase/decrease arrays */
if( !oldsolvalisfrac )
{
probindex = SCIPvarGetProbindex(shiftvar);
assert(0 <= probindex && probindex < nvars);
increaseweight *= WEIGHTFACTOR;
if( newsolval < oldsolval )
ndecreases[probindex] += increaseweight;
else
nincreases[probindex] += increaseweight;
if( increaseweight >= 1e+09 )
{
int i;
for( i = 0; i < nvars; ++i )
{
nincreases[i] /= increaseweight;
ndecreases[i] /= increaseweight;
}
increaseweight = 1.0;
}
}
SCIPdebugMessage("shifting heuristic: -> nfrac=%d, nviolrows=%d, obj=%g (best possible obj: %g)\n",
nfrac, nviolrows, SCIPgetSolOrigObj(scip, sol), SCIPretransformObj(scip, minobj));
}
/* check, if the new solution is feasible */
if( nfrac == 0 && nviolrows == 0 )
{
SCIP_Bool stored;
/* check solution for feasibility, and add it to solution store if possible
* neither integrality nor feasibility of LP rows has to be checked, because this is already
* done in the shifting heuristic itself; however, we better check feasibility of LP rows,
* because of numerical problems with activity updating
*/
SCIP_CALL( SCIPtrySol(scip, sol, FALSE, FALSE, FALSE, TRUE, &stored) );
if( stored )
{
SCIPdebugMessage("found feasible shifted solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, sol, NULL, FALSE) ) );
*result = SCIP_FOUNDSOL;
}
}
/* free memory buffers */
SCIPfreeBufferArray(scip, &ndecreases);
SCIPfreeBufferArray(scip, &nincreases);
SCIPfreeBufferArray(scip, &nfracsinrow);
SCIPfreeBufferArray(scip, &violrowpos);
SCIPfreeBufferArray(scip, &violrows);
SCIPfreeBufferArray(scip, &activities);
return SCIP_OKAY;
}
/** returns a variable, that pushes activity of the row in the given direction with minimal negative impact on other rows;
* if variables have equal impact, chooses the one with best objective value improvement in corresponding direction;
* prefer fractional integers over other variables in order to become integral during the process;
* shifting in a direction is forbidden, if this forces the objective value over the upper bound, or if the variable
* was already shifted in the opposite direction
*/
static
SCIP_RETCODE selectShifting(
SCIP* scip, /**< SCIP data structure */
SCIP_SOL* sol, /**< primal solution */
SCIP_ROW* row, /**< LP row */
SCIP_Real rowactivity, /**< activity of LP row */
int direction, /**< should the activity be increased (+1) or decreased (-1)? */
SCIP_Real* nincreases, /**< array with weighted number of increasings per variables */
SCIP_Real* ndecreases, /**< array with weighted number of decreasings per variables */
SCIP_Real increaseweight, /**< current weight of increase/decrease updates */
SCIP_VAR** shiftvar, /**< pointer to store the shifting variable, returns NULL if impossible */
SCIP_Real* oldsolval, /**< pointer to store old solution value of shifting variable */
SCIP_Real* newsolval /**< pointer to store new (shifted) solution value of shifting variable */
)
{
SCIP_COL** rowcols;
SCIP_Real* rowvals;
int nrowcols;
SCIP_Real activitydelta;
SCIP_Real bestshiftscore;
SCIP_Real bestdeltaobj;
int c;
assert(direction == +1 || direction == -1);
assert(nincreases != NULL);
assert(ndecreases != NULL);
assert(shiftvar != NULL);
assert(oldsolval != NULL);
assert(newsolval != NULL);
/* get row entries */
rowcols = SCIProwGetCols(row);
rowvals = SCIProwGetVals(row);
nrowcols = SCIProwGetNLPNonz(row);
/* calculate how much the activity must be shifted in order to become feasible */
activitydelta = (direction == +1 ? SCIProwGetLhs(row) - rowactivity : SCIProwGetRhs(row) - rowactivity);
assert((direction == +1 && SCIPisPositive(scip, activitydelta))
|| (direction == -1 && SCIPisNegative(scip, activitydelta)));
/* select shifting variable */
bestshiftscore = SCIP_REAL_MAX;
bestdeltaobj = SCIPinfinity(scip);
*shiftvar = NULL;
*newsolval = 0.0;
*oldsolval = 0.0;
for( c = 0; c < nrowcols; ++c )
{
SCIP_COL* col;
SCIP_VAR* var;
SCIP_Real val;
SCIP_Real solval;
SCIP_Real shiftval;
SCIP_Real shiftscore;
SCIP_Bool isinteger;
SCIP_Bool isfrac;
SCIP_Bool increase;
col = rowcols[c];
var = SCIPcolGetVar(col);
val = rowvals[c];
assert(!SCIPisZero(scip, val));
solval = SCIPgetSolVal(scip, sol, var);
isinteger = (SCIPvarGetType(var) == SCIP_VARTYPE_BINARY || SCIPvarGetType(var) == SCIP_VARTYPE_INTEGER);
isfrac = isinteger && !SCIPisFeasIntegral(scip, solval);
increase = (direction * val > 0.0);
/* calculate the score of the shifting (prefer smaller values) */
if( isfrac )
shiftscore = increase ? -1.0 / (SCIPvarGetNLocksUp(var) + 1.0) :
-1.0 / (SCIPvarGetNLocksDown(var) + 1.0);
else
{
int probindex;
probindex = SCIPvarGetProbindex(var);
if( increase )
shiftscore = ndecreases[probindex]/increaseweight;
else
shiftscore = nincreases[probindex]/increaseweight;
if( isinteger )
shiftscore += 1.0;
}
if( shiftscore <= bestshiftscore )
{
SCIP_Real deltaobj;
if( !increase )
{
/* shifting down */
assert(direction * val < 0.0);
if( isfrac )
shiftval = SCIPfeasFloor(scip, solval);
else
{
SCIP_Real lb;
assert(activitydelta/val < 0.0);
shiftval = solval + activitydelta/val;
assert(shiftval <= solval); /* may be equal due to numerical digit erasement in the subtraction */
if( SCIPvarIsIntegral(var) )
shiftval = SCIPfeasFloor(scip, shiftval);
lb = SCIPvarGetLbGlobal(var);
shiftval = MAX(shiftval, lb);
}
}
else
{
/* shifting up */
assert(direction * val > 0.0);
if( isfrac )
shiftval = SCIPfeasCeil(scip, solval);
else
{
SCIP_Real ub;
assert(activitydelta/val > 0.0);
shiftval = solval + activitydelta/val;
assert(shiftval >= solval); /* may be equal due to numerical digit erasement in the subtraction */
if( SCIPvarIsIntegral(var) )
shiftval = SCIPfeasCeil(scip, shiftval);
ub = SCIPvarGetUbGlobal(var);
shiftval = MIN(shiftval, ub);
}
}
if( SCIPisEQ(scip, shiftval, solval) )
continue;
deltaobj = SCIPvarGetObj(var) * (shiftval - solval);
if( shiftscore < bestshiftscore || deltaobj < bestdeltaobj )
{
bestshiftscore = shiftscore;
bestdeltaobj = deltaobj;
*shiftvar = var;
*oldsolval = solval;
*newsolval = shiftval;
}
}
}
return SCIP_OKAY;
}
/** reads the given solution file */
static
SCIP_RETCODE readSol(
SCIP* scip, /**< SCIP data structure */
const char* filename /**< name of the input file */
)
{
SCIP_FILE* file;
SCIP_Bool error;
SCIP_Bool unknownvariablemessage;
int lineno;
int nfixed;
assert(scip != NULL);
assert(filename != NULL);
/* open input file */
file = SCIPfopen(filename, "r");
if( file == NULL )
{
SCIPerrorMessage("cannot open file <%s> for reading\n", filename);
SCIPprintSysError(filename);
return SCIP_NOFILE;
}
/* read the file */
error = FALSE;
unknownvariablemessage = FALSE;
lineno = 0;
nfixed = 0;
while( !SCIPfeof(file) && !error )
{
char buffer[SCIP_MAXSTRLEN];
char varname[SCIP_MAXSTRLEN];
char valuestring[SCIP_MAXSTRLEN];
char objstring[SCIP_MAXSTRLEN];
SCIP_VAR* var;
SCIP_Real value;
SCIP_Bool infeasible;
SCIP_Bool fixed;
int nread;
/* get next line */
if( SCIPfgets(buffer, (int) sizeof(buffer), file) == NULL )
break;
lineno++;
/* the lines "solution status: ..." and "objective value: ..." may preceed the solution information */
if( strncasecmp(buffer, "solution status:", 16) == 0 || strncasecmp(buffer, "objective value:", 16) == 0 )
continue;
/* parse the line */
nread = sscanf(buffer, "%s %s %s\n", varname, valuestring, objstring);
if( nread < 2 )
{
SCIPerrorMessage("invalid input line %d in solution file <%s>: <%s>\n", lineno, filename, buffer);
error = TRUE;
break;
}
/* find the variable */
var = SCIPfindVar(scip, varname);
if( var == NULL )
{
if( !unknownvariablemessage )
{
SCIPwarningMessage(scip, "unknown variable <%s> in line %d of solution file <%s>\n", varname, lineno, filename);
SCIPwarningMessage(scip, " (further unknown variables are ignored)\n");
unknownvariablemessage = TRUE;
}
continue;
}
/* cast the value */
if( strncasecmp(valuestring, "inv", 3) == 0 )
continue;
else if( strncasecmp(valuestring, "+inf", 4) == 0 || strncasecmp(valuestring, "inf", 3) == 0 )
value = SCIPinfinity(scip);
else if( strncasecmp(valuestring, "-inf", 4) == 0 )
value = -SCIPinfinity(scip);
else
{
nread = sscanf(valuestring, "%lf", &value);
if( nread != 1 )
{
SCIPerrorMessage("invalid solution value <%s> for variable <%s> in line %d of solution file <%s>\n",
valuestring, varname, lineno, filename);
error = TRUE;
break;
}
}
/* fix the variable */
SCIP_CALL( SCIPfixVar(scip, var, value, &infeasible, &fixed) );
if( infeasible )
{
SCIPerrorMessage("infeasible solution value of <%s>[%.15g,%.15g] to %.15g in line %d of solution file <%s>\n",
varname, SCIPvarGetLbGlobal(var), SCIPvarGetUbGlobal(var), value, lineno, filename);
error = TRUE;
break;
}
if( fixed )
nfixed++;
}
/* close input file */
SCIPfclose(file);
/* display result */
SCIPverbMessage(scip, SCIP_VERBLEVEL_NORMAL, NULL, "fixed %d variables from solution file <%s>\n", nfixed, filename);
if( error )
return SCIP_READERROR;
else
return SCIP_OKAY;
}
/** propagator to force finding the debugging solution */
static
SCIP_DECL_PROPEXEC(propExecDebug)
{ /*lint --e{715}*/
SCIP_VAR** vars;
int nvars;
int i;
assert(scip != NULL);
assert(result != NULL);
*result = SCIP_DIDNOTFIND;
/* check if we are in the original problem and not in a sub MIP */
if( !isSolutionInMip(scip->set) )
return SCIP_OKAY;
if( SCIPgetStage(scip) != SCIP_STAGE_SOLVING )
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(scip->set) )
return SCIP_OKAY;
#if 1
/* solve at least one LP */
if( SCIPgetNLPIterations(scip) == 0 )
return SCIP_OKAY;
#endif
vars = SCIPgetOrigVars(scip);
nvars = SCIPgetNOrigVars(scip);
for( i = 0; i < nvars; ++i )
{
SCIP_Real solval;
SCIP_Real lb;
SCIP_Real ub;
SCIP_Bool infeasible;
SCIP_Bool fixed;
SCIP_CALL( getSolutionValue(scip->set, vars[i], &solval) );
if( solval == SCIP_UNKNOWN ) /*lint !e777*/
{
SCIPerrorMessage("original variable without debugging solution value\n");
SCIPABORT();
}
lb = SCIPvarGetLbGlobal(vars[i]);
ub = SCIPvarGetUbGlobal(vars[i]);
if( SCIPisLT(scip, solval, lb) || SCIPisGT(scip, solval, ub) )
{
SCIPerrorMessage("solution value %.15g of <%s> outside bounds loc=[%.15g,%.15g], glb=[%.15g,%.15g]\n",
solval, SCIPvarGetName(vars[i]), lb, ub, SCIPvarGetLbGlobal(vars[i]), SCIPvarGetUbGlobal(vars[i]));
SCIPABORT();
}
SCIP_CALL( SCIPfixVar(scip, vars[i], solval, &infeasible, &fixed) );
if( infeasible )
*result = SCIP_CUTOFF;
else if( fixed )
*result = SCIP_REDUCEDDOM;
}
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;
}
/** creates the all variables of the subproblem */
static SCIP_RETCODE fixVariables(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP data structure for the subproblemd */
SCIP_VAR** subvars, /**< the variables of the subproblem */
int* selection, /**< pool of solutions crossover will use */
SCIP_HEURDATA* heurdata, /**< primal heuristic data */
SCIP_Bool* success /**< pointer to store whether the problem was created successfully */
)
{
SCIP_VAR** vars; /* original scip variables */
SCIP_SOL** sols; /* pool of solutions */
SCIP_Real fixingrate; /* percentage of variables that are fixed */
int nvars;
int nbinvars;
int nintvars;
int i;
int j;
int fixingcounter;
sols = SCIPgetSols(scip);
assert(sols != NULL);
/* get required data of the original problem */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
fixingcounter = 0;
/* create the binary and general integer variables of the subproblem */
for( i = 0; i < nbinvars + nintvars; i++ )
{
SCIP_Real solval;
SCIP_Bool fixable;
fixable = TRUE;
solval = SCIPgetSolVal(scip, sols[selection[0]], vars[i]);
/* check, whether variable's value is identical for each selected solution */
for( j = 1; j < heurdata->nusedsols; j++ )
{
SCIP_Real varsolval;
varsolval = SCIPgetSolVal(scip, sols[selection[j]], vars[i]);
if( REALABS(solval - varsolval) > 0.5 )
{
fixable = FALSE;
break;
}
}
/* original solval can be outside transformed global bounds */
fixable = fixable && SCIPvarGetLbGlobal(vars[i]) <= solval && solval <= SCIPvarGetUbGlobal(vars[i]);
/* if solutions' values are equal, variable is fixed in the subproblem */
if( fixable )
{
SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], solval) );
SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], solval) );
fixingcounter++;
}
}
fixingrate = (SCIP_Real)fixingcounter / (SCIP_Real)(MAX(nbinvars + nintvars, 1));
/* if all variables were fixed or amount of fixed variables is insufficient, skip residual part of
* subproblem creation and abort immediately */
*success = fixingcounter < nbinvars + nintvars && fixingrate >= heurdata->minfixingrate;
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;
}
/** determines shifting bounds for variable */
static
void calculateBounds(
SCIP* scip, /**< pointer to current SCIP data structure */
SCIP_VAR* var, /**< the variable for which lb and ub have to be calculated */
SCIP_Real currentvalue, /**< the current value of var in the working solution */
SCIP_Real* upperbound, /**< pointer to store the calculated upper bound on the variable shift */
SCIP_Real* lowerbound, /**< pointer to store the calculated lower bound on the variable shift */
SCIP_Real* upslacks, /**< array that contains the slacks between row activities and the right hand sides of the rows */
SCIP_Real* downslacks, /**< array that contains lhs slacks */
int nslacks, /**< current number of slacks */
SCIP_Bool* numericalerror /**< flag to determine whether a numerical error occurred */
)
{
SCIP_COL* col;
SCIP_ROW** colrows;
SCIP_Real* colvals;
int ncolvals;
int i;
assert(scip != NULL);
assert(var != NULL);
assert(upslacks != NULL);
assert(downslacks != NULL);
assert(upperbound != NULL);
assert(lowerbound != NULL);
/* get the column associated to the variable, the nonzero rows and the nonzero coefficients */
col = SCIPvarGetCol(var);
colrows = SCIPcolGetRows(col);
colvals = SCIPcolGetVals(col);
ncolvals = SCIPcolGetNLPNonz(col);
/* only proceed, when variable has nonzero coefficients */
if( ncolvals == 0 )
return;
assert(colvals != NULL);
assert(colrows != NULL);
/* initialize the bounds on the shift to be the gap of the current solution value to the bounds of the variable */
if( SCIPisInfinity(scip, SCIPvarGetUbGlobal(var)) )
*upperbound = SCIPinfinity(scip);
else
*upperbound = SCIPvarGetUbGlobal(var) - currentvalue;
if( SCIPisInfinity(scip, -SCIPvarGetLbGlobal(var)) )
*lowerbound = SCIPinfinity(scip);
else
*lowerbound = currentvalue - SCIPvarGetLbGlobal(var);
/* go through every nonzero row coefficient corresponding to var to determine bounds for shifting
* in such a way that shifting maintains feasibility in every LP row.
* a lower or upper bound as it is calculated in zirounding always has to be >= 0.0.
* if one of these values is significantly < 0.0, this will cause the abort of execution of the heuristic so that
* infeasible solutions are avoided
*/
for( i = 0; i < ncolvals && (*lowerbound > 0.0 || *upperbound > 0.0); ++i )
{
SCIP_ROW* row;
int rowpos;
row = colrows[i];
rowpos = SCIProwGetLPPos(row);
/* the row might currently not be in the LP, ignore it! */
if( rowpos == -1 )
continue;
assert(0 <= rowpos && rowpos < nslacks);
/* all bounds and slacks as they are calculated in zirounding always have to be greater equal zero.
* It might however be due to numerical issues, e.g. with scaling, that they are not. Better abort in this case.
*/
if( SCIPisFeasLT(scip, *lowerbound, 0.0) || SCIPisFeasLT(scip, *upperbound, 0.0)
|| SCIPisFeasLT(scip, upslacks[rowpos], 0.0) || SCIPisFeasLT(scip, downslacks[rowpos] , 0.0) )
{
*numericalerror = TRUE;
return;
}
SCIPdebugMessage("colval: %15.8g, downslack: %15.8g, upslack: %5.2g, lb: %5.2g, ub: %5.2g\n", colvals[i], downslacks[rowpos], upslacks[rowpos],
*lowerbound, *upperbound);
/* if coefficient > 0, rounding up might violate up slack and rounding down might violate down slack
* thus search for the minimum so that no constraint is violated; vice versa for coefficient < 0
*/
if( colvals[i] > 0 )
{
if( !SCIPisInfinity(scip, upslacks[rowpos]) )
{
SCIP_Real upslack;
upslack = MAX(upslacks[rowpos], 0.0); /* avoid errors due to numerically slightly infeasible rows */
*upperbound = MIN(*upperbound, upslack/colvals[i]);
}
if( !SCIPisInfinity(scip, downslacks[rowpos]) )
{
SCIP_Real downslack;
downslack = MAX(downslacks[rowpos], 0.0); /* avoid errors due to numerically slightly infeasible rows */
*lowerbound = MIN(*lowerbound, downslack/colvals[i]);
}
}
else
{
assert(colvals[i] != 0.0);
if( !SCIPisInfinity(scip, upslacks[rowpos]) )
{
SCIP_Real upslack;
upslack = MAX(upslacks[rowpos], 0.0); /* avoid errors due to numerically slightly infeasible rows */
*lowerbound = MIN(*lowerbound, -upslack/colvals[i]);
}
if( !SCIPisInfinity(scip, downslacks[rowpos]) )
{
SCIP_Real downslack;
downslack = MAX(downslacks[rowpos], 0.0); /* avoid errors due to numerically slightly infeasible rows */
*upperbound = MIN(*upperbound, -downslack/colvals[i]);
}
}
}
}
/** avoid to generate columns which are fixed to zero; therefore add for each variable which is fixed to zero a
* corresponding logicor constraint to forbid this column
*
* @note variable which are fixed locally to zero should not be generated again by the pricing MIP
*/
static
SCIP_RETCODE addFixedVarsConss(
SCIP* scip, /**< SCIP data structure */
SCIP* subscip, /**< pricing SCIP data structure */
SCIP_VAR** vars, /**< variable array of the subscuip */
SCIP_CONS** conss, /**< array of setppc constraint for each item one */
int nitems /**< number of items */
)
{
SCIP_VAR** origvars;
int norigvars;
SCIP_CONS* cons;
int* consids;
int nconsids;
int consid;
int nvars;
SCIP_VAR** logicorvars;
SCIP_VAR* var;
SCIP_VARDATA* vardata;
SCIP_Bool needed;
int nlogicorvars;
int v;
int c;
int o;
/* collect all variable which are currently existing */
origvars = SCIPgetVars(scip);
norigvars = SCIPgetNVars(scip);
/* loop over all these variables and check if they are fixed to zero */
for( v = 0; v < norigvars; ++v )
{
assert(SCIPvarGetType(origvars[v]) == SCIP_VARTYPE_BINARY);
/* if the upper bound is smaller than 0.5 if follows due to the integrality that the binary variable is fixed to zero */
if( SCIPvarGetUbLocal(origvars[v]) < 0.5 )
{
SCIPdebugMessage("variable <%s> glb=[%.15g,%.15g] loc=[%.15g,%.15g] is fixed to zero\n",
SCIPvarGetName(origvars[v]), SCIPvarGetLbGlobal(origvars[v]), SCIPvarGetUbGlobal(origvars[v]),
SCIPvarGetLbLocal(origvars[v]), SCIPvarGetUbLocal(origvars[v]) );
/* coolect the constraints/items the variable belongs to */
vardata = SCIPvarGetData(origvars[v]);
nconsids = SCIPvardataGetNConsids(vardata);
consids = SCIPvardataGetConsids(vardata);
needed = TRUE;
SCIP_CALL( SCIPallocBufferArray(subscip, &logicorvars, nitems) );
nlogicorvars = 0;
consid = consids[0];
nvars = 0;
/* loop over these items and create a linear (logicor) constraint which forbids this item combination in the
* pricing problem; thereby check if this item combination is already forbidden
*/
for( c = 0, o = 0; o < nitems && needed; ++o )
{
assert(o <= consid);
cons = conss[o];
if( SCIPconsIsEnabled(cons) )
{
assert( SCIPgetNFixedonesSetppc(scip, cons) == 0 );
var = vars[nvars];
nvars++;
assert(var != NULL);
if( o == consid )
{
SCIP_CALL( SCIPgetNegatedVar(subscip, var, &var) );
}
logicorvars[nlogicorvars] = var;
nlogicorvars++;
}
else if( o == consid )
needed = FALSE;
if( o == consid )
{
c++;
if ( c == nconsids )
consid = nitems + 100;
else
{
assert(consid < consids[c]);
consid = consids[c];
}
}
}
if( needed )
{
SCIP_CALL( SCIPcreateConsBasicLogicor(subscip, &cons, SCIPvarGetName(origvars[v]), nlogicorvars, logicorvars) );
SCIP_CALL( SCIPsetConsInitial(subscip, cons, FALSE) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
}
SCIPfreeBufferArray(subscip, &logicorvars);
}
}
return SCIP_OKAY;
}
/** execution method of presolver */
static
SCIP_DECL_PRESOLEXEC(presolExecDualfix)
{ /*lint --e{715}*/
SCIP_VAR** vars;
SCIP_Real bound;
SCIP_Real roundbound;
SCIP_Real obj;
SCIP_Bool infeasible;
SCIP_Bool fixed;
int nvars;
int v;
assert(presol != NULL);
assert(strcmp(SCIPpresolGetName(presol), PRESOL_NAME) == 0);
assert(result != NULL);
*result = SCIP_DIDNOTFIND;
/* get active problem variables */
vars = SCIPgetVars(scip);
nvars = SCIPgetNVars(scip);
/* look for fixable variables
* loop backwards, since a variable fixing can change the current and the subsequent slots in the vars array
*/
for( v = nvars - 1; v >= 0; --v )
{
/* don't perform dual presolving operations on deleted variables */
if( SCIPvarIsDeleted(vars[v]) )
continue;
obj = SCIPvarGetObj(vars[v]);
/* if the objective coefficient of the variable is 0 and it may be rounded both
* up and down, then fix it to the closest feasible value to 0 */
if( SCIPisZero(scip, obj) && SCIPvarMayRoundDown(vars[v]) && SCIPvarMayRoundUp(vars[v]) )
{
bound = SCIPvarGetLbGlobal(vars[v]);
if( SCIPisLT(scip, bound, 0.0) )
{
if( SCIPisLE(scip, 0.0, SCIPvarGetUbGlobal(vars[v])) )
bound = 0.0;
else
{
/* try to take an integer value, only for polishing */
roundbound = SCIPfloor(scip, SCIPvarGetUbGlobal(vars[v]));
if( roundbound < bound )
bound = SCIPvarGetUbGlobal(vars[v]);
else
bound = roundbound;
}
}
else
{
/* try to take an integer value, only for polishing */
roundbound = SCIPceil(scip, bound);
if( roundbound < SCIPvarGetUbGlobal(vars[v]) )
bound = roundbound;
}
SCIPdebugMessage("variable <%s> with objective 0 fixed to %g\n",
SCIPvarGetName(vars[v]), bound);
}
else
{
/* if it is always possible to round variable in direction of objective value,
* fix it to its proper bound
*/
if( SCIPvarMayRoundDown(vars[v]) && !SCIPisNegative(scip, obj) )
{
bound = SCIPvarGetLbGlobal(vars[v]);
if( SCIPisZero(scip, obj) && SCIPvarGetNLocksUp(vars[v]) == 1 && SCIPisInfinity(scip, -bound) )
{
/* variable can be set to -infinity, and it is only contained in one constraint:
* we hope that the corresponding constraint handler is clever enough to set/aggregate the variable
* to something more useful than -infinity and do nothing here
*/
continue;
}
SCIPdebugMessage("variable <%s> with objective %g and %d uplocks fixed to lower bound %g\n",
SCIPvarGetName(vars[v]), SCIPvarGetObj(vars[v]), SCIPvarGetNLocksUp(vars[v]), bound);
}
else if( SCIPvarMayRoundUp(vars[v]) && !SCIPisPositive(scip, obj) )
{
bound = SCIPvarGetUbGlobal(vars[v]);
if( SCIPisZero(scip, obj) && SCIPvarGetNLocksDown(vars[v]) == 1 && SCIPisInfinity(scip, bound) )
{
/* variable can be set to +infinity, and it is only contained in one constraint:
* we hope that the corresponding constraint handler is clever enough to set/aggregate the variable
* to something more useful than +infinity and do nothing here
*/
continue;
}
SCIPdebugMessage("variable <%s> with objective %g and %d downlocks fixed to upper bound %g\n",
SCIPvarGetName(vars[v]), SCIPvarGetObj(vars[v]), SCIPvarGetNLocksDown(vars[v]), bound);
}
else
continue;
}
/* apply the fixing */
if( SCIPisInfinity(scip, REALABS(bound)) && !SCIPisZero(scip, obj) )
{
SCIPdebugMessage(" -> unbounded fixing\n");
SCIPverbMessage(scip, SCIP_VERBLEVEL_NORMAL, NULL,
"problem infeasible or unbounded: variable <%s> with objective %.15g can be made infinitely %s\n",
SCIPvarGetName(vars[v]), SCIPvarGetObj(vars[v]), bound < 0.0 ? "small" : "large");
*result = SCIP_UNBOUNDED;
return SCIP_OKAY;
}
SCIP_CALL( SCIPfixVar(scip, vars[v], bound, &infeasible, &fixed) );
if( infeasible )
{
SCIPdebugMessage(" -> infeasible fixing\n");
*result = SCIP_CUTOFF;
return SCIP_OKAY;
}
assert(fixed);
(*nfixedvars)++;
*result = SCIP_SUCCESS;
}
return SCIP_OKAY;
}
/** compute value by which the solution of variable @p var can be shifted */
static
SCIP_Real calcShiftVal(
SCIP* scip, /**< SCIP data structure */
SCIP_VAR* var, /**< variable that should be shifted */
SCIP_Real solval, /**< current solution value */
SCIP_Real* activities /**< LP row activities */
)
{
SCIP_Real lb;
SCIP_Real ub;
SCIP_Real obj;
SCIP_Real shiftval;
SCIP_COL* col;
SCIP_ROW** colrows;
SCIP_Real* colvals;
SCIP_Bool shiftdown;
int ncolrows;
int i;
/* get variable's solution value, global bounds and objective coefficient */
lb = SCIPvarGetLbGlobal(var);
ub = SCIPvarGetUbGlobal(var);
obj = SCIPvarGetObj(var);
shiftval = 0.0;
shiftdown = TRUE;
/* determine shifting direction and maximal possible shifting w.r.t. corresponding bound */
if( obj > 0.0 && SCIPisFeasGE(scip, solval - 1.0, lb) )
shiftval = SCIPfeasFloor(scip, solval - lb);
else if( obj < 0.0 && SCIPisFeasLE(scip, solval + 1.0, ub) )
{
shiftval = SCIPfeasFloor(scip, ub - solval);
shiftdown = FALSE;
}
else
return 0.0;
SCIPdebugMessage("Try to shift %s variable <%s> with\n", shiftdown ? "down" : "up", SCIPvarGetName(var) );
SCIPdebugMessage(" lb:<%g> <= val:<%g> <= ub:<%g> and obj:<%g> by at most: <%g>\n", lb, solval, ub, obj, shiftval);
/* get data of LP column */
col = SCIPvarGetCol(var);
colrows = SCIPcolGetRows(col);
colvals = SCIPcolGetVals(col);
ncolrows = SCIPcolGetNLPNonz(col);
assert(ncolrows == 0 || (colrows != NULL && colvals != NULL));
/* find minimal shift value, st. all rows stay valid */
for( i = 0; i < ncolrows && shiftval > 0.0; ++i )
{
SCIP_ROW* row;
int rowpos;
row = colrows[i];
rowpos = SCIProwGetLPPos(row);
assert(-1 <= rowpos && rowpos < SCIPgetNLPRows(scip) );
/* only global rows need to be valid */
if( rowpos >= 0 && !SCIProwIsLocal(row) )
{
SCIP_Real shiftvalrow;
assert(SCIProwIsInLP(row));
if( shiftdown == (colvals[i] > 0) )
shiftvalrow = SCIPfeasFloor(scip, (activities[rowpos] - SCIProwGetLhs(row)) / ABS(colvals[i]));
else
shiftvalrow = SCIPfeasFloor(scip, (SCIProwGetRhs(row) - activities[rowpos]) / ABS(colvals[i]));
#ifdef SCIP_DEBUG
if( shiftvalrow < shiftval )
{
SCIPdebugMessage(" -> The shift value had to be reduced to <%g>, because of row <%s>.\n",
shiftvalrow, SCIProwGetName(row));
SCIPdebugMessage(" lhs:<%g> <= act:<%g> <= rhs:<%g>, colval:<%g>\n",
SCIProwGetLhs(row), activities[rowpos], SCIProwGetRhs(row), colvals[i]);
}
#endif
shiftval = MIN(shiftval, shiftvalrow);
/* shiftvalrow might be negative, if we detected infeasibility -> make sure that shiftval is >= 0 */
shiftval = MAX(shiftval, 0.0);
}
}
if( shiftdown )
shiftval *= -1.0;
/* we must not shift variables to infinity */
if( SCIPisInfinity(scip, solval + shiftval) )
shiftval = 0.0;
return shiftval;
}
/** branching execution method for external candidates */
static
SCIP_DECL_BRANCHEXECEXT(branchExecextPscost)
{ /*lint --e{715}*/
SCIP_BRANCHRULEDATA* branchruledata;
SCIP_VAR** externcands;
SCIP_Real* externcandssol;
SCIP_Real* externcandsscore;
int nprioexterncands;
SCIP_VAR* brvar;
SCIP_Real brpoint;
int nchildren;
assert(branchrule != NULL);
assert(strcmp(SCIPbranchruleGetName(branchrule), BRANCHRULE_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
SCIPdebugMessage("Execext method of pscost branching\n");
/* get branching candidates */
SCIP_CALL( SCIPgetExternBranchCands(scip, &externcands, &externcandssol, &externcandsscore, NULL, &nprioexterncands, NULL, NULL, NULL) );
assert(nprioexterncands > 0);
/* get current update strategy for pseudo costs, if our multiplier rule is 'u' */
if( branchruledata->strategy == 'u' )
{
SCIP_CALL( SCIPgetCharParam(scip, "branching/lpgainnormalize", &branchruledata->updatestrategy) );
}
/* select branching variable */
SCIP_CALL( selectBranchVar(scip, branchrule, externcands, externcandssol, externcandsscore, nprioexterncands, &brvar, &brpoint) );
if( brvar == NULL )
{
SCIPerrorMessage("branchExecextPscost failed to select a branching variable from %d candidates\n", nprioexterncands);
*result = SCIP_DIDNOTRUN;
return SCIP_OKAY;
}
assert(SCIPvarIsActive(SCIPvarGetProbvar(brvar)));
SCIPdebugMessage("branching on variable <%s>: new intervals: [%g, %g] and [%g, %g]\n",
SCIPvarGetName(brvar), SCIPvarGetLbLocal(brvar), SCIPadjustedVarUb(scip, brvar, brpoint), SCIPadjustedVarLb(scip, brvar, brpoint), SCIPvarGetUbLocal(brvar));
if( branchruledata->nchildren > 2 && SCIPnodeGetDepth(SCIPgetCurrentNode(scip)) <= branchruledata->narymaxdepth )
{
/* do n-ary branching */
SCIP_Real minwidth;
minwidth = 0.0;
if( !SCIPisInfinity(scip, -SCIPvarGetLbGlobal(brvar)) && !SCIPisInfinity(scip, SCIPvarGetUbGlobal(brvar)) )
minwidth = branchruledata->naryminwidth * (SCIPvarGetUbGlobal(brvar) - SCIPvarGetLbGlobal(brvar));
SCIP_CALL( SCIPbranchVarValNary(scip, brvar, brpoint, branchruledata->nchildren, minwidth, branchruledata->narywidthfactor, &nchildren) );
}
else
{
/* do binary branching */
SCIP_CALL( SCIPbranchVarValNary(scip, brvar, brpoint, 2, 0.0, 1.0, &nchildren) );
}
if( nchildren > 1 )
{
*result = SCIP_BRANCHED;
}
else
{
/* if there are no children, then variable should have been fixed by SCIPbranchVarVal */
assert(SCIPisEQ(scip, SCIPvarGetLbLocal(brvar), SCIPvarGetUbLocal(brvar)));
*result = SCIP_REDUCEDDOM;
}
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecOneopt)
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_SOL* bestsol; /* incumbent solution */
SCIP_SOL* worksol; /* heuristic's working solution */
SCIP_VAR** vars; /* SCIP variables */
SCIP_VAR** shiftcands; /* shiftable variables */
SCIP_ROW** lprows; /* SCIP LP rows */
SCIP_Real* activities; /* row activities for working solution */
SCIP_Real* shiftvals;
SCIP_Real lb;
SCIP_Real ub;
SCIP_Bool localrows;
SCIP_Bool valid;
int nchgbound;
int nbinvars;
int nintvars;
int nvars;
int nlprows;
int i;
int nshiftcands;
int shiftcandssize;
SCIP_RETCODE retcode;
assert(heur != NULL);
assert(scip != NULL);
assert(result != NULL);
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
*result = SCIP_DELAYED;
/* we only want to process each solution once */
bestsol = SCIPgetBestSol(scip);
if( bestsol == NULL || heurdata->lastsolindex == SCIPsolGetIndex(bestsol) )
return SCIP_OKAY;
/* reset the timing mask to its default value (at the root node it could be different) */
if( SCIPgetNNodes(scip) > 1 )
SCIPheurSetTimingmask(heur, HEUR_TIMING);
/* get problem variables */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
nintvars += nbinvars;
/* do not run if there are no discrete variables */
if( nintvars == 0 )
{
*result = SCIP_DIDNOTRUN;
return SCIP_OKAY;
}
if( heurtiming == SCIP_HEURTIMING_BEFOREPRESOL )
{
SCIP* subscip; /* the subproblem created by zeroobj */
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_Real* subsolvals; /* solution values of the subproblem */
SCIP_Real timelimit; /* time limit for zeroobj subproblem */
SCIP_Real memorylimit; /* memory limit for zeroobj subproblem */
SCIP_SOL* startsol;
SCIP_SOL** subsols;
int nsubsols;
if( !heurdata->beforepresol )
return SCIP_OKAY;
/* check whether there is enough time and memory left */
timelimit = 0.0;
memorylimit = 0.0;
SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
if( !SCIPisInfinity(scip, timelimit) )
timelimit -= SCIPgetSolvingTime(scip);
SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
/* substract the memory already used by the main SCIP and the estimated memory usage of external software */
if( !SCIPisInfinity(scip, memorylimit) )
{
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
}
/* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
return SCIP_OKAY;
/* initialize the subproblem */
SCIP_CALL( SCIPcreate(&subscip) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
/* copy complete SCIP instance */
valid = FALSE;
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "oneopt", TRUE, FALSE, TRUE, &valid) );
SCIP_CALL( SCIPtransformProb(subscip) );
/* get variable image */
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
/* copy the solution */
SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );
SCIP_CALL( SCIPgetSolVals(scip, bestsol, nvars, vars, subsolvals) );
/* create start solution for the subproblem */
SCIP_CALL( SCIPcreateOrigSol(subscip, &startsol, NULL) );
SCIP_CALL( SCIPsetSolVals(subscip, startsol, nvars, subvars, subsolvals) );
/* try to add new solution to sub-SCIP and free it immediately */
valid = FALSE;
SCIP_CALL( SCIPtrySolFree(subscip, &startsol, FALSE, FALSE, FALSE, FALSE, &valid) );
SCIPfreeBufferArray(scip, &subsolvals);
SCIPhashmapFree(&varmapfw);
/* disable statistic timing inside sub SCIP */
SCIP_CALL( SCIPsetBoolParam(subscip, "timing/statistictiming", FALSE) );
/* deactivate basically everything except oneopt in the sub-SCIP */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
SCIP_CALL( SCIPsetHeuristics(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", 1LL) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
/* if necessary, some of the parameters have to be unfixed first */
if( SCIPisParamFixed(subscip, "lp/solvefreq") )
{
SCIPwarningMessage(scip, "unfixing parameter lp/solvefreq in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "lp/solvefreq") );
}
SCIP_CALL( SCIPsetIntParam(subscip, "lp/solvefreq", -1) );
if( SCIPisParamFixed(subscip, "heuristics/oneopt/freq") )
{
SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/freq in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/freq") );
}
SCIP_CALL( SCIPsetIntParam(subscip, "heuristics/oneopt/freq", 1) );
if( SCIPisParamFixed(subscip, "heuristics/oneopt/forcelpconstruction") )
{
SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/forcelpconstruction in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/forcelpconstruction") );
}
SCIP_CALL( SCIPsetBoolParam(subscip, "heuristics/oneopt/forcelpconstruction", TRUE) );
/* avoid recursive call, which would lead to an endless loop */
if( SCIPisParamFixed(subscip, "heuristics/oneopt/beforepresol") )
{
SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/beforepresol in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/beforepresol") );
}
SCIP_CALL( SCIPsetBoolParam(subscip, "heuristics/oneopt/beforepresol", FALSE) );
if( valid )
{
retcode = SCIPsolve(subscip);
/* errors in solving the subproblem should not kill the overall solving process;
* hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage(scip, "Error while solving subproblem in zeroobj heuristic; sub-SCIP terminated with code <%d>\n",retcode);
}
#ifdef SCIP_DEBUG
SCIP_CALL( SCIPprintStatistics(subscip, NULL) );
#endif
}
/* check, whether a solution was found;
* due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
*/
nsubsols = SCIPgetNSols(subscip);
subsols = SCIPgetSols(subscip);
valid = FALSE;
for( i = 0; i < nsubsols && !valid; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &valid) );
if( valid )
*result = SCIP_FOUNDSOL;
}
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/* we can only work on solutions valid in the transformed space */
if( SCIPsolIsOriginal(bestsol) )
return SCIP_OKAY;
if( heurtiming == SCIP_HEURTIMING_BEFORENODE && (SCIPhasCurrentNodeLP(scip) || heurdata->forcelpconstruction) )
{
SCIP_Bool cutoff;
cutoff = FALSE;
SCIP_CALL( SCIPconstructLP(scip, &cutoff) );
SCIP_CALL( SCIPflushLP(scip) );
/* get problem variables again, SCIPconstructLP() might have added new variables */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
nintvars += nbinvars;
}
/* we need an LP */
if( SCIPgetNLPRows(scip) == 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
nchgbound = 0;
/* initialize data */
nshiftcands = 0;
shiftcandssize = 8;
heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
SCIP_CALL( SCIPcreateSolCopy(scip, &worksol, bestsol) );
SCIPsolSetHeur(worksol,heur);
SCIPdebugMessage("Starting bound adjustment in 1-opt heuristic\n");
/* maybe change solution values due to global bound changes first */
for( i = nvars - 1; i >= 0; --i )
{
SCIP_VAR* var;
SCIP_Real solval;
var = vars[i];
lb = SCIPvarGetLbGlobal(var);
ub = SCIPvarGetUbGlobal(var);
solval = SCIPgetSolVal(scip, bestsol,var);
/* old solution value is smaller than the actual lower bound */
if( SCIPisFeasLT(scip, solval, lb) )
{
/* set the solution value to the global lower bound */
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, lb) );
++nchgbound;
SCIPdebugMessage("var <%s> type %d, old solval %g now fixed to lb %g\n", SCIPvarGetName(var), SCIPvarGetType(var), solval, lb);
}
/* old solution value is greater than the actual upper bound */
else if( SCIPisFeasGT(scip, solval, SCIPvarGetUbGlobal(var)) )
{
/* set the solution value to the global upper bound */
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, ub) );
++nchgbound;
SCIPdebugMessage("var <%s> type %d, old solval %g now fixed to ub %g\n", SCIPvarGetName(var), SCIPvarGetType(var), solval, ub);
}
}
SCIPdebugMessage("number of bound changes (due to global bounds) = %d\n", nchgbound);
SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );
localrows = FALSE;
valid = TRUE;
/* initialize activities */
for( i = 0; i < nlprows; ++i )
{
SCIP_ROW* row;
row = lprows[i];
assert(SCIProwGetLPPos(row) == i);
if( !SCIProwIsLocal(row) )
{
activities[i] = SCIPgetRowSolActivity(scip, row, worksol);
SCIPdebugMessage("Row <%s> has activity %g\n", SCIProwGetName(row), activities[i]);
if( SCIPisFeasLT(scip, activities[i], SCIProwGetLhs(row)) || SCIPisFeasGT(scip, activities[i], SCIProwGetRhs(row)) )
{
valid = FALSE;
SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );
SCIPdebugMessage("row <%s> activity %g violates bounds, lhs = %g, rhs = %g\n", SCIProwGetName(row), activities[i], SCIProwGetLhs(row), SCIProwGetRhs(row));
break;
}
}
else
localrows = TRUE;
}
if( !valid )
{
/** @todo try to correct lp rows */
SCIPdebugMessage("Some global bound changes were not valid in lp rows.\n");
goto TERMINATE;
}
SCIP_CALL( SCIPallocBufferArray(scip, &shiftcands, shiftcandssize) );
SCIP_CALL( SCIPallocBufferArray(scip, &shiftvals, shiftcandssize) );
SCIPdebugMessage("Starting 1-opt heuristic\n");
/* enumerate all integer variables and find out which of them are shiftable */
for( i = 0; i < nintvars; i++ )
{
if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
{
SCIP_Real shiftval;
SCIP_Real solval;
/* find out whether the variable can be shifted */
solval = SCIPgetSolVal(scip, worksol, vars[i]);
shiftval = calcShiftVal(scip, vars[i], solval, activities);
/* insert the variable into the list of shifting candidates */
if( !SCIPisFeasZero(scip, shiftval) )
{
SCIPdebugMessage(" -> Variable <%s> can be shifted by <%1.1f> \n", SCIPvarGetName(vars[i]), shiftval);
if( nshiftcands == shiftcandssize)
{
shiftcandssize *= 8;
SCIP_CALL( SCIPreallocBufferArray(scip, &shiftcands, shiftcandssize) );
SCIP_CALL( SCIPreallocBufferArray(scip, &shiftvals, shiftcandssize) );
}
shiftcands[nshiftcands] = vars[i];
shiftvals[nshiftcands] = shiftval;
nshiftcands++;
}
}
}
/* if at least one variable can be shifted, shift variables sorted by their objective */
if( nshiftcands > 0 )
{
SCIP_Real shiftval;
SCIP_Real solval;
SCIP_VAR* var;
/* the case that exactly one variable can be shifted is slightly easier */
if( nshiftcands == 1 )
{
var = shiftcands[0];
assert(var != NULL);
solval = SCIPgetSolVal(scip, worksol, var);
shiftval = shiftvals[0];
assert(!SCIPisFeasZero(scip,shiftval));
SCIPdebugMessage(" Only one shiftcand found, var <%s>, which is now shifted by<%1.1f> \n",
SCIPvarGetName(var), shiftval);
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, solval+shiftval) );
}
else
{
SCIP_Real* objcoeffs;
SCIP_CALL( SCIPallocBufferArray(scip, &objcoeffs, nshiftcands) );
SCIPdebugMessage(" %d shiftcands found \n", nshiftcands);
/* sort the variables by their objective, optionally weighted with the shiftval */
if( heurdata->weightedobj )
{
for( i = 0; i < nshiftcands; ++i )
objcoeffs[i] = SCIPvarGetObj(shiftcands[i])*shiftvals[i];
}
else
{
for( i = 0; i < nshiftcands; ++i )
objcoeffs[i] = SCIPvarGetObj(shiftcands[i]);
}
/* sort arrays with respect to the first one */
SCIPsortRealPtr(objcoeffs, (void**)shiftcands, nshiftcands);
/* try to shift each variable -> Activities have to be updated */
for( i = 0; i < nshiftcands; ++i )
{
var = shiftcands[i];
assert(var != NULL);
solval = SCIPgetSolVal(scip, worksol, var);
shiftval = calcShiftVal(scip, var, solval, activities);
SCIPdebugMessage(" -> Variable <%s> is now shifted by <%1.1f> \n", SCIPvarGetName(vars[i]), shiftval);
assert(i > 0 || !SCIPisFeasZero(scip, shiftval));
assert(SCIPisFeasGE(scip, solval+shiftval, SCIPvarGetLbGlobal(var)) && SCIPisFeasLE(scip, solval+shiftval, SCIPvarGetUbGlobal(var)));
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, solval+shiftval) );
SCIP_CALL( updateRowActivities(scip, activities, var, shiftval) );
}
SCIPfreeBufferArray(scip, &objcoeffs);
}
/* if the problem is a pure IP, try to install the solution, if it is a MIP, solve LP again to set the continuous
* variables to the best possible value
*/
if( nvars == nintvars || !SCIPhasCurrentNodeLP(scip) || SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
{
SCIP_Bool success;
/* since we ignore local rows, we cannot guarantee their feasibility and have to set the checklprows flag to
* TRUE if local rows are present
*/
SCIP_CALL( SCIPtrySol(scip, worksol, FALSE, FALSE, FALSE, localrows, &success) );
if( success )
{
SCIPdebugMessage("found feasible shifted solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, worksol, NULL, FALSE) ) );
heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
*result = SCIP_FOUNDSOL;
}
}
else
{
SCIP_Bool lperror;
#ifdef NDEBUG
SCIP_RETCODE retstat;
#endif
SCIPdebugMessage("shifted solution should be feasible -> solve LP to fix continuous variables to best values\n");
/* start diving to calculate the LP relaxation */
SCIP_CALL( SCIPstartDive(scip) );
/* set the bounds of the variables: fixed for integers, global bounds for continuous */
for( i = 0; i < nvars; ++i )
{
if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
{
SCIP_CALL( SCIPchgVarLbDive(scip, vars[i], SCIPvarGetLbGlobal(vars[i])) );
SCIP_CALL( SCIPchgVarUbDive(scip, vars[i], SCIPvarGetUbGlobal(vars[i])) );
}
}
/* apply this after global bounds to not cause an error with intermediate empty domains */
for( i = 0; i < nintvars; ++i )
{
if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
{
solval = SCIPgetSolVal(scip, worksol, vars[i]);
SCIP_CALL( SCIPchgVarLbDive(scip, vars[i], solval) );
SCIP_CALL( SCIPchgVarUbDive(scip, vars[i], solval) );
}
}
/* solve LP */
SCIPdebugMessage(" -> old LP iterations: %" SCIP_LONGINT_FORMAT "\n", SCIPgetNLPIterations(scip));
/**@todo in case of an MINLP, if SCIPisNLPConstructed() is TRUE, say, rather solve the NLP instead of the LP */
/* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic.
* Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
#ifdef NDEBUG
retstat = SCIPsolveDiveLP(scip, -1, &lperror, NULL);
if( retstat != SCIP_OKAY )
{
SCIPwarningMessage(scip, "Error while solving LP in Oneopt heuristic; LP solve terminated with code <%d>\n",retstat);
}
#else
SCIP_CALL( SCIPsolveDiveLP(scip, -1, &lperror, NULL) );
#endif
SCIPdebugMessage(" -> new LP iterations: %" SCIP_LONGINT_FORMAT "\n", SCIPgetNLPIterations(scip));
SCIPdebugMessage(" -> error=%u, status=%d\n", lperror, SCIPgetLPSolstat(scip));
/* check if this is a feasible solution */
if( !lperror && SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OPTIMAL )
{
SCIP_Bool success;
/* copy the current LP solution to the working solution */
SCIP_CALL( SCIPlinkLPSol(scip, worksol) );
SCIP_CALL( SCIPtrySol(scip, worksol, FALSE, FALSE, FALSE, FALSE, &success) );
/* check solution for feasibility */
if( success )
{
SCIPdebugMessage("found feasible shifted solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, worksol, NULL, FALSE) ) );
heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
*result = SCIP_FOUNDSOL;
}
}
/* terminate the diving */
SCIP_CALL( SCIPendDive(scip) );
}
}
SCIPdebugMessage("Finished 1-opt heuristic\n");
SCIPfreeBufferArray(scip, &shiftvals);
SCIPfreeBufferArray(scip, &shiftcands);
TERMINATE:
SCIPfreeBufferArray(scip, &activities);
SCIP_CALL( SCIPfreeSol(scip, &worksol) );
return SCIP_OKAY;
}
/** creates a subproblem for subscip by fixing a number of variables */
static
SCIP_RETCODE createSubproblem(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP data structure for the subproblem */
SCIP_VAR** subvars, /**< the variables of the subproblem */
SCIP_Real minfixingrate, /**< percentage of integer variables that have to be fixed */
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;
}
/** presolving execution method */
static
SCIP_DECL_PRESOLEXEC(presolExecTrivial)
{ /*lint --e{715}*/
SCIP_VAR** vars;
int nvars;
int v;
assert(result != NULL);
*result = SCIP_DIDNOTFIND;
/* get the problem variables */
vars = SCIPgetVars(scip);
nvars = SCIPgetNVars(scip);
/* scan the variables for trivial bound reductions
* (loop backwards, since a variable fixing can change the current and the subsequent slots in the vars array)
*/
for( v = nvars-1; v >= 0; --v )
{
SCIP_Real lb;
SCIP_Real ub;
SCIP_Bool infeasible;
SCIP_Bool fixed;
/* get variable's bounds */
lb = SCIPvarGetLbGlobal(vars[v]);
ub = SCIPvarGetUbGlobal(vars[v]);
/* is variable integral? */
if( SCIPvarGetType(vars[v]) != SCIP_VARTYPE_CONTINUOUS )
{
SCIP_Real newlb;
SCIP_Real newub;
/* round fractional bounds on integer variables */
newlb = SCIPfeasCeil(scip, lb);
newub = SCIPfeasFloor(scip, ub);
/* check bounds on variable for infeasibility */
if( newlb > newub + 0.5 )
{
SCIPverbMessage(scip, SCIP_VERBLEVEL_NORMAL, NULL,
"problem infeasible: integral variable <%s> has bounds [%.17f,%.17f] rounded to [%.17f,%.17f]\n",
SCIPvarGetName(vars[v]), lb, ub, newlb, newub);
*result = SCIP_CUTOFF;
return SCIP_OKAY;
}
/* fix variables with equal bounds */
if( newlb > newub - 0.5 )
{
SCIPdebugMessage("fixing integral variable <%s>: [%.17f,%.17f] -> [%.17f,%.17f]\n",
SCIPvarGetName(vars[v]), lb, ub, newlb, newub);
SCIP_CALL( SCIPfixVar(scip, vars[v], newlb, &infeasible, &fixed) );
if( infeasible )
{
SCIPdebugMessage(" -> infeasible fixing\n");
*result = SCIP_CUTOFF;
return SCIP_OKAY;
}
assert(fixed);
(*nfixedvars)++;
}
else
{
/* round fractional bounds */
if( !SCIPisFeasEQ(scip, lb, newlb) )
{
SCIPdebugMessage("rounding lower bound of integral variable <%s>: [%.17f,%.17f] -> [%.17f,%.17f]\n",
SCIPvarGetName(vars[v]), lb, ub, newlb, ub);
SCIP_CALL( SCIPchgVarLb(scip, vars[v], newlb) );
(*nchgbds)++;
}
if( !SCIPisFeasEQ(scip, ub, newub) )
{
SCIPdebugMessage("rounding upper bound of integral variable <%s>: [%.17f,%.17f] -> [%.17f,%.17f]\n",
SCIPvarGetName(vars[v]), newlb, ub, newlb, newub);
SCIP_CALL( SCIPchgVarUb(scip, vars[v], newub) );
(*nchgbds)++;
}
}
}
else
{
/* check bounds on continuous variable for infeasibility */
if( SCIPisFeasGT(scip, lb, ub) )
{
SCIPverbMessage(scip, SCIP_VERBLEVEL_NORMAL, NULL,
"problem infeasible: continuous variable <%s> has bounds [%.17f,%.17f]\n",
SCIPvarGetName(vars[v]), lb, ub);
*result = SCIP_CUTOFF;
return SCIP_OKAY;
}
/* fix variables with equal bounds */
if( SCIPisEQ(scip, lb, ub) )
{
SCIP_Real fixval;
#ifdef FIXSIMPLEVALUE
fixval = SCIPselectSimpleValue(lb - 0.9 * SCIPepsilon(scip), ub + 0.9 * SCIPepsilon(scip), MAXDNOM);
#else
fixval = (lb + ub)/2;
#endif
SCIPdebugMessage("fixing continuous variable <%s>[%.17f,%.17f] to %.17f\n",
SCIPvarGetName(vars[v]), lb, ub, fixval);
SCIP_CALL( SCIPfixVar(scip, vars[v], fixval, &infeasible, &fixed) );
if( infeasible )
{
SCIPdebugMessage(" -> infeasible fixing\n");
*result = SCIP_CUTOFF;
return SCIP_OKAY;
}
assert(fixed);
(*nfixedvars)++;
}
}
}
return SCIP_OKAY;
}
/** presolving execution method */
static
SCIP_DECL_PRESOLEXEC(presolExecInttobinary)
{ /*lint --e{715}*/
SCIP_VAR** scipvars;
SCIP_VAR** vars;
int nbinvars;
int nintvars;
int v;
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
if( SCIPdoNotAggr(scip) )
return SCIP_OKAY;
/* get the problem variables */
scipvars = SCIPgetVars(scip);
nbinvars = SCIPgetNBinVars(scip);
nintvars = SCIPgetNIntVars(scip);
if( nintvars == 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
/* copy the integer variables into an own array, since adding binary variables affects the left-most slots in the
* array and thereby interferes with our search loop
*/
SCIP_CALL( SCIPduplicateBufferArray(scip, &vars, &scipvars[nbinvars], nintvars) );
/* scan the integer variables for possible conversion into binaries;
* we have to collect the variables first in an own
*/
for( v = 0; v < nintvars; ++v )
{
SCIP_Real lb;
SCIP_Real ub;
assert(SCIPvarGetType(vars[v]) == SCIP_VARTYPE_INTEGER);
/* get variable's bounds */
lb = SCIPvarGetLbGlobal(vars[v]);
ub = SCIPvarGetUbGlobal(vars[v]);
/* check if bounds are exactly one apart */
if( SCIPisEQ(scip, lb, ub - 1.0) )
{
SCIP_VAR* binvar;
char binvarname[SCIP_MAXSTRLEN];
SCIP_Bool infeasible;
SCIP_Bool redundant;
SCIP_Bool aggregated;
SCIPdebugMessage("converting <%s>[%g,%g] into binary variable\n", SCIPvarGetName(vars[v]), lb, ub);
/* create binary variable */
(void) SCIPsnprintf(binvarname, SCIP_MAXSTRLEN, "%s_bin", SCIPvarGetName(vars[v]));
SCIP_CALL( SCIPcreateVar(scip, &binvar, binvarname, 0.0, 1.0, 0.0, SCIP_VARTYPE_BINARY,
SCIPvarIsInitial(vars[v]), SCIPvarIsRemovable(vars[v]), NULL, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPaddVar(scip, binvar) );
/* aggregate integer and binary variable */
SCIP_CALL( SCIPaggregateVars(scip, vars[v], binvar, 1.0, -1.0, lb, &infeasible, &redundant, &aggregated) );
/* release binary variable */
SCIP_CALL( SCIPreleaseVar(scip, &binvar) );
/* it can be the case that this aggregation detects an infeasibility; for example, during the copy of the
* variable bounds from the integer variable to the binary variable, infeasibility can be detected; this can
* happen because an upper bound or a lower bound of such a variable bound variable was "just" changed and the
* varbound constraint handler, who would detect that infeasibility (since it was creating it from a varbound
* constraint), was called before that bound change was detected due to the presolving priorities;
*/
if( infeasible )
{
*result = SCIP_CUTOFF;
break;
}
assert(redundant);
assert(aggregated);
(*nchgvartypes)++;
*result = SCIP_SUCCESS;
}
}
/* free temporary memory */
SCIPfreeBufferArray(scip, &vars);
return SCIP_OKAY;
}
/** gets value of given variable in debugging solution */
static
SCIP_RETCODE getSolutionValue(
SCIP_SET* set, /**< global SCIP settings */
SCIP_VAR* var, /**< variable to get solution value for */
SCIP_Real* val /**< pointer to store solution value */
)
{
SCIP_VAR* solvar;
SCIP_Real scalar;
SCIP_Real constant;
const char* name;
int left;
int right;
int middle;
int cmp;
assert(set != NULL);
assert(var != NULL);
assert(val != NULL);
SCIP_CALL( readSolution(set) );
SCIPdebugMessage("Now handling variable <%s>, which has status %d, is of type %d, and was deleted: %d, negated: %d, transformed: %d\n",
SCIPvarGetName(var), SCIPvarGetStatus(var), SCIPvarGetType(var), SCIPvarIsDeleted(var), SCIPvarIsNegated(var),SCIPvarIsTransformedOrigvar(var));
/* ignore deleted variables */
if( SCIPvarIsDeleted(var) )
{
SCIPdebugMessage("**** unknown solution value for deleted variable <%s>\n", SCIPvarGetName(var));
*val = SCIP_UNKNOWN;
return SCIP_OKAY;
}
/* retransform variable onto original variable space */
solvar = var;
scalar = 1.0;
constant = 0.0;
if( SCIPvarIsNegated(solvar) )
{
scalar = -1.0;
constant = SCIPvarGetNegationConstant(solvar);
solvar = SCIPvarGetNegationVar(solvar);
}
if( SCIPvarIsTransformed(solvar) )
{
SCIP_CALL( SCIPvarGetOrigvarSum(&solvar, &scalar, &constant) );
if( solvar == NULL )
{
/* if no original counterpart, then maybe someone added a value for the transformed variable, so search for var (or its negation) */
SCIPdebugMessage("variable <%s> has no original counterpart\n", SCIPvarGetName(var));
solvar = var;
scalar = 1.0;
constant = 0.0;
if( SCIPvarIsNegated(solvar) )
{
scalar = -1.0;
constant = SCIPvarGetNegationConstant(solvar);
solvar = SCIPvarGetNegationVar(solvar);
}
}
}
/* perform a binary search for the variable */
name = SCIPvarGetName(solvar);
left = 0;
right = nsolvals-1;
while( left <= right )
{
middle = (left+right)/2;
cmp = strcmp(name, solnames[middle]);
if( cmp < 0 )
right = middle-1;
else if( cmp > 0 )
left = middle+1;
else
{
*val = scalar * solvals[middle] + constant;
return SCIP_OKAY;
}
}
*val = constant;
if( *val < SCIPvarGetLbGlobal(var) - 1e-06 || *val > SCIPvarGetUbGlobal(var) + 1e-06 )
{
SCIPwarningMessage("invalid solution value %.15g for variable <%s>[%.15g,%.15g]\n",
*val, SCIPvarGetName(var), SCIPvarGetLbGlobal(var), SCIPvarGetUbGlobal(var));
}
return SCIP_OKAY;
}
