/** creates and captures a linear constraint
* in its most basic version, i. e., all constraint flags are set to their basic value as explained for the
* method SCIPcreateConsLinear(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h
*
* @see SCIPcreateConsLinear() for information about the basic constraint flag configuration
*
* @note the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()
*/
JNIEXPORT
jlong JNISCIPCONSLINEAR(createConsBasicLinear)(
JNIEnv* env, /**< JNI environment variable */
jobject jobj, /**< JNI class pointer */
jlong jscip, /**< SCIP data structure */
jstring jname, /**< name of constraint */
jint jnvars, /**< number of nonzeros in the constraint */
jlongArray jvars, /**< array with variables of constraint entries */
jdoubleArray jvals, /**< array with coefficients of constraint entries */
jdouble jlhs, /**< left hand side of constraint */
jdouble jrhs /**< right hand side of constraint */
)
{
SCIP* scip;
SCIP_CONS* cons;
const char* name;
int nvars;
/* convert JNI pointer into C pointer */
scip = (SCIP*) (size_t) jscip;
assert(scip != NULL);
/* convert JNI string into C const char* */
name = (*env)->GetStringUTFChars(env, jname, NULL);
if( name == NULL )
SCIPABORT();
/* create linear constraint with zero variables */
JNISCIP_CALL( SCIPcreateConsBasicLinear(scip, &cons, name, 0, NULL, NULL, (SCIP_Real) jlhs, (SCIP_Real) jrhs) );
/* convert JNI integer into integer */
nvars = (int)jnvars;
if( nvars > 0 )
{
jlong* vars;
jdouble* vals;
int v;
JNISCIP_CALL( SCIPallocBufferArray(scip, &vars, nvars) );
JNISCIP_CALL( SCIPallocBufferArray(scip, &vals, nvars) );
(*env)->GetLongArrayRegion(env, jvars, 0, nvars, vars);
(*env)->GetDoubleArrayRegion(env, jvals, 0, nvars, vals);
for( v = 0; v < nvars; ++v )
{
JNISCIP_CALL( SCIPaddCoefLinear(scip, cons, (SCIP_VAR*)(size_t)vars[v], (SCIP_Real)vals[v]));
}
SCIPfreeBufferArray(scip, &vals);
SCIPfreeBufferArray(scip, &vars);
}
/* relase string object */
(*env)->ReleaseStringUTFChars(env, jname, name);
return (jlong)(size_t)cons;
}
/** writes problem to file */
JNIEXPORT
jint JNISCIPREADERPIP(writePip)(
JNIEnv* env, /**< JNI environment variable */
jobject jobj, /**< JNI class pointer */
jlong jscip, /**< SCIP data structure */
jlong jfile, /**< output file, or NULL if standard output should be used */
jstring jname, /**< problem name */
jboolean jtransformed, /**< TRUE iff problem is the transformed problem */
jint jobjsense, /**< objective sense */
jdouble jobjscale, /**< scalar applied to objective function; external objective value is
* extobj = objsense * objscale * (intobj + objoffset) */
jdouble jobjoffset, /**< objective offset from bound shifting and fixing */
jlongArray jvars, /**< array with active variables ordered binary, integer, implicit, continuous */
jint jnvars, /**< number of mutable variables in the problem */
jint jnbinvars, /**< number of binary variables */
jint jnintvars, /**< number of general integer variables */
jint jnimplvars, /**< number of implicit integer variables */
jint jncontvars, /**< number of continuous variables */
jlongArray jconss, /**< array with constraints of the problem */
jint jnconss /**< number of constraints in the problem */
)
{
SCIP* scip;
const char* name;
SCIP_VAR** vars;
SCIP_CONS** conss;
SCIP_RESULT result;
jboolean iscopy;
/* convert JNI pointer into C pointer */
scip = (SCIP*) (size_t) jscip;
assert(scip != NULL);
JNISCIP_CALL( SCIPallocBufferArray(scip, &vars, (int)jnvars) );
JNISCIP_CALL( SCIPallocBufferArray(scip, &conss, (int)jnconss) );
(*env)->GetLongArrayRegion(env, jvars, 0, jnvars, (jlong*)(*vars));
(*env)->GetLongArrayRegion(env, jconss, 0, jnconss, (jlong*)(*conss));
/* convert JNI string into C const char* */
name = (*env)->GetStringUTFChars(env, jname, &iscopy);
if( name == NULL )
SCIPABORT();
assert(iscopy);
JNISCIP_CALL( SCIPwritePip(scip, (FILE*)(size_t) jfile, name, (SCIP_Bool)jtransformed, (SCIP_OBJSENSE)jobjsense, (SCIP_Real)jobjscale, (SCIP_Real)jobjoffset, vars, (int)jnvars, (int)jnbinvars, (int)jnintvars, (jint)jnimplvars, (int)jncontvars, conss, (int)jnconss, &result) );
SCIPfreeBufferArray(scip, &vars);
SCIPfreeBufferArray(scip, &conss);
(*env)->ReleaseStringUTFChars(env, jname, name);
return (jint) result;
}
/** creates a new solution for the original problem by copying the solution of the subproblem */
static
SCIP_RETCODE createNewSol(
SCIP* scip, /**< original SCIP data structure */
SCIP_HEUR* heur, /**< the current heuristic */
SCIP_SOL* sol, /**< solution of the subproblem */
SCIP_Bool* success /**< used to store whether new solution was found or not */
)
{
SCIP_VAR** vars; /* the original problem's variables */
int nvars; /* the original problem's number of variables */
SCIP_Real* solvals; /* solution values of the subproblem */
SCIP_SOL* newsol; /* solution to be created for the original problem */
assert(scip != NULL);
/* get variables' data */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPallocBufferArray(scip, &solvals, nvars) );
/* copy the solution */
SCIP_CALL( SCIPgetSolVals(scip, sol, nvars, vars, solvals) );
/* create new solution for the original problem */
SCIP_CALL( SCIPcreateSol(scip, &newsol, heur) );
SCIP_CALL( SCIPsetSolVals(scip, newsol, nvars, vars, solvals) );
/* try to add new solution to scip and free it immediately */
SCIP_CALL( SCIPtrySolFree(scip, &newsol, FALSE, TRUE, TRUE, TRUE, success) );
SCIPfreeBufferArray(scip, &solvals);
return SCIP_OKAY;
}
static
SCIP_RETCODE selectBranchingVertex(
SCIP* scip, /**< original SCIP data structure */
int* vertex /**< the vertex to branch on */
)
{
SCIP_PROBDATA* probdata;
SCIP_VAR** edgevars;
GRAPH* g;
SCIP_Real maxflow;
SCIP_Real* inflow;
int a;
int k;
int nnodes;
int branchvert;
/* get problem data */
probdata = SCIPgetProbData(scip);
assert(probdata != NULL);
/* get graph */
g = SCIPprobdataGetGraph(probdata);
assert(g != NULL);
/* LP has not been solved */
if( !SCIPhasCurrentNodeLP(scip) || SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
{
*vertex = UNKNOWN;
return SCIP_OKAY;
}
edgevars = SCIPprobdataGetEdgeVars(scip);
assert(edgevars != NULL);
nnodes = g->knots;
SCIP_CALL( SCIPallocBufferArray(scip, &inflow, nnodes) );
branchvert = UNKNOWN;
maxflow = 1.0;
for( k = 0; k < nnodes; k++ )
{
inflow[k] = 0.0;
for( a = g->inpbeg[k]; a != EAT_LAST; a = g->ieat[a] )
inflow[k] += SCIPvarGetLPSol(edgevars[a]);
if( !Is_term(g->term[k]) && SCIPisLT(scip, inflow[k], 1.0) && SCIPisLT(scip, fabs(inflow[k] - 0.5), maxflow) )
{
branchvert = k;
maxflow = fabs(inflow[k] - 0.5);
SCIPdebugMessage("new maxflow %f on vertex %d \n", inflow[k], branchvert );
}
}
SCIPdebugMessage("maxflow %f on vertex %d, term? %d \n", maxflow, branchvert, Is_term(g->term[branchvert]) );
(*vertex) = branchvert;
SCIPfreeBufferArray(scip, &inflow);
return SCIP_OKAY;
}
/** writes problem to file */
JNIEXPORT
jint JNISCIPREADERCCG(writeCcg)(
JNIEnv* env, /**< JNI environment variable */
jobject jobj, /**< JNI class pointer */
jlong jscip, /**< SCIP data structure */
jlong jfile, /**< output file, or NULL if standard output should be used */
jstring jname, /**< problem name */
jboolean jtransformed, /**< TRUE iff problem is the transformed problem */
jlongArray jvars, /**< array with active variables ordered binary, integer, implicit, continuous */
jint jnvars, /**< number of mutable variables in the problem */
jlongArray jconss, /**< array with constraints of the problem */
jint jnconss /**< number of constraints in the problem */
)
{
SCIP* scip;
const char* name;
SCIP_VAR** vars;
SCIP_CONS** conss;
SCIP_RESULT result;
jboolean iscopy;
/* convert JNI pointer into C pointer */
scip = (SCIP*) (size_t) jscip;
assert(scip != NULL);
JNISCIP_CALL( SCIPallocBufferArray(scip, &vars, (int)jnvars) );
JNISCIP_CALL( SCIPallocBufferArray(scip, &conss, (int)jnconss) );
(*env)->GetLongArrayRegion(env, jvars, 0, jnvars, (jlong*)(*vars));
(*env)->GetLongArrayRegion(env, jconss, 0, jnconss, (jlong*)(*conss));
/* convert JNI string into C const char* */
name = (*env)->GetStringUTFChars(env, jname, &iscopy);
if( name == NULL )
SCIPABORT();
assert(iscopy);
JNISCIP_CALL( SCIPwriteCcg(scip, (FILE*)(size_t)jfile, name, (SCIP_Bool)jtransformed, vars, (int)jnvars, conss, (int)jnconss, &result) );
SCIPfreeBufferArray(scip, &vars);
SCIPfreeBufferArray(scip, &conss);
(*env)->ReleaseStringUTFChars(env, jname, name);
return (jint) result;
}
/** creates and captures an indicator constraint with given linear constraint and slack variable
* in its most basic version, i. e., all constraint flags are set to their basic value as explained for the
* method SCIPcreateConsIndicator(); all flags can be set via SCIPsetConsFLAGNAME-methods in scip.h
*
* @note @a binvar is checked to be binary only later. This enables a change of the type in
* procedures reading an instance.
*
* @note we assume that @a slackvar actually appears in @a lincons and we also assume that it takes
* the role of a slack variable!
*
* @note the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()
*
* @see SCIPcreateConsIndicatorLinCons() for information about the basic constraint flag configuration
*
* @note the constraint gets captured, hence at one point you have to release it using the method SCIPreleaseCons()
*/
JNIEXPORT
jlong JNISCIPCONSINDICATOR(createConsBasicIndicator)(
JNIEnv* env, /**< JNI environment variable */
jobject jobj, /**< JNI class pointer */
jlong jscip, /**< SCIP data structure */
jstring jname, /**< name of constraint */
jlong jbinvar, /**< binary indicator variable (or NULL) */
jint nvars, /**< number of variables in the inequality */
jlongArray jvars, /**< array with variables of inequality (or NULL) */
jdoubleArray jvals, /**< values of variables in inequality (or NULL) */
jdouble rhs /**< rhs of the inequality */
)
{
SCIP* scip;
SCIP_CONS* cons;
const char* name;
SCIP_VAR* binvar;
SCIP_VAR** vars;
SCIP_Real* vals;
/* convert JNI pointer into C pointer */
scip = (SCIP*) (size_t) jscip;
assert(scip != NULL);
/* convert JNI string into C const char* */
name = (*env)->GetStringUTFChars(env, jname, NULL);
if( name == NULL )
SCIPABORT();
/* convert JNI pointer into C pointer */
binvar = (SCIP_VAR*) (size_t) jbinvar;
JNISCIP_CALL( SCIPallocBufferArray(scip, &vars, nvars) );
JNISCIP_CALL( SCIPallocBufferArray(scip, &vals, nvars) );
(*env)->GetLongArrayRegion(env, jvars, 0, nvars, (jlong*)(*vars));
(*env)->GetDoubleArrayRegion(env, jvals, 0, nvars, (jdouble*)vals);
JNISCIP_CALL( SCIPcreateConsBasicIndicator(scip, &cons, name, binvar, (int)nvars, vars, vals, (SCIP_Real)rhs) );
SCIPfreeBufferArray(scip, &vals);
SCIPfreeBufferArray(scip, &vars);
(*env)->ReleaseStringUTFChars(env, jname, name);
return (jlong)(size_t)cons;
}
/** creates the rows of the subproblem */
static
SCIP_RETCODE createRows(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP data structure for the subproblem */
SCIP_VAR** subvars /**< the variables of the subproblem */
)
{
SCIP_ROW** rows; /* original scip rows */
SCIP_CONS* cons; /* new constraint */
SCIP_VAR** consvars; /* new constraint's variables */
SCIP_COL** cols; /* original row's columns */
SCIP_Real constant; /* constant added to the row */
SCIP_Real lhs; /* left hand side of the row */
SCIP_Real rhs; /* left right side of the row */
SCIP_Real* vals; /* variables' coefficient values of the row */
int nrows;
int nnonz;
int i;
int j;
/* get the rows and their number */
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
/* copy all rows to linear constraints */
for( i = 0; i < nrows; i++ )
{
/* ignore rows that are only locally valid */
if( SCIProwIsLocal(rows[i]) )
continue;
/* get the row's data */
constant = SCIProwGetConstant(rows[i]);
lhs = SCIProwGetLhs(rows[i]) - constant;
rhs = SCIProwGetRhs(rows[i]) - constant;
vals = SCIProwGetVals(rows[i]);
nnonz = SCIProwGetNNonz(rows[i]);
cols = SCIProwGetCols(rows[i]);
assert(lhs <= rhs);
/* allocate memory array to be filled with the corresponding subproblem variables */
SCIP_CALL( SCIPallocBufferArray(scip, &consvars, nnonz) );
for( j = 0; j < nnonz; j++ )
consvars[j] = subvars[SCIPvarGetProbindex(SCIPcolGetVar(cols[j]))];
/* create a new linear constraint and add it to the subproblem */
SCIP_CALL( SCIPcreateConsLinear(subscip, &cons, SCIProwGetName(rows[i]), nnonz, consvars, vals, lhs, rhs,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
/* free temporary memory */
SCIPfreeBufferArray(scip, &consvars);
}
return SCIP_OKAY;
}
/** parese job informations */
static
SCIP_RETCODE getJobs(
SCIP* scip, /**< SCIP data structure */
int lineno, /**< current line number of input file */
char* linestr, /**< current line */
STATE* state, /**< pointer to current reading state */
SCIP_RCPSPDATA* rcpspdata /**< pointer to resources constrained project scheduling data */
)
{
char jobname[SCIP_MAXSTRLEN];
int value;
int jobid;
int r;
assert(linestr != NULL);
assert(state != NULL);
/* skip lines which are not of interest */
if ( (!strncmp(linestr, "REQUESTS", 4) ) || ( !strncmp(linestr, "jobnr", 3) ) || ( !strncmp(linestr, "-", 1) ) )
{
*state = JOBS;
return SCIP_OKAY;
}
/* parse job id */
SCIPstrToIntValue(linestr, &value, &linestr);
jobid = value - 1;
/* construct job name */
(void)SCIPsnprintf(jobname, SCIP_MAXSTRLEN, "%d" , jobid) ;
/* copy job name */
SCIP_CALL( SCIPduplicateBufferArray(scip, &rcpspdata->jobnames[jobid], jobname, strlen(jobname) + 1) );
/* skip next value */
SCIPstrToIntValue(linestr, &value, &linestr);
/* parse duration */
SCIPstrToIntValue(linestr, &value, &linestr);
rcpspdata->durations[jobid] = value;
SCIP_CALL( SCIPallocBufferArray(scip, &rcpspdata->demands[jobid], rcpspdata->nresources) );
/* parse demands */
for( r = 0; r < rcpspdata->nresources; ++r )
{
SCIPstrToIntValue(linestr, &value, &linestr);
rcpspdata->demands[jobid][r] = value;
}
/* check if we paresed the last job */
if(jobid == rcpspdata->njobs - 1)
*state = NEXT;
return SCIP_OKAY;
}
/** initialize graph */
static
SCIP_RETCODE initGraph(
SCIP* scip, /**< SCIP data structure */
SparseGraph* G, /**< graph to free */
unsigned int nNodes, /**< number of nodes */
unsigned int initSize /**< initial size of lists */
)
{
unsigned int i;
G->n = nNodes;
G->m = 0;
SCIP_CALL( SCIPallocBufferArray(scip, &G->deg, (int) nNodes) );
SCIP_CALL( SCIPallocBufferArray(scip, &G->size, (int) nNodes) );
SCIP_CALL( SCIPallocBufferArray(scip, &G->A, (int) nNodes) );
SCIP_CALL( SCIPallocBufferArray(scip, &G->W, (int) nNodes) );
for( i = 0; i < nNodes; ++i )
{
G->deg[i] = 0;
G->size[i] = initSize;
SCIP_CALL( SCIPallocBufferArray(scip, &(G->A[i]), (int) initSize) ); /*lint !e866 */
SCIP_CALL( SCIPallocBufferArray(scip, &(G->W[i]), (int) initSize) ); /*lint !e866 */
G->A[i][0] = -1;
}
return SCIP_OKAY;
}
/** parese number of resources */
static
SCIP_RETCODE getNResources(
SCIP* scip, /**< SCIP data structure */
int lineno, /**< current line number of input file */
char* linestr, /**< current line */
STATE* state, /**< pointer to current reading state */
SCIP_RCPSPDATA* rcpspdata /**< pointer to resources constrained project scheduling data */
)
{
SCIP_Real nresources;
char* endptr;
char* number;
assert(linestr != NULL);
assert(state != NULL);
if( strncmp(linestr, "RESOURCES", 4) == 0 )
return SCIP_OKAY;
/* truncate the line via ':' and ignore the first part */
(void)SCIPstrtok(linestr, ":", &endptr);
number = SCIPstrtok(NULL, ":", &endptr);
if( !SCIPstrToRealValue(number, &nresources, &endptr) )
{
parseError(scip, lineno, "expexted number of resources", linestr, state);
return SCIP_OKAY;
}
rcpspdata->nresources = (int)(nresources + 0.5);
SCIP_CALL( SCIPallocBufferArray(scip, &rcpspdata->capacities, nresources) );
SCIP_CALL( SCIPallocBufferArray(scip, &rcpspdata->resourcenames, nresources) );
*state = NEXT;
return SCIP_OKAY;
}
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpImpliedbounds)
{ /*lint --e{715}*/
SCIP_VAR** vars;
SCIP_VAR** fracvars;
SCIP_Real* solvals;
SCIP_Real* fracvals;
SCIP_Bool cutoff;
int nvars;
int nbinvars;
int nfracs;
int ncuts;
assert(sepa != NULL);
assert(scip != NULL);
*result = SCIP_DIDNOTRUN;
/* gets active problem variables */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, NULL, NULL, NULL) );
if( nbinvars == 0 )
return SCIP_OKAY;
/* get fractional problem variables */
/* todo try out also separating fractional implicit integer variables */
SCIP_CALL( SCIPgetLPBranchCands(scip, &fracvars, &fracvals, NULL, &nfracs, NULL, NULL) );
if( nfracs == 0 )
return SCIP_OKAY;
/* get solution values for all variables */
SCIP_CALL( SCIPallocBufferArray(scip, &solvals, nvars) );
SCIP_CALL( SCIPgetVarSols(scip, nvars, vars, solvals) );
/* call the cut separation */
SCIP_CALL( separateCuts(scip, sepa, NULL, solvals, fracvars, fracvals, nfracs, &cutoff, &ncuts) );
/* adjust result code */
if ( cutoff )
*result = SCIP_CUTOFF;
else if ( ncuts > 0 )
*result = SCIP_SEPARATED;
else
*result = SCIP_DIDNOTFIND;
/* free temporary memory */
SCIPfreeBufferArray(scip, &solvals);
return SCIP_OKAY;
}
/** constraint copying method of constraint handler */
static
SCIP_DECL_CONSCOPY(consCopyConjuction)
{ /*lint --e{715}*/
SCIP_CONSDATA* sourcedata;
SCIP_CONS** sourceconss;
SCIP_CONS** conss;
int nconss;
int c;
sourcedata = SCIPconsGetData(sourcecons);
assert(sourcedata != NULL);
nconss = sourcedata->nconss;
if( nconss == 0 && !SCIPconsIsModifiable(sourcecons) )
{
*valid = TRUE;
return SCIP_OKAY;
}
SCIP_CALL( SCIPallocBufferArray(scip, &conss, nconss) );
sourceconss = sourcedata->conss;
/* copy each constraint one by one */
for( c = 0; c < nconss && (*valid); ++c )
{
SCIP_CALL( SCIPgetConsCopy(sourcescip, scip, sourceconss[c], &conss[c], sourceconshdlr,
varmap, consmap, SCIPconsGetName(sourceconss[c]),
SCIPconsIsInitial(sourceconss[c]), SCIPconsIsSeparated(sourceconss[c]), SCIPconsIsEnforced(sourceconss[c]),
SCIPconsIsChecked(sourceconss[c]), SCIPconsIsPropagated(sourceconss[c]),
SCIPconsIsLocal(sourceconss[c]), SCIPconsIsModifiable(sourceconss[c]),
SCIPconsIsDynamic(sourceconss[c]), SCIPconsIsRemovable(sourceconss[c]), SCIPconsIsStickingAtNode(sourceconss[c]),
global, valid) );
assert(!(*valid) || conss[c] != NULL);
}
if( *valid )
{
SCIP_CALL( SCIPcreateConsDisjunction(scip, cons, name, nconss, conss,
initial, enforce, check, local, modifiable, dynamic) );
}
SCIPfreeBufferArray(scip, &conss);
return SCIP_OKAY;
}
/** creates a new solution for the original problem by copying the solution of the subproblem */
static
SCIP_RETCODE createNewSol(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP structure of the subproblem */
SCIP_VAR** subvars, /**< the variables of the subproblem */
SCIP_HEUR* heur, /**< crossover heuristic structure */
SCIP_SOL* subsol, /**< solution of the subproblem */
int* solindex, /**< index of the solution */
SCIP_Bool* success /**< used to store whether new solution was found or not */
)
{
SCIP_VAR** vars; /* the original problem's variables */
int nvars;
SCIP_SOL* newsol; /* solution to be created for the original problem */
SCIP_Real* subsolvals; /* solution values of the subproblem */
assert(scip != NULL);
assert(subscip != NULL);
assert(subvars != NULL);
assert(subsol != NULL);
/* get variables' data */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* sub-SCIP may have more variables than the number of active (transformed) variables in the main SCIP
* since constraint copying may have required the copy of variables that are fixed in the main SCIP
*/
assert(nvars <= SCIPgetNOrigVars(subscip));
SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );
/* copy the solution */
SCIP_CALL( SCIPgetSolVals(subscip, subsol, nvars, subvars, subsolvals) );
/* create new solution for the original problem */
SCIP_CALL( SCIPcreateSol(scip, &newsol, heur) );
SCIP_CALL( SCIPsetSolVals(scip, newsol, nvars, vars, subsolvals) );
*solindex = SCIPsolGetIndex(newsol);
/* try to add new solution to scip and free it immediately */
SCIP_CALL( SCIPtrySolFree(scip, &newsol, FALSE, TRUE, TRUE, TRUE, success) );
SCIPfreeBufferArray(scip, &subsolvals);
return SCIP_OKAY;
}
/** handle given linear constraint information */
static
SCIP_RETCODE handleLinearCons(
SCIP* scip, /**< SCIP data structure */
SCIP_VAR** vars, /**< array of variables */
SCIP_Real* vals, /**< array of coefficients values (or NULL if all coefficient values are 1) */
int nvars, /**< number of variables */
SCIP_Bool transformed, /**< transformed constraint? */
SparseGraph* G /**< graph */
)
{
int v;
SCIP_VAR** activevars;
SCIP_Real* activevals;
int nactivevars;
SCIP_Real activeconstant = 0.0;
assert( scip != NULL );
assert( nvars > 0 );
/* duplicate variable and value array */
nactivevars = nvars;
SCIP_CALL( SCIPduplicateBufferArray(scip, &activevars, vars, nactivevars ) );
if( vals != NULL )
SCIP_CALL( SCIPduplicateBufferArray(scip, &activevals, vals, nactivevars ) );
else
{
SCIP_CALL( SCIPallocBufferArray(scip, &activevals, nactivevars) );
for( v = 0; v < nactivevars; ++v )
activevals[v] = 1.0;
}
/* retransform given variables to active variables */
SCIP_CALL( getActiveVariables(scip, activevars, activevals, &nactivevars, &activeconstant, transformed) );
/* print constraint */
SCIP_CALL( createEdgesFromRow(scip, activevars, activevals, nactivevars, G) );
/* free buffer arrays */
SCIPfreeBufferArray(scip, &activevars);
SCIPfreeBufferArray(scip, &activevals);
return SCIP_OKAY;
}
/** creates a new solution for the original problem by copying the solution of the subproblem */
static
SCIP_RETCODE createNewSol(
SCIP* scip, /**< SCIP data structure of the original problem */
SCIP* subscip, /**< SCIP data structure of the subproblem */
SCIP_VAR** subvars, /**< the variables of the subproblem */
SCIP_HEUR* heur, /**< the Localbranching heuristic */
SCIP_SOL* subsol, /**< solution of the subproblem */
SCIP_Bool* success /**< pointer to store, whether new solution was found */
)
{
SCIP_VAR** vars;
int nvars;
SCIP_SOL* newsol;
SCIP_Real* subsolvals;
assert( scip != NULL );
assert( subscip != NULL );
assert( subvars != NULL );
assert( subsol != NULL );
/* copy the solution */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* sub-SCIP may have more variables than the number of active (transformed) variables in the main SCIP
* since constraint copying may have required the copy of variables that are fixed in the main SCIP
*/
assert(nvars <= SCIPgetNOrigVars(subscip));
SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );
/* copy the solution */
SCIP_CALL( SCIPgetSolVals(subscip, subsol, nvars, subvars, subsolvals) );
/* create new solution for the original problem */
SCIP_CALL( SCIPcreateSol(scip, &newsol, heur) );
SCIP_CALL( SCIPsetSolVals(scip, newsol, nvars, vars, subsolvals) );
SCIP_CALL( SCIPtrySolFree(scip, &newsol, FALSE, TRUE, TRUE, TRUE, success) );
SCIPfreeBufferArray(scip, &subsolvals);
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecMutation)
{ /*lint --e{715}*/
SCIP_Longint maxnnodes;
SCIP_Longint nsubnodes; /* node limit for the subproblem */
SCIP_HEURDATA* heurdata; /* heuristic's data */
SCIP* subscip; /* the subproblem created by mutation */
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_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real maxnnodesr;
SCIP_Real memorylimit;
SCIP_Real timelimit; /* timelimit for the subproblem */
SCIP_Real upperbound;
int nvars; /* number of original problem's variables */
int i;
SCIP_Bool success;
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;
/* only call heuristic, if feasible solution is available */
if( SCIPgetNSols(scip) <= 0 )
return SCIP_OKAY;
/* only call heuristic, if the best solution comes from transformed problem */
assert( SCIPgetBestSol(scip) != NULL );
if( SCIPsolIsOriginal(SCIPgetBestSol(scip)) )
return SCIP_OKAY;
/* only call heuristic, if enough nodes were processed since last incumbent */
if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip,SCIPgetBestSol(scip)) < heurdata->nwaitingnodes)
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* only call heuristic, if discrete variables are present */
if( SCIPgetNBinVars(scip) == 0 && SCIPgetNIntVars(scip) == 0 )
return SCIP_OKAY;
/* calculate the maximal number of branching nodes until heuristic is aborted */
maxnnodesr = heurdata->nodesquot * SCIPgetNNodes(scip);
/* reward mutation if it succeeded often, count the setup costs for the sub-MIP as 100 nodes */
maxnnodesr *= 1.0 + 2.0 * (SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur) + 1.0);
maxnnodes = (SCIP_Longint) maxnnodesr - 100 * SCIPheurGetNCalls(heur);
maxnnodes += heurdata->nodesofs;
/* determine the node limit for the current process */
nsubnodes = maxnnodes - heurdata->usednodes;
nsubnodes = MIN(nsubnodes, heurdata->maxnodes);
/* check whether we have enough nodes left to call subproblem solving */
if( nsubnodes < heurdata->minnodes )
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) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
if( heurdata->uselprows )
{
char probname[SCIP_MAXSTRLEN];
/* copy all plugins */
SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );
/* get name of the original problem and add the string "_mutationsub" */
(void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_mutationsub", SCIPgetProbName(scip));
/* create the subproblem */
SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );
/* copy all variables */
SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
}
else
{
SCIP_Bool valid;
valid = FALSE;
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "rens", TRUE, FALSE, TRUE, &valid) );
if( heurdata->copycuts )
{
/* copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
}
SCIPdebugMessage("Copying the SCIP instance was %s complete.\n", valid ? "" : "not ");
}
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
/* free hash map */
SCIPhashmapFree(&varmapfw);
/* create a new problem, which fixes variables with same value in bestsol and LP relaxation */
SCIP_CALL( createSubproblem(scip, subscip, subvars, heurdata->minfixingrate, &heurdata->randseed, heurdata->uselprows) );
/* 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) );
/* 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) );
/* 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 )
goto TERMINATE;
/* set limits for the subproblem */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nsubnodes) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
/* 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) );
/* use best estimate node selection */
if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
}
/* use inference branching */
if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
}
/* disable conflict analysis */
if( !SCIPisParamFixed(subscip, "conflict/useprop") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/useinflp") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/usesb") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/usepseudo") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
}
/* employ a limit on the number of enforcement rounds in the quadratic constraint handlers; 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 decutions 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) );
}
/* add an objective cutoff */
cutoff = SCIPinfinity(scip);
assert( !SCIPisInfinity(scip, SCIPgetUpperbound(scip)) );
upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
if( !SCIPisInfinity(scip, -1.0 * SCIPgetLowerbound(scip)) )
{
cutoff = (1-heurdata->minimprove) * SCIPgetUpperbound(scip) + heurdata->minimprove * SCIPgetLowerbound(scip);
}
else
{
if( SCIPgetUpperbound ( scip ) >= 0 )
cutoff = ( 1 - heurdata->minimprove ) * SCIPgetUpperbound ( scip );
else
cutoff = ( 1 + heurdata->minimprove ) * SCIPgetUpperbound ( scip );
}
cutoff = MIN(upperbound, cutoff );
SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );
/* solve the subproblem */
SCIPdebugMessage("Solve Mutation subMIP\n");
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 Mutation heuristic; sub-SCIP terminated with code <%d>\n",retcode);
}
heurdata->usednodes += SCIPgetNNodes(subscip);
/* check, whether a solution was found */
if( SCIPgetNSols(subscip) > 0 )
{
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 one was accepted
*/
nsubsols = SCIPgetNSols(subscip);
subsols = SCIPgetSols(subscip);
success = FALSE;
for( i = 0; i < nsubsols && !success; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
}
if( success )
*result = SCIP_FOUNDSOL;
}
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/** separate 2-cuts */
static
SCIP_RETCODE sep_2cut(
SCIP* scip, /**< SCIP data structure */
SCIP_CONSHDLR* conshdlr, /**< constraint handler */
SCIP_CONSHDLRDATA* conshdlrdata, /**< constraint handler data */
SCIP_CONSDATA* consdata, /**< constraint data */
int maxcuts, /**< maximal number of cuts */
int* ncuts /**< pointer to store number of cuts */
)
{
const SCIP_Bool nested_cut = conshdlrdata->nestedcut;
const SCIP_Bool back_cut = conshdlrdata->backcut;
const SCIP_Bool creep_flow = conshdlrdata->creepflow;
const SCIP_Bool disjunct_cut = conshdlrdata->disjunctcut;
const SCIP_Bool flowsep = conshdlrdata->flowsep;
GRAPH* g;
SCIP_Real* xval;
SCIP_Real* cost;
PATH* path;
int* w;
int* capa;
int* term;
int terms = 0;
int tsave;
int i;
int k;
int layer;
int count = 0;
int rerun = FALSE;
int nedges;
int nnodes;
SCIP_Bool addedcut;
assert(scip != NULL);
assert(conshdlr != NULL);
assert(conshdlrdata != NULL);
g = consdata->graph;
assert(g != NULL);
nedges = g->edges;
nnodes = g->knots;
addedcut = FALSE;
xval = SCIPprobdataGetXval(scip, NULL);
assert(xval != NULL);
SCIP_CALL( SCIPallocBufferArray(scip, &capa, nedges) );
SCIP_CALL( SCIPallocBufferArray(scip, &cost, nedges) );
SCIP_CALL( SCIPallocBufferArray(scip, &w, nnodes) );
SCIP_CALL( SCIPallocBufferArray(scip, &term, g->terms) );
SCIP_CALL( SCIPallocBufferArray(scip, &path, nnodes) );
for( layer = 0; layer < g->layers; layer++ )
{
/* For 2-terminal nets no cuts are necessary if flows are given */
if( flowsep && (g->locals[layer] == 2) )
continue;
for( i = 0; i < nedges; i++ )
cost[i] = SCIPisFeasLT(scip, xval[layer * nedges + i], 1.0) ? 1.0 : 0.0;
for( i = 0; i < nnodes; i++ )
{
w[i] = 0;
g->mark[i] = TRUE;
}
graph_path_exec(scip, g, FSP_MODE, g->source[layer], cost, path);
/* search all terminals not connected to the root by the LP solution */
for( i = 0, count = 0; i < nnodes; i++ )
{
if( (g->term[i] == layer) && (i != g->source[layer]) )
{
if( SCIPisPositive(scip, path[i].dist) )
term[terms++] = i;
else
count++;
}
}
SCIPdebugMessage("Cut Pretest: %d eliminations\n", count);
count = 0;
tsave = terms;
/* from source to terminal */
if( !nested_cut || disjunct_cut )
set_capacity(g, layer, creep_flow, 0, capa, xval);
while( terms > 0 )
{
if( SCIPisStopped(scip) && terms % 100 == 0 )
break;
/* look for reachable terminal */
i = graph_next_term(terms, term, w);
terms--;
assert(g->term[i] == layer);
assert(g->source[layer] != i);
if( nested_cut && !disjunct_cut )
set_capacity(g, layer, creep_flow, 0, capa, xval);
do
{
graph_mincut_exec(g, g->source[layer], i, capa, w, rerun);
rerun = TRUE;
/* cut */
for( k = 0; k < nnodes; k++ )
g->mark[k] = (w[k] != 0);
SCIP_CALL( cut_add(scip, conshdlr, g, layer, xval, capa, nested_cut || disjunct_cut, ncuts, &addedcut) );
if( addedcut )
{
count++;
if( *ncuts >= maxcuts )
goto TERMINATE;
}
else
break;
}
while( nested_cut ); /* Nested Cut is CONSTANT ! */
}
/* back cuts enabled? */
if( back_cut )
{
if( !nested_cut || disjunct_cut )
set_capacity(g, layer, creep_flow, 1, capa, xval);
terms = tsave;
while( terms > 0 )
{
/* look for reachable terminal */
i = graph_next_term(terms, term, w);
terms--;
assert(g->term[i] == layer);
assert(g->source[layer] != i);
if( nested_cut && !disjunct_cut )
set_capacity(g, layer, creep_flow, 1, capa, xval);
rerun = FALSE;
do
{
graph_mincut_exec(g, i, g->source[layer], capa, w, rerun);
rerun = TRUE;
for( k = 0; k < nnodes; k++ )
g->mark[k] = (w[k] != 0) ? 1 : 0;
SCIP_CALL( cut_add(scip, conshdlr, g, layer, xval, capa, nested_cut || disjunct_cut, ncuts, &addedcut) );
if( addedcut )
{
count++;
if( *ncuts >= maxcuts )
goto TERMINATE;
}
else
break;
#if 0
if (nested_cut || disjunct_cut)
for(k = p->beg[p->rcnt - 1]; k < p->nzcnt; k++)
capa[p->ind[k] % nedges
+ (((p->ind[k] % nedges) % 2)
? -1 : 1)] = FLOW_FACTOR;
#endif
}
while( nested_cut ); /* Nested Cut is CONSTANT ! */
rerun = FALSE;
}
}
}
TERMINATE:
SCIPfreeBufferArray(scip, &path);
SCIPfreeBufferArray(scip, &term);
SCIPfreeBufferArray(scip, &w);
SCIPfreeBufferArray(scip, &cost);
SCIPfreeBufferArray(scip, &capa);
SCIPdebugMessage("2-cut Separator: %d Inequalities added\n", count);
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecIntdiving) /*lint --e{715}*/
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_LPSOLSTAT lpsolstat;
SCIP_VAR** pseudocands;
SCIP_VAR** fixcands;
SCIP_Real* fixcandscores;
SCIP_Real searchubbound;
SCIP_Real searchavgbound;
SCIP_Real searchbound;
SCIP_Real objval;
SCIP_Bool lperror;
SCIP_Bool cutoff;
SCIP_Bool backtracked;
SCIP_Longint ncalls;
SCIP_Longint nsolsfound;
SCIP_Longint nlpiterations;
SCIP_Longint maxnlpiterations;
int nfixcands;
int nbinfixcands;
int depth;
int maxdepth;
int maxdivedepth;
int divedepth;
int nextcand;
int c;
assert(heur != NULL);
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
assert(SCIPhasCurrentNodeLP(scip));
*result = SCIP_DELAYED;
/* 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;
/* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */
if( !SCIPisLPSolBasic(scip) )
return SCIP_OKAY;
/* don't dive two times at the same node */
if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */
depth = SCIPgetDepth(scip);
maxdepth = SCIPgetMaxDepth(scip);
maxdepth = MAX(maxdepth, 100);
if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth )
return SCIP_OKAY;
/* calculate the maximal number of LP iterations until heuristic is aborted */
nlpiterations = SCIPgetNNodeLPIterations(scip);
ncalls = SCIPheurGetNCalls(heur);
nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess;
maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations);
maxnlpiterations += heurdata->maxlpiterofs;
/* don't try to dive, if we took too many LP iterations during diving */
if( heurdata->nlpiterations >= maxnlpiterations )
return SCIP_OKAY;
/* allow at least a certain number of LP iterations in this dive */
maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER);
/* get unfixed integer variables */
SCIP_CALL( SCIPgetPseudoBranchCands(scip, &pseudocands, &nfixcands, NULL) );
/* don't try to dive, if there are no fractional variables */
if( nfixcands == 0 )
return SCIP_OKAY;
/* calculate the objective search bound */
if( SCIPgetNSolsFound(scip) == 0 )
{
if( heurdata->maxdiveubquotnosol > 0.0 )
searchubbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveubquotnosol * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip));
else
searchubbound = SCIPinfinity(scip);
if( heurdata->maxdiveavgquotnosol > 0.0 )
searchavgbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveavgquotnosol * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip));
else
searchavgbound = SCIPinfinity(scip);
}
else
{
if( heurdata->maxdiveubquot > 0.0 )
searchubbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveubquot * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip));
else
searchubbound = SCIPinfinity(scip);
if( heurdata->maxdiveavgquot > 0.0 )
searchavgbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveavgquot * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip));
else
searchavgbound = SCIPinfinity(scip);
}
searchbound = MIN(searchubbound, searchavgbound);
if( SCIPisObjIntegral(scip) )
searchbound = SCIPceil(scip, searchbound);
/* calculate the maximal diving depth: 10 * min{number of integer variables, max depth} */
maxdivedepth = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip);
maxdivedepth = MIN(maxdivedepth, maxdepth);
maxdivedepth *= 10;
*result = SCIP_DIDNOTFIND;
/* start diving */
SCIP_CALL( SCIPstartProbing(scip) );
/* enables collection of variable statistics during probing */
SCIPenableVarHistory(scip);
SCIPdebugMessage("(node %" SCIP_LONGINT_FORMAT ") executing intdiving heuristic: depth=%d, %d non-fixed, dualbound=%g, searchbound=%g\n",
SCIPgetNNodes(scip), SCIPgetDepth(scip), nfixcands, SCIPgetDualbound(scip), SCIPretransformObj(scip, searchbound));
/* copy the pseudo candidates into own array, because we want to reorder them */
SCIP_CALL( SCIPduplicateBufferArray(scip, &fixcands, pseudocands, nfixcands) );
/* sort non-fixed variables by non-increasing inference score, but prefer binaries over integers in any case */
SCIP_CALL( SCIPallocBufferArray(scip, &fixcandscores, nfixcands) );
nbinfixcands = 0;
for( c = 0; c < nfixcands; ++c )
{
SCIP_VAR* var;
SCIP_Real score;
int colveclen;
int left;
int right;
int i;
assert(c >= nbinfixcands);
var = fixcands[c];
assert(SCIPvarIsIntegral(var));
colveclen = (SCIPvarGetStatus(var) == SCIP_VARSTATUS_COLUMN ? SCIPcolGetNNonz(SCIPvarGetCol(var)) : 0);
if( SCIPvarIsBinary(var) )
{
score = 500.0 * SCIPvarGetNCliques(var, TRUE) + 100.0 * SCIPvarGetNImpls(var, TRUE)
+ SCIPgetVarAvgInferenceScore(scip, var) + (SCIP_Real)colveclen/100.0;
/* shift the non-binary variables one slot to the right */
for( i = c; i > nbinfixcands; --i )
{
fixcands[i] = fixcands[i-1];
fixcandscores[i] = fixcandscores[i-1];
}
/* put the new candidate into the first nbinfixcands slot */
left = 0;
right = nbinfixcands;
nbinfixcands++;
}
else
{
score = 5.0 * (SCIPvarGetNCliques(var, FALSE) + SCIPvarGetNCliques(var, TRUE))
+ SCIPvarGetNImpls(var, FALSE) + SCIPvarGetNImpls(var, TRUE) + SCIPgetVarAvgInferenceScore(scip, var)
+ (SCIP_Real)colveclen/10000.0;
/* put the new candidate in the slots after the binary candidates */
left = nbinfixcands;
right = c;
}
for( i = right; i > left && score > fixcandscores[i-1]; --i )
{
fixcands[i] = fixcands[i-1];
fixcandscores[i] = fixcandscores[i-1];
}
fixcands[i] = var;
fixcandscores[i] = score;
SCIPdebugMessage(" <%s>: ncliques=%d/%d, nimpls=%d/%d, inferencescore=%g, colveclen=%d -> score=%g\n",
SCIPvarGetName(var), SCIPvarGetNCliques(var, FALSE), SCIPvarGetNCliques(var, TRUE),
SCIPvarGetNImpls(var, FALSE), SCIPvarGetNImpls(var, TRUE), SCIPgetVarAvgInferenceScore(scip, var),
colveclen, score);
}
SCIPfreeBufferArray(scip, &fixcandscores);
/* get LP objective value */
lpsolstat = SCIP_LPSOLSTAT_OPTIMAL;
objval = SCIPgetLPObjval(scip);
/* dive as long we are in the given objective, depth and iteration limits, but if possible, we dive at least with
* the depth 10
*/
lperror = FALSE;
cutoff = FALSE;
divedepth = 0;
nextcand = 0;
while( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL
&& (divedepth < 10
|| (divedepth < maxdivedepth && heurdata->nlpiterations < maxnlpiterations && objval < searchbound))
&& !SCIPisStopped(scip) )
{
SCIP_VAR* var;
SCIP_Real bestsolval;
SCIP_Real bestfixval;
int bestcand;
SCIP_Longint nnewlpiterations;
SCIP_Longint nnewdomreds;
/* open a new probing node if this will not exceed the maximal tree depth, otherwise stop here */
if( SCIPgetDepth(scip) < SCIPgetDepthLimit(scip) )
{
SCIP_CALL( SCIPnewProbingNode(scip) );
divedepth++;
}
else
break;
nnewlpiterations = 0;
nnewdomreds = 0;
/* fix binary variable that is closest to 1 in the LP solution to 1;
* if all binary variables are fixed, fix integer variable with least fractionality in LP solution
*/
bestcand = -1;
bestsolval = -1.0;
bestfixval = 1.0;
/* look in the binary variables for fixing candidates */
for( c = nextcand; c < nbinfixcands; ++c )
{
SCIP_Real solval;
var = fixcands[c];
/* ignore already fixed variables */
if( var == NULL )
continue;
if( SCIPvarGetLbLocal(var) > 0.5 || SCIPvarGetUbLocal(var) < 0.5 )
{
fixcands[c] = NULL;
continue;
}
/* get the LP solution value */
solval = SCIPvarGetLPSol(var);
if( solval > bestsolval )
{
bestcand = c;
bestfixval = 1.0;
bestsolval = solval;
if( SCIPisGE(scip, bestsolval, 1.0) )
{
/* we found an unfixed binary variable with LP solution value of 1.0 - there cannot be a better candidate */
break;
}
else if( SCIPisLE(scip, bestsolval, 0.0) )
{
/* the variable is currently at 0.0 - this is the only situation where we want to fix it to 0.0 */
bestfixval = 0.0;
}
}
}
/* if all binary variables are fixed, look in the integer variables for a fixing candidate */
if( bestcand == -1 )
{
SCIP_Real bestfrac;
bestfrac = SCIP_INVALID;
for( c = MAX(nextcand, nbinfixcands); c < nfixcands; ++c )
{
SCIP_Real solval;
SCIP_Real frac;
var = fixcands[c];
/* ignore already fixed variables */
if( var == NULL )
continue;
if( SCIPvarGetUbLocal(var) - SCIPvarGetLbLocal(var) < 0.5 )
{
fixcands[c] = NULL;
continue;
}
/* get the LP solution value */
solval = SCIPvarGetLPSol(var);
frac = SCIPfrac(scip, solval);
/* ignore integer variables that are currently integral */
if( SCIPisFeasFracIntegral(scip, frac) )
continue;
if( frac < bestfrac )
{
bestcand = c;
bestsolval = solval;
bestfrac = frac;
bestfixval = SCIPfloor(scip, bestsolval + 0.5);
if( SCIPisZero(scip, bestfrac) )
{
/* we found an unfixed integer variable with integral LP solution value */
break;
}
}
}
}
assert(-1 <= bestcand && bestcand < nfixcands);
/* if there is no unfixed candidate left, we are done */
if( bestcand == -1 )
break;
var = fixcands[bestcand];
assert(var != NULL);
assert(SCIPvarIsIntegral(var));
assert(SCIPvarGetUbLocal(var) - SCIPvarGetLbLocal(var) > 0.5);
assert(SCIPisGE(scip, bestfixval, SCIPvarGetLbLocal(var)));
assert(SCIPisLE(scip, bestfixval, SCIPvarGetUbLocal(var)));
backtracked = FALSE;
do
{
/* if the variable is already fixed or if the solution value is outside the domain, numerical troubles may have
* occured or variable was fixed by propagation while backtracking => Abort diving!
*/
if( SCIPvarGetLbLocal(var) >= SCIPvarGetUbLocal(var) - 0.5 )
{
SCIPdebugMessage("Selected variable <%s> already fixed to [%g,%g], diving aborted \n",
SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var));
cutoff = TRUE;
break;
}
if( SCIPisFeasLT(scip, bestfixval, SCIPvarGetLbLocal(var)) || SCIPisFeasGT(scip, bestfixval, SCIPvarGetUbLocal(var)) )
{
SCIPdebugMessage("selected variable's <%s> solution value is outside the domain [%g,%g] (solval: %.9f), diving aborted\n",
SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), bestfixval);
assert(backtracked);
break;
}
/* apply fixing of best candidate */
SCIPdebugMessage(" dive %d/%d, LP iter %" SCIP_LONGINT_FORMAT "/%" SCIP_LONGINT_FORMAT ", %d unfixed: var <%s>, sol=%g, oldbounds=[%g,%g], fixed to %g\n",
divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations, SCIPgetNPseudoBranchCands(scip),
SCIPvarGetName(var), bestsolval, SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), bestfixval);
SCIP_CALL( SCIPfixVarProbing(scip, var, bestfixval) );
/* apply domain propagation */
SCIP_CALL( SCIPpropagateProbing(scip, 0, &cutoff, &nnewdomreds) );
if( !cutoff )
{
/* if the best candidate was just fixed to its LP value and no domain reduction was found, the LP solution
* stays valid, and the LP does not need to be resolved
*/
if( nnewdomreds > 0 || !SCIPisEQ(scip, bestsolval, bestfixval) )
{
/* resolve the diving 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
SCIP_RETCODE retstat;
nlpiterations = SCIPgetNLPIterations(scip);
retstat = SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff);
if( retstat != SCIP_OKAY )
{
SCIPwarningMessage(scip, "Error while solving LP in Intdiving heuristic; LP solve terminated with code <%d>\n",retstat);
}
#else
nlpiterations = SCIPgetNLPIterations(scip);
SCIP_CALL( SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff) );
#endif
if( lperror )
break;
/* update iteration count */
nnewlpiterations = SCIPgetNLPIterations(scip) - nlpiterations;
heurdata->nlpiterations += nnewlpiterations;
/* get LP solution status */
lpsolstat = SCIPgetLPSolstat(scip);
assert(cutoff || (lpsolstat != SCIP_LPSOLSTAT_OBJLIMIT && lpsolstat != SCIP_LPSOLSTAT_INFEASIBLE &&
(lpsolstat != SCIP_LPSOLSTAT_OPTIMAL || SCIPisLT(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)))));
}
}
/* perform backtracking if a cutoff was detected */
if( cutoff && !backtracked && heurdata->backtrack )
{
SCIPdebugMessage(" *** cutoff detected at level %d - backtracking\n", SCIPgetProbingDepth(scip));
SCIP_CALL( SCIPbacktrackProbing(scip, SCIPgetProbingDepth(scip)-1) );
/* after backtracking there has to be at least one open node without exceeding the maximal tree depth */
assert(SCIPgetDepthLimit(scip) > SCIPgetDepth(scip));
SCIP_CALL( SCIPnewProbingNode(scip) );
bestfixval = SCIPvarIsBinary(var)
? 1.0 - bestfixval
: (SCIPisGT(scip, bestsolval, bestfixval) && SCIPisFeasLE(scip, bestfixval + 1, SCIPvarGetUbLocal(var)) ? bestfixval + 1 : bestfixval - 1);
backtracked = TRUE;
}
else
backtracked = FALSE;
}
while( backtracked );
if( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
{
SCIP_Bool success;
/* get new objective value */
objval = SCIPgetLPObjval(scip);
if( nnewlpiterations > 0 || !SCIPisEQ(scip, bestsolval, bestfixval) )
{
/* we must start again with the first candidate, since the LP solution changed */
nextcand = 0;
/* create solution from diving LP and try to round it */
SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) );
if( success )
{
SCIPdebugMessage("intdiving found roundable primal solution: obj=%g\n",
SCIPgetSolOrigObj(scip, heurdata->sol));
/* try to add solution to SCIP */
SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );
/* check, if solution was feasible and good enough */
if( success )
{
SCIPdebugMessage(" -> solution was feasible and good enough\n");
*result = SCIP_FOUNDSOL;
}
}
}
else
nextcand = bestcand+1; /* continue with the next candidate in the following loop */
}
SCIPdebugMessage(" -> lpsolstat=%d, objval=%g/%g\n", lpsolstat, objval, searchbound);
}
/* free temporary memory */
SCIPfreeBufferArray(scip, &fixcands);
/* end diving */
SCIP_CALL( SCIPendProbing(scip) );
if( *result == SCIP_FOUNDSOL )
heurdata->nsuccess++;
SCIPdebugMessage("intdiving heuristic finished\n");
return SCIP_OKAY;
}
/** problem reading method of reader */
static
SCIP_DECL_READERREAD(readerReadBpa)
{ /*lint --e{715}*/
SCIP_FILE* file;
SCIP_Longint* weights;
int* ids;
SCIP_Bool error;
char name[SCIP_MAXSTRLEN];
char format[16];
char buffer[SCIP_MAXSTRLEN];
int capacity;
int nitems;
int bestsolvalue;
int nread;
int weight;
int nweights;
int lineno;
*result = SCIP_DIDNOTRUN;
/* open file */
file = SCIPfopen(filename, "r");
if( file == NULL )
{
SCIPerrorMessage("cannot open file <%s> for reading\n", filename);
SCIPprintSysError(filename);
return SCIP_NOFILE;
}
lineno = 0;
/* read problem name */
if( !SCIPfeof(file) )
{
/* get next line */
if( SCIPfgets(buffer, sizeof(buffer), file) == NULL )
return SCIP_READERROR;
lineno++;
/* parse dimension line */
sprintf(format, "%%%ds\n", SCIP_MAXSTRLEN);
nread = sscanf(buffer, format, name);
if( nread == 0 )
{
SCIPwarningMessage(scip, "invalid input line %d in file <%s>: <%s>\n", lineno, filename, buffer);
return SCIP_READERROR;
}
SCIPdebugMessage("problem name <%s>\n", name);
}
/* read problem dimension */
if( !SCIPfeof(file) )
{
/* get next line */
if( SCIPfgets(buffer, sizeof(buffer), file) == NULL )
return SCIP_READERROR;
lineno++;
/* parse dimension line */
nread = sscanf(buffer, "%d %d %d\n", &capacity, &nitems, &bestsolvalue);
if( nread < 2 )
{
SCIPwarningMessage(scip, "invalid input line %d in file <%s>: <%s>\n", lineno, filename, buffer);
return SCIP_READERROR;
}
SCIPdebugMessage("capacity = <%d>, number of items = <%d>, best known solution = <%d>\n", capacity, nitems, bestsolvalue);
}
/* allocate buffer memory for storing the weights and ids temporary */
SCIP_CALL( SCIPallocBufferArray(scip, &weights, nitems) );
SCIP_CALL( SCIPallocBufferArray(scip, &ids, nitems) );
/* pasre weights */
nweights = 0;
error = FALSE;
while( !SCIPfeof(file) && !error )
{
/* get next line */
if( SCIPfgets(buffer, sizeof(buffer), file) == NULL )
break;
lineno++;
/* parse the line */
nread = sscanf(buffer, "%d\n", &weight);
if( nread == 0 )
{
SCIPwarningMessage(scip, "invalid input line %d in file <%s>: <%s>\n", lineno, filename, buffer);
error = TRUE;
break;
}
SCIPdebugMessage("found weight %d <%d>\n", nweights, weight);
weights[nweights] = weight;
ids[nweights] = nweights;
nweights++;
if( nweights == nitems )
break;
}
if( nweights < nitems )
{
SCIPwarningMessage(scip, "set nitems from <%d> to <%d> since the file <%s> only contains <%d> weights\n", nitems, weights, filename, weights);
nitems = nweights;
}
if( !error )
{
/* create a new problem in SCIP */
SCIP_CALL( SCIPprobdataCreate(scip, name, ids, weights, nitems, (SCIP_Longint)capacity) );
}
(void)SCIPfclose(file);
SCIPfreeBufferArray(scip, &ids);
SCIPfreeBufferArray(scip, &weights);
if( error )
return SCIP_READERROR;
*result = SCIP_SUCCESS;
return SCIP_OKAY;
}
/** sets up the problem data */
SCIP_RETCODE SCIPprobdataCreate(
SCIP* scip, /**< SCIP data structure */
const char* probname, /**< problem name */
int* ids, /**< array of item ids */
SCIP_Longint* weights, /**< array containing the item weights */
int nitems, /**< number of items */
SCIP_Longint capacity /**< bin capacity */
)
{
SCIP_PROBDATA* probdata;
SCIP_CONS** conss;
char name[SCIP_MAXSTRLEN];
int i;
assert(scip != NULL);
/* create event handler if it does not exist yet */
if( SCIPfindEventhdlr(scip, EVENTHDLR_NAME) == NULL )
{
SCIP_CALL( SCIPincludeEventhdlrBasic(scip, NULL, EVENTHDLR_NAME, EVENTHDLR_DESC, eventExecAddedVar, NULL) );
}
/* create problem in SCIP and add non-NULL callbacks via setter functions */
SCIP_CALL( SCIPcreateProbBasic(scip, probname) );
SCIP_CALL( SCIPsetProbDelorig(scip, probdelorigBinpacking) );
SCIP_CALL( SCIPsetProbTrans(scip, probtransBinpacking) );
SCIP_CALL( SCIPsetProbDeltrans(scip, probdeltransBinpacking) );
SCIP_CALL( SCIPsetProbInitsol(scip, probinitsolBinpacking) );
SCIP_CALL( SCIPsetProbExitsol(scip, probexitsolBinpacking) );
/* set objective sense */
SCIP_CALL( SCIPsetObjsense(scip, SCIP_OBJSENSE_MINIMIZE) );
/* tell SCIP that the objective will be always integral */
SCIP_CALL( SCIPsetObjIntegral(scip) );
SCIP_CALL( SCIPallocBufferArray(scip, &conss, nitems) );
/* create set covering constraints for each item */
for( i = 0; i < nitems; ++i )
{
(void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "item_%d", ids[i]);
SCIP_CALL( SCIPcreateConsBasicSetcover(scip, &conss[i], name, 0, NULL) );
/* declare constraint modifiable for adding variables during pricing */
SCIP_CALL( SCIPsetConsModifiable(scip, conss[i], TRUE) );
SCIP_CALL( SCIPaddCons(scip, conss[i]) );
}
/* create problem data */
SCIP_CALL( probdataCreate(scip, &probdata, NULL, conss, weights, ids, 0, nitems, capacity) );
SCIP_CALL( createInitialColumns(scip, probdata) );
/* set user problem data */
SCIP_CALL( SCIPsetProbData(scip, probdata) );
SCIP_CALL( SCIPpricerBinpackingActivate(scip, conss, weights, ids, nitems, capacity) );
/* free local buffer arrays */
SCIPfreeBufferArray(scip, &conss);
return SCIP_OKAY;
}
/** selects the branching variable from given candidate array */
static
SCIP_RETCODE selectBranchVar(
SCIP* scip, /**< SCIP data structure */
SCIP_BRANCHRULE* branchrule, /**< branching rule */
SCIP_VAR** cands, /**< array of branching candidates */
SCIP_Real* candssol, /**< array of candidate solution values */
SCIP_Real* candsscore, /**< array of candidate scores */
int ncands, /**< the number of candidates */
SCIP_VAR** brvar, /**< pointer to store the selected branching candidate or NULL if none */
SCIP_Real* brpoint /**< pointer to store branching point of selected branching variable */
)
{ /*lint --e{850}*/
SCIP_BRANCHRULEDATA* branchruledata;
SCIP_VAR* cand;
SCIP_Real candsol;
SCIP_Real bestbranchscore;
SCIP_Real scoremin;
SCIP_Real scoresum;
SCIP_Real scoremax;
SCIP_VAR** candssorted;
int* candsorigidx;
int i;
int j;
assert(brvar != NULL);
assert(brpoint != NULL);
(*brvar) = NULL;
(*brpoint) = SCIP_INVALID;
if( ncands == 0 )
return SCIP_OKAY;
branchruledata = SCIPbranchruleGetData(branchrule);
assert(branchruledata != NULL);
/* sort branching candidates (in a copy), such that same variables are on consecutive positions */
SCIP_CALL( SCIPduplicateBufferArray(scip, &candssorted, cands, ncands) );
SCIP_CALL( SCIPallocBufferArray(scip, &candsorigidx, ncands) );
for( i = 0; i < ncands; ++i )
candsorigidx[i] = i;
SCIPsortPtrInt((void**)candssorted, candsorigidx, SCIPvarComp, ncands);
bestbranchscore = -1.0;
for( i = 0; i < ncands; ++i )
{
cand = candssorted[i];
/* there should be no fixed branching candidates */
assert(!SCIPisEQ(scip, SCIPvarGetLbLocal(cand), SCIPvarGetUbLocal(cand)));
/* compute min, sum, and max of all registered scores for this variables
* set candsol to a valid value, if someone registered one */
scoremin = candsscore[candsorigidx[i]];
scoresum = scoremin;
scoremax = scoremin;
candsol = candssol[candsorigidx[i]];
for( j = i+1 ; j < ncands && SCIPvarCompare(candssorted[j], cand) == 0; ++j )
{
assert(candsscore[candsorigidx[j]] >= 0.0);
scoresum += candsscore[candsorigidx[j]];
if( candsscore[candsorigidx[j]] < scoremin )
scoremin = candsscore[candsorigidx[j]];
else if( candsscore[candsorigidx[j]] > scoremax )
scoremax = candsscore[candsorigidx[j]];
/* @todo if there are two valid externcandssol available for the same variable, should we take the one closer to the middle of the domain? */
if( SCIPisInfinity(scip, REALABS(candsol)) )
candsol = candssol[candsorigidx[j]];
}
/* set i to last occurrence of cand in candssorted (instead of first one as before), so in next round we look at another variable */
i = j-1;
assert(candssorted[i] == cand);
/* check if new candidate is better than previous candidate (if any) */
SCIP_CALL( updateBestCandidate(scip, branchruledata, brvar, brpoint, &bestbranchscore, cand, scoremin, scoremax, scoresum, candsol) );
}
/* there were candidates, but no variable was selected; this can only happen if the branching points are huge values
* for all variables on which we cannot branch
* @todo delay the node?
*/
if( (*brvar) == NULL )
{
SCIPerrorMessage("no branching could be created: all external candidates have huge bounds\n");
SCIPABORT();
return SCIP_BRANCHERROR; /*lint !e527*/
}
/* free buffer arrays */
SCIPfreeBufferArray(scip, &candssorted);
SCIPfreeBufferArray(scip, &candsorigidx);
return SCIP_OKAY;
}
/** constraint parsing method of constraint handler */
static
SCIP_DECL_CONSPARSE(consParseConjunction)
{ /*lint --e{715}*/
SCIP_CONS** conss;
int nconss;
int sconss;
char* token;
char* saveptr;
char* nexttokenstart;
char* copystr;
assert(scip != NULL);
assert(conshdlr != NULL);
assert(cons != NULL);
assert(success != NULL);
assert(str != NULL);
assert(name != NULL);
SCIPdebugMessage("parsing conjunction <%s>\n", name);
*success = TRUE;
/* allocate memory for constraint in conjunction, initial size is set to 10 */
nconss = 0;
sconss = 10;
SCIP_CALL( SCIPallocBufferArray(scip, &conss, sconss) );
SCIP_CALL( SCIPduplicateBufferArray(scip, ©str, str, (int)strlen(str)+1) );
/* find '(' at the beginning, string should start with 'conjunction(' */
saveptr = strpbrk(copystr, "("); /*lint !e158*/
if( saveptr == NULL )
{
SCIPdebugMessage("error parsing conjunctive constraint: \"%s\"\n", str);
*success = FALSE;
goto TERMINATE;
}
/* skip '(' */
++saveptr;
/* remember token start position */
nexttokenstart = saveptr;
/* brackets '(' and ')' can exist co we check for them and the constraint delimeter */
saveptr = strpbrk(saveptr, "(,");
/* brackets '(' and ')' can exist in the rest of the string so we need to skip them to find the end of the first
* sub-constraint marked by a ','
*/
if( saveptr != NULL )
{
do
{
int bracketcounter = 0;
if( *saveptr == '(' )
{
do
{
++bracketcounter;
++saveptr;
/* find last ending bracket */
while( bracketcounter > 0 )
{
saveptr = strpbrk(saveptr, "()");
if( saveptr != NULL )
{
if( *saveptr == '(' )
++bracketcounter;
else
--bracketcounter;
++saveptr;
}
else
{
SCIPdebugMessage("error parsing conjunctive constraint: \"%s\"\n", str);
*success = FALSE;
goto TERMINATE;
}
}
saveptr = strpbrk(saveptr, "(,");
}
while( saveptr != NULL && *saveptr == '(' );
}
/* we found a ',' so the end of the first sub-constraint is determined */
if( saveptr != NULL )
{
assert(*saveptr == ',');
/* resize constraint array if necessary */
if( nconss == sconss )
{
sconss = SCIPcalcMemGrowSize(scip, nconss+1);
assert(nconss < sconss);
SCIP_CALL( SCIPreallocBufferArray(scip, &conss, sconss) );
}
assert(saveptr > nexttokenstart);
/* extract token for parsing */
SCIP_CALL( SCIPduplicateBufferArray(scip, &token, nexttokenstart, saveptr - nexttokenstart + 1) );
token[saveptr - nexttokenstart] = '\0';
SCIPdebugMessage("conjunctive parsing token(constraint): %s\n", token);
/* parsing a constraint, part of the conjunction */
SCIP_CALL( SCIPparseCons(scip, &(conss[nconss]), token, initial, separate, enforce, check, propagate, local, modifiable, dynamic, removable, stickingatnode, success) );
SCIPfreeBufferArray(scip, &token);
if( *success )
++nconss;
else
{
SCIPdebugMessage("error parsing conjunctive constraint: \"%s\"\n", str);
goto TERMINATE;
}
/* skip ',' delimeter */
++saveptr;
/* remember token start position */
nexttokenstart = saveptr;
saveptr = strpbrk(saveptr, "(,");
}
}
while( saveptr != NULL );
}
/* find end of conjunction constraint */
saveptr = strrchr(nexttokenstart, ')');
if( saveptr == NULL )
{
SCIPdebugMessage("error parsing conjunctive constraint: \"%s\"\n", str);
*success = FALSE;
goto TERMINATE;
}
/* parse last sub-constraint */
else
{
/* resize constraint array if necessary */
if( nconss == sconss )
{
++sconss;
SCIP_CALL( SCIPreallocBufferArray(scip, &conss, sconss) );
}
assert(saveptr > nexttokenstart);
/* extract token for parsing */
SCIP_CALL( SCIPduplicateBufferArray(scip, &token, nexttokenstart, saveptr - nexttokenstart + 1) );
token[saveptr - nexttokenstart] = '\0';
SCIPdebugMessage("conjunctive parsing token(constraint): %s\n", token);
/* parsing a constraint, part of the conjunction */
SCIP_CALL( SCIPparseCons(scip, &(conss[nconss]), token, initial, separate, enforce, check, propagate, local, modifiable, dynamic, removable, stickingatnode, success) );
if( *success )
++nconss;
SCIPfreeBufferArray(scip, &token);
}
assert(nconss > 0 || !(*success));
/* if parsing sub-constraints was fine, create the conjunctive constraint */
if( *success )
{
/* create conjunctive constraint */
SCIP_CALL( SCIPcreateConsConjunction(scip, cons, name, nconss, conss,
enforce, check, local, modifiable, dynamic) );
}
/* free parsed constraints */
for( --nconss; nconss >= 0; --nconss )
{
SCIP_CALL( SCIPreleaseCons(scip, &conss[nconss]) );
}
TERMINATE:
/* free temporary memory */
SCIPfreeBufferArray(scip, ©str);
SCIPfreeBufferArray(scip, &conss);
return SCIP_OKAY;
}
/** transforms given solution of the master problem into solution of the original problem
* @todo think about types of epsilons used in this method
*/
SCIP_RETCODE GCGrelaxTransformMastersolToOrigsol(
SCIP* scip, /**< SCIP data structure */
SCIP_SOL* mastersol, /**< solution of the master problem, or NULL for current LP solution */
SCIP_SOL** origsol /**< pointer to store the new created original problem's solution */
)
{
SCIP* masterprob;
int npricingprobs;
int* blocknrs;
SCIP_Real* blockvalue;
SCIP_Real increaseval;
SCIP_VAR** mastervars;
SCIP_Real* mastervals;
int nmastervars;
SCIP_VAR** vars;
int nvars;
SCIP_Real feastol;
int i;
int j;
assert(scip != NULL);
assert(origsol != NULL);
masterprob = GCGrelaxGetMasterprob(scip);
npricingprobs = GCGrelaxGetNPricingprobs(scip);
assert( !SCIPisInfinity(scip, SCIPgetSolOrigObj(masterprob, mastersol)) );
SCIP_CALL( SCIPcreateSol(scip, origsol, GCGrelaxGetProbingheur(scip)) );
SCIP_CALL( SCIPallocBufferArray(scip, &blockvalue, npricingprobs) );
SCIP_CALL( SCIPallocBufferArray(scip, &blocknrs, npricingprobs) );
/* get variables of the master problem and their solution values */
SCIP_CALL( SCIPgetVarsData(masterprob, &mastervars, &nmastervars, NULL, NULL, NULL, NULL) );
assert(mastervars != NULL);
assert(nmastervars >= 0);
SCIP_CALL( SCIPallocBufferArray(scip, &mastervals, nmastervars) );
SCIP_CALL( SCIPgetSolVals(masterprob, mastersol, nmastervars, mastervars, mastervals) );
/* initialize the block values for the pricing problems */
for( i = 0; i < npricingprobs; i++ )
{
blockvalue[i] = 0.0;
blocknrs[i] = 0;
}
/* loop over all given master variables */
for( i = 0; i < nmastervars; i++ )
{
SCIP_VAR** origvars;
int norigvars;
SCIP_Real* origvals;
SCIP_Bool isray;
int blocknr;
origvars = GCGmasterVarGetOrigvars(mastervars[i]);
norigvars = GCGmasterVarGetNOrigvars(mastervars[i]);
origvals = GCGmasterVarGetOrigvals(mastervars[i]);
blocknr = GCGvarGetBlock(mastervars[i]);
isray = GCGmasterVarIsRay(mastervars[i]);
assert(GCGvarIsMaster(mastervars[i]));
assert(!SCIPisFeasNegative(scip, mastervals[i]));
/** @todo handle infinite master solution values */
assert(!SCIPisInfinity(scip, mastervals[i]));
/* first of all, handle variables representing rays */
if( isray )
{
assert(blocknr >= 0);
/* we also want to take into account variables representing rays, that have a small value (between normal and feas eps),
* so we do no feas comparison here */
if( SCIPisPositive(scip, mastervals[i]) )
{
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
if( SCIPisZero(scip, origvals[j]) )
break;
assert(!SCIPisZero(scip, origvals[j]));
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done later) */
if( GCGvarIsLinking(origvars[j]) )
continue;
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[j]), origvals[j] * mastervals[i], SCIPvarGetName(mastervars[i]));
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[j], origvals[j] * mastervals[i]) );
}
}
mastervals[i] = 0.0;
continue;
}
/* handle the variables with value >= 1 to get integral values in original solution */
while( SCIPisFeasGE(scip, mastervals[i], 1.0) )
{
/* variable was directly transferred to the master problem (only in linking conss or linking variable) */
/** @todo this may be the wrong place for this case, handle it before the while loop
* and remove the similar case in the next while loop */
if( blocknr == -1 )
{
assert(norigvars == 1);
assert(origvals[0] == 1.0);
/* increase the corresponding value */
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[0]), origvals[0] * mastervals[i], SCIPvarGetName(mastervars[i]));
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[0], origvals[0] * mastervals[i]) );
mastervals[i] = 0.0;
}
else
{
assert(blocknr >= 0);
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
SCIP_VAR* pricingvar;
int norigpricingvars;
SCIP_VAR** origpricingvars;
if( SCIPisZero(scip, origvals[j]) )
break;
assert(!SCIPisZero(scip, origvals[j]));
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done above) */
if( GCGvarIsLinking(origvars[j]) )
continue;
pricingvar = GCGoriginalVarGetPricingVar(origvars[j]);
assert(GCGvarIsPricing(pricingvar));
norigpricingvars = GCGpricingVarGetNOrigvars(pricingvar);
origpricingvars = GCGpricingVarGetOrigvars(pricingvar);
/* just in case a variable has a value higher than the number of blocks, it represents */
if( norigpricingvars <= blocknrs[blocknr] )
{
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[norigpricingvars-1]), mastervals[i] * origvals[j], SCIPvarGetName(mastervars[i]));
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[norigpricingvars-1], mastervals[i] * origvals[j]) );
mastervals[i] = 1.0;
}
/* this should be default */
else
{
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[blocknrs[blocknr]]), origvals[j], SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[blocknrs[blocknr]], origvals[j]) );
}
}
mastervals[i] = mastervals[i] - 1.0;
blocknrs[blocknr]++;
}
}
}
/* loop over all given master variables */
for( i = 0; i < nmastervars; i++ )
{
SCIP_VAR** origvars;
int norigvars;
SCIP_Real* origvals;
int blocknr;
origvars = GCGmasterVarGetOrigvars(mastervars[i]);
norigvars = GCGmasterVarGetNOrigvars(mastervars[i]);
origvals = GCGmasterVarGetOrigvals(mastervars[i]);
blocknr = GCGvarGetBlock(mastervars[i]);
if( SCIPisFeasZero(scip, mastervals[i]) )
{
continue;
}
assert(SCIPisFeasGE(scip, mastervals[i], 0.0) && SCIPisFeasLT(scip, mastervals[i], 1.0));
while( SCIPisFeasPositive(scip, mastervals[i]) )
{
assert(GCGvarIsMaster(mastervars[i]));
assert(!GCGmasterVarIsRay(mastervars[i]));
if( blocknr == -1 )
{
assert(norigvars == 1);
assert(origvals[0] == 1.0);
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[0]), origvals[0] * mastervals[i], SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[0], origvals[0] * mastervals[i]) );
mastervals[i] = 0.0;
}
else
{
increaseval = MIN(mastervals[i], 1.0 - blockvalue[blocknr]);
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
SCIP_VAR* pricingvar;
int norigpricingvars;
SCIP_VAR** origpricingvars;
if( SCIPisZero(scip, origvals[j]) )
continue;
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done above) */
if( GCGvarIsLinking(origvars[j]) )
continue;
pricingvar = GCGoriginalVarGetPricingVar(origvars[j]);
assert(GCGvarIsPricing(pricingvar));
norigpricingvars = GCGpricingVarGetNOrigvars(pricingvar);
origpricingvars = GCGpricingVarGetOrigvars(pricingvar);
if( norigpricingvars <= blocknrs[blocknr] )
{
increaseval = mastervals[i];
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[norigpricingvars-1]), origvals[j] * increaseval, SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[norigpricingvars-1], origvals[j] * increaseval) );
}
else
{
/* increase the corresponding value */
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[blocknrs[blocknr]]), origvals[j] * increaseval, SCIPvarGetName(mastervars[i]) );
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[blocknrs[blocknr]], origvals[j] * increaseval) );
}
}
mastervals[i] = mastervals[i] - increaseval;
if( SCIPisFeasZero(scip, mastervals[i]) )
{
mastervals[i] = 0.0;
}
blockvalue[blocknr] += increaseval;
/* if the value assigned to the block is equal to 1, this block is full and we take the next block */
if( SCIPisFeasGE(scip, blockvalue[blocknr], 1.0) )
{
blockvalue[blocknr] = 0.0;
blocknrs[blocknr]++;
}
}
}
}
SCIPfreeBufferArray(scip, &mastervals);
SCIPfreeBufferArray(scip, &blocknrs);
SCIPfreeBufferArray(scip, &blockvalue);
/* if the solution violates one of its bounds by more than feastol
* and less than 10*feastol, round it and print a warning
*/
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPgetRealParam(scip, "numerics/feastol", &feastol) );
for( i = 0; i < nvars; ++i )
{
SCIP_Real solval;
SCIP_Real lb;
SCIP_Real ub;
solval = SCIPgetSolVal(scip, *origsol, vars[i]);
lb = SCIPvarGetLbLocal(vars[i]);
ub = SCIPvarGetUbLocal(vars[i]);
if( SCIPisFeasGT(scip, solval, ub) && EPSEQ(solval, ub, 10 * feastol) )
{
SCIP_CALL( SCIPsetSolVal(scip, *origsol, vars[i], ub) );
SCIPwarningMessage(scip, "Variable %s rounded from %g to %g in relaxation solution\n",
SCIPvarGetName(vars[i]), solval, ub);
}
else if( SCIPisFeasLT(scip, solval, lb) && EPSEQ(solval, lb, 10 * feastol) )
{
SCIP_CALL( SCIPsetSolVal(scip, *origsol, vars[i], lb) );
SCIPwarningMessage(scip, "Variable %s rounded from %g to %g in relaxation solution\n",
SCIPvarGetName(vars[i]), solval, lb);
}
}
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecObjpscostdiving) /*lint --e{715}*/
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_LPSOLSTAT lpsolstat;
SCIP_VAR* var;
SCIP_VAR** lpcands;
SCIP_Real* lpcandssol;
SCIP_Real* lpcandsfrac;
SCIP_Real primsol;
SCIP_Real frac;
SCIP_Real pscostquot;
SCIP_Real bestpscostquot;
SCIP_Real oldobj;
SCIP_Real newobj;
SCIP_Real objscale;
SCIP_Bool bestcandmayrounddown;
SCIP_Bool bestcandmayroundup;
SCIP_Bool bestcandroundup;
SCIP_Bool mayrounddown;
SCIP_Bool mayroundup;
SCIP_Bool roundup;
SCIP_Bool lperror;
SCIP_Longint ncalls;
SCIP_Longint nsolsfound;
SCIP_Longint nlpiterations;
SCIP_Longint maxnlpiterations;
int* roundings;
int nvars;
int varidx;
int nlpcands;
int startnlpcands;
int depth;
int maxdepth;
int maxdivedepth;
int divedepth;
int bestcand;
int c;
assert(heur != NULL);
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
assert(SCIPhasCurrentNodeLP(scip));
*result = SCIP_DELAYED;
/* 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;
/* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */
if( !SCIPisLPSolBasic(scip) )
return SCIP_OKAY;
/* don't dive two times at the same node */
if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* only apply heuristic, if only a few solutions have been found */
if( heurdata->maxsols >= 0 && SCIPgetNSolsFound(scip) >= heurdata->maxsols )
return SCIP_OKAY;
/* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */
depth = SCIPgetDepth(scip);
maxdepth = SCIPgetMaxDepth(scip);
maxdepth = MAX(maxdepth, 30);
if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth )
return SCIP_OKAY;
/* calculate the maximal number of LP iterations until heuristic is aborted */
nlpiterations = SCIPgetNNodeLPIterations(scip);
ncalls = SCIPheurGetNCalls(heur);
nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess;
maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations);
maxnlpiterations += heurdata->maxlpiterofs;
/* don't try to dive, if we took too many LP iterations during diving */
if( heurdata->nlpiterations >= maxnlpiterations )
return SCIP_OKAY;
/* allow at least a certain number of LP iterations in this dive */
maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER);
/* get fractional variables that should be integral */
SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) );
/* don't try to dive, if there are no fractional variables */
if( nlpcands == 0 )
return SCIP_OKAY;
/* calculate the maximal diving depth */
nvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip);
if( SCIPgetNSolsFound(scip) == 0 )
maxdivedepth = (int)(heurdata->depthfacnosol * nvars);
else
maxdivedepth = (int)(heurdata->depthfac * nvars);
maxdivedepth = MIN(maxdivedepth, 10*maxdepth);
*result = SCIP_DIDNOTFIND;
/* get temporary memory for remembering the current soft roundings */
SCIP_CALL( SCIPallocBufferArray(scip, &roundings, nvars) );
BMSclearMemoryArray(roundings, nvars);
/* start diving */
SCIP_CALL( SCIPstartDive(scip) );
SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") executing objpscostdiving heuristic: depth=%d, %d fractionals, dualbound=%g, maxnlpiterations=%"SCIP_LONGINT_FORMAT", maxdivedepth=%d\n",
SCIPgetNNodes(scip), SCIPgetDepth(scip), nlpcands, SCIPgetDualbound(scip), maxnlpiterations, maxdivedepth);
/* dive as long we are in the given diving depth and iteration limits and fractional variables exist, but
* - if the last objective change was in a direction, that corresponds to a feasible rounding, we continue in any case
* - if possible, we dive at least with the depth 10
* - if the number of fractional variables decreased at least with 1 variable per 2 dive depths, we continue diving
*/
lperror = FALSE;
lpsolstat = SCIP_LPSOLSTAT_OPTIMAL;
divedepth = 0;
bestcandmayrounddown = FALSE;
bestcandmayroundup = FALSE;
startnlpcands = nlpcands;
while( !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL && nlpcands > 0
&& (divedepth < 10
|| nlpcands <= startnlpcands - divedepth/2
|| (divedepth < maxdivedepth && nlpcands <= startnlpcands - divedepth/10
&& heurdata->nlpiterations < maxnlpiterations)) && !SCIPisStopped(scip) )
{
SCIP_RETCODE retcode;
divedepth++;
/* choose variable for objective change:
* - prefer variables that may not be rounded without destroying LP feasibility:
* - of these variables, change objective value of variable with largest rel. difference of pseudo cost values
* - if all remaining fractional variables may be rounded without destroying LP feasibility:
* - change objective value of variable with largest rel. difference of pseudo cost values
*/
bestcand = -1;
bestpscostquot = -1.0;
bestcandmayrounddown = TRUE;
bestcandmayroundup = TRUE;
bestcandroundup = FALSE;
for( c = 0; c < nlpcands; ++c )
{
var = lpcands[c];
mayrounddown = SCIPvarMayRoundDown(var);
mayroundup = SCIPvarMayRoundUp(var);
primsol = lpcandssol[c];
frac = lpcandsfrac[c];
if( mayrounddown || mayroundup )
{
/* the candidate may be rounded: choose this candidate only, if the best candidate may also be rounded */
if( bestcandmayrounddown || bestcandmayroundup )
{
/* choose rounding direction:
* - if variable may be rounded in both directions, round corresponding to the pseudo cost values
* - otherwise, round in the infeasible direction, because feasible direction is tried by rounding
* the current fractional solution
*/
roundup = FALSE;
if( mayrounddown && mayroundup )
calcPscostQuot(scip, var, primsol, frac, 0, &pscostquot, &roundup);
else if( mayrounddown )
calcPscostQuot(scip, var, primsol, frac, +1, &pscostquot, &roundup);
else
calcPscostQuot(scip, var, primsol, frac, -1, &pscostquot, &roundup);
/* prefer variables, that have already been soft rounded but failed to get integral */
varidx = SCIPvarGetProbindex(var);
assert(0 <= varidx && varidx < nvars);
if( roundings[varidx] != 0 )
pscostquot *= 1000.0;
/* check, if candidate is new best candidate */
if( pscostquot > bestpscostquot )
{
bestcand = c;
bestpscostquot = pscostquot;
bestcandmayrounddown = mayrounddown;
bestcandmayroundup = mayroundup;
bestcandroundup = roundup;
}
}
}
else
{
/* the candidate may not be rounded: calculate pseudo cost quotient and preferred direction */
calcPscostQuot(scip, var, primsol, frac, 0, &pscostquot, &roundup);
/* prefer variables, that have already been soft rounded but failed to get integral */
varidx = SCIPvarGetProbindex(var);
assert(0 <= varidx && varidx < nvars);
if( roundings[varidx] != 0 )
pscostquot *= 1000.0;
/* check, if candidate is new best candidate: prefer unroundable candidates in any case */
if( bestcandmayrounddown || bestcandmayroundup || pscostquot > bestpscostquot )
{
bestcand = c;
bestpscostquot = pscostquot;
bestcandmayrounddown = FALSE;
bestcandmayroundup = FALSE;
bestcandroundup = roundup;
}
}
}
assert(bestcand != -1);
/* if all candidates are roundable, try to round the solution */
if( bestcandmayrounddown || bestcandmayroundup )
{
SCIP_Bool success;
/* create solution from diving LP and try to round it */
SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) );
if( success )
{
SCIPdebugMessage("objpscostdiving found roundable primal solution: obj=%g\n",
SCIPgetSolOrigObj(scip, heurdata->sol));
/* try to add solution to SCIP */
SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );
/* check, if solution was feasible and good enough */
if( success )
{
SCIPdebugMessage(" -> solution was feasible and good enough\n");
*result = SCIP_FOUNDSOL;
}
}
}
var = lpcands[bestcand];
/* check, if the best candidate was already subject to soft rounding */
varidx = SCIPvarGetProbindex(var);
assert(0 <= varidx && varidx < nvars);
if( roundings[varidx] == +1 )
{
/* variable was already soft rounded upwards: hard round it downwards */
SCIP_CALL( SCIPchgVarUbDive(scip, var, SCIPfeasFloor(scip, lpcandssol[bestcand])) );
SCIPdebugMessage(" dive %d/%d: var <%s>, round=%u/%u, sol=%g, was already soft rounded upwards -> bounds=[%g,%g]\n",
divedepth, maxdivedepth, SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var));
}
else if( roundings[varidx] == -1 )
{
/* variable was already soft rounded downwards: hard round it upwards */
SCIP_CALL( SCIPchgVarLbDive(scip, var, SCIPfeasCeil(scip, lpcandssol[bestcand])) );
SCIPdebugMessage(" dive %d/%d: var <%s>, round=%u/%u, sol=%g, was already soft rounded downwards -> bounds=[%g,%g]\n",
divedepth, maxdivedepth, SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var));
}
else
{
assert(roundings[varidx] == 0);
/* apply soft rounding of best candidate via a change in the objective value */
objscale = divedepth * 1000.0;
oldobj = SCIPgetVarObjDive(scip, var);
if( bestcandroundup )
{
/* soft round variable up: make objective value (more) negative */
if( oldobj < 0.0 )
newobj = objscale * oldobj;
else
newobj = -objscale * oldobj;
newobj = MIN(newobj, -objscale);
/* remember, that this variable was soft rounded upwards */
roundings[varidx] = +1;
}
else
{
/* soft round variable down: make objective value (more) positive */
if( oldobj > 0.0 )
newobj = objscale * oldobj;
else
newobj = -objscale * oldobj;
newobj = MAX(newobj, objscale);
/* remember, that this variable was soft rounded downwards */
roundings[varidx] = -1;
}
SCIP_CALL( SCIPchgVarObjDive(scip, var, newobj) );
SCIPdebugMessage(" dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT": var <%s>, round=%u/%u, sol=%g, bounds=[%g,%g], obj=%g, newobj=%g\n",
divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations,
SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var), oldobj, newobj);
}
/* resolve the diving LP */
nlpiterations = SCIPgetNLPIterations(scip);
retcode = SCIPsolveDiveLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, NULL);
lpsolstat = SCIPgetLPSolstat(scip);
/* 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.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
if( lpsolstat != SCIP_LPSOLSTAT_UNBOUNDEDRAY )
{
SCIP_CALL( retcode );
}
#endif
SCIPwarningMessage(scip, "Error while solving LP in Objpscostdiving heuristic; LP solve terminated with code <%d>\n", retcode);
SCIPwarningMessage(scip, "This does not affect the remaining solution procedure --> continue\n");
}
if( lperror )
break;
/* update iteration count */
heurdata->nlpiterations += SCIPgetNLPIterations(scip) - nlpiterations;
/* get LP solution status and fractional variables, that should be integral */
if( lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
{
/* get new fractional variables */
SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) );
}
SCIPdebugMessage(" -> lpsolstat=%d, nfrac=%d\n", lpsolstat, nlpcands);
}
/* check if a solution has been found */
if( nlpcands == 0 && !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
{
SCIP_Bool success;
/* create solution from diving LP */
SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
SCIPdebugMessage("objpscostdiving found primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol));
/* try to add solution to SCIP */
SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );
/* check, if solution was feasible and good enough */
if( success )
{
SCIPdebugMessage(" -> solution was feasible and good enough\n");
*result = SCIP_FOUNDSOL;
}
}
/* end diving */
SCIP_CALL( SCIPendDive(scip) );
if( *result == SCIP_FOUNDSOL )
heurdata->nsuccess++;
/* free temporary memory for remembering the current soft roundings */
SCIPfreeBufferArray(scip, &roundings);
SCIPdebugMessage("objpscostdiving heuristic finished\n");
return SCIP_OKAY;
}
/** creates and captures a linear constraint
*
* @note the constraint gets captured, hence at one point you have to release it using the method {@link releaseCons()}
*/
JNIEXPORT
jlong JNISCIPCONSLINEAR(createConsLinear)(
JNIEnv* env, /**< JNI environment variable */
jobject jobj, /**< JNI class pointer */
jlong jscip, /**< SCIP data structure */
jstring jname, /**< name of constraint */
jint jnvars, /**< number of nonzeros in the constraint */
jlongArray jvars, /**< array with variables of constraint entries */
jdoubleArray jvals, /**< array with coefficients of constraint entries */
jdouble jlhs, /**< left hand side of constraint */
jdouble jrhs, /**< right hand side of constraint */
jboolean initial, /**< should the LP relaxation of constraint be in the initial LP?
* Usually set to TRUE. Set to FALSE for 'lazy constraints'. */
jboolean separate, /**< should the constraint be separated during LP processing?
* Usually set to TRUE. */
jboolean enforce, /**< should the constraint be enforced during node processing?
* TRUE for model constraints, FALSE for additional, redundant constraints. */
jboolean check, /**< should the constraint be checked for feasibility?
* TRUE for model constraints, FALSE for additional, redundant constraints. */
jboolean propagate, /**< should the constraint be propagated during node processing?
* Usually set to TRUE. */
jboolean local, /**< is constraint only valid locally?
* Usually set to FALSE. Has to be set to TRUE, e.g., for branching constraints. */
jboolean modifiable, /**< is constraint modifiable (subject to column generation)?
* Usually set to FALSE. In column generation applications, set to TRUE if pricing
* adds coefficients to this constraint. */
jboolean dynamic, /**< is constraint subject to aging?
* Usually set to FALSE. Set to TRUE for own cuts which
* are seperated as constraints. */
jboolean removable, /**< should the relaxation be removed from the LP due to aging or cleanup?
* Usually set to FALSE. Set to TRUE for 'lazy constraints' and 'user cuts'. */
jboolean stickingatnode /**< should the constraint always be kept at the node where it was added, even
* if it may be moved to a more global node?
* Usually set to FALSE. Set to TRUE to for constraints that represent node data. */
)
{
SCIP* scip;
SCIP_CONS* cons;
const char* name;
int nvars;
/* convert JNI pointer into C pointer */
scip = (SCIP*) (size_t) jscip;
assert(scip != NULL);
/* convert JNI string into C const char* */
name = (*env)->GetStringUTFChars(env, jname, NULL);
if( name == NULL )
SCIPABORT();
/* create linear constraint with zero variables */
JNISCIP_CALL( SCIPcreateConsLinear(scip, &cons, name, 0, NULL, NULL, (SCIP_Real) jlhs, (SCIP_Real) jrhs,
(SCIP_Bool) initial, (SCIP_Bool) separate, (SCIP_Bool) enforce, (SCIP_Bool) check, (SCIP_Bool) propagate,
(SCIP_Bool) local, (SCIP_Bool) modifiable, (SCIP_Bool) dynamic, (SCIP_Bool) removable, (SCIP_Bool) stickingatnode) );
/* convert JNI integer into integer */
nvars = (int)jnvars;
if( nvars > 0 )
{
jlong* vars;
jdouble* vals;
int v;
JNISCIP_CALL( SCIPallocBufferArray(scip, &vars, nvars) );
JNISCIP_CALL( SCIPallocBufferArray(scip, &vals, nvars) );
(*env)->GetLongArrayRegion(env, jvars, 0, nvars, vars);
(*env)->GetDoubleArrayRegion(env, jvals, 0, nvars, vals);
for( v = 0; v < nvars; ++v )
{
JNISCIP_CALL( SCIPaddCoefLinear(scip, cons, (SCIP_VAR*)(size_t)vars[v], (SCIP_Real)vals[v]));
}
SCIPfreeBufferArray(scip, &vals);
SCIPfreeBufferArray(scip, &vars);
}
/* relase string object */
(*env)->ReleaseStringUTFChars(env, jname, name);
return (jlong)(size_t)cons;
}
/** creates a subproblem for subscip by fixing a number of variables */
static
SCIP_RETCODE createSubproblem(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP data structure for the subproblem */
SCIP_VAR** subvars, /**< the variables of the subproblem */
SCIP_Real minfixingrate, /**< percentage of integer variables that have to be fixed */
unsigned int* randseed, /**< a seed value for the random number generator */
SCIP_Bool uselprows /**< should subproblem be created out of the rows in the LP rows? */
)
{
SCIP_VAR** vars; /* original scip variables */
SCIP_SOL* sol; /* pool of solutions */
SCIP_Bool* marked; /* array of markers, which variables to fixed */
SCIP_Bool fixingmarker; /* which flag should label a fixed variable? */
int nvars;
int nbinvars;
int nintvars;
int i;
int j;
int nmarkers;
/* get required data of the original problem */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
sol = SCIPgetBestSol(scip);
assert(sol != NULL);
SCIP_CALL( SCIPallocBufferArray(scip, &marked, nbinvars+nintvars) );
if( minfixingrate > 0.5 )
{
nmarkers = nbinvars + nintvars - (int) SCIPfloor(scip, minfixingrate*(nbinvars+nintvars));
fixingmarker = FALSE;
}
else
{
nmarkers = (int) SCIPceil(scip, minfixingrate*(nbinvars+nintvars));
fixingmarker = TRUE;
}
assert( 0 <= nmarkers && nmarkers <= SCIPceil(scip,(nbinvars+nintvars)/2.0 ) );
j = 0;
BMSclearMemoryArray(marked, nbinvars+nintvars);
while( j < nmarkers )
{
do
{
i = SCIPgetRandomInt(0, nbinvars+nintvars-1, randseed);
}
while( marked[i] );
marked[i] = TRUE;
j++;
}
assert( j == nmarkers );
/* change bounds of variables of the subproblem */
for( i = 0; i < nbinvars + nintvars; i++ )
{
/* fix all randomly marked variables */
if( marked[i] == fixingmarker )
{
SCIP_Real solval;
SCIP_Real lb;
SCIP_Real ub;
solval = SCIPgetSolVal(scip, sol, vars[i]);
lb = SCIPvarGetLbGlobal(subvars[i]);
ub = SCIPvarGetUbGlobal(subvars[i]);
assert(SCIPisLE(scip, lb, ub));
/* due to dual reductions, it may happen that the solution value is not in
the variable's domain anymore */
if( SCIPisLT(scip, solval, lb) )
solval = lb;
else if( SCIPisGT(scip, solval, ub) )
solval = ub;
/* perform the bound change */
if( !SCIPisInfinity(scip, solval) && !SCIPisInfinity(scip, -solval) )
{
SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], solval) );
SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], solval) );
}
}
}
if( uselprows )
{
SCIP_ROW** rows; /* original scip rows */
int nrows;
/* get the rows and their number */
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
/* copy all rows to linear constraints */
for( i = 0; i < nrows; i++ )
{
SCIP_CONS* cons;
SCIP_VAR** consvars;
SCIP_COL** cols;
SCIP_Real constant;
SCIP_Real lhs;
SCIP_Real rhs;
SCIP_Real* vals;
int nnonz;
/* ignore rows that are only locally valid */
if( SCIProwIsLocal(rows[i]) )
continue;
/* get the row's data */
constant = SCIProwGetConstant(rows[i]);
lhs = SCIProwGetLhs(rows[i]) - constant;
rhs = SCIProwGetRhs(rows[i]) - constant;
vals = SCIProwGetVals(rows[i]);
nnonz = SCIProwGetNNonz(rows[i]);
cols = SCIProwGetCols(rows[i]);
assert( lhs <= rhs );
/* allocate memory array to be filled with the corresponding subproblem variables */
SCIP_CALL( SCIPallocBufferArray(scip, &consvars, nnonz) );
for( j = 0; j < nnonz; j++ )
consvars[j] = subvars[SCIPvarGetProbindex(SCIPcolGetVar(cols[j]))];
/* create a new linear constraint and add it to the subproblem */
SCIP_CALL( SCIPcreateConsLinear(subscip, &cons, SCIProwGetName(rows[i]), nnonz, consvars, vals, lhs, rhs,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
/* free temporary memory */
SCIPfreeBufferArray(scip, &consvars);
}
}
SCIPfreeBufferArray(scip, &marked);
return SCIP_OKAY;
}
/** execution method of presolver */
static
SCIP_DECL_PRESOLEXEC(presolExecDualagg)
{ /*lint --e{715}*/
SCIPMILPMATRIX* matrix;
SCIP_Bool initialized;
SCIP_Bool complete;
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
if( (SCIPgetStage(scip) != SCIP_STAGE_PRESOLVING) || SCIPinProbing(scip) || SCIPisNLPEnabled(scip) )
return SCIP_OKAY;
if( SCIPisStopped(scip) || SCIPgetNActivePricers(scip) > 0 )
return SCIP_OKAY;
if( SCIPgetNBinVars(scip) == 0 )
return SCIP_OKAY;
if( !SCIPallowDualReds(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
matrix = NULL;
SCIP_CALL( SCIPmatrixCreate(scip, &matrix, &initialized, &complete) );
/* we only work on pure MIPs currently */
if( initialized && complete )
{
AGGRTYPE* aggtypes;
SCIP_VAR** binvars;
int nvaragg;
int ncols;
ncols = SCIPmatrixGetNColumns(matrix);
nvaragg = 0;
SCIP_CALL( SCIPallocBufferArray(scip, &aggtypes, ncols) );
BMSclearMemoryArray(aggtypes, ncols);
SCIP_CALL( SCIPallocBufferArray(scip, &binvars, ncols) );
SCIPdebug( BMSclearMemoryArray(binvars, ncols) );
/* search for aggregations */
SCIP_CALL( findUplockAggregations(scip, matrix, &nvaragg, aggtypes, binvars) );
SCIP_CALL( findDownlockAggregations(scip, matrix, &nvaragg, aggtypes, binvars) );
/* apply aggregations, if we found any */
if( nvaragg > 0 )
{
int v;
for( v = 0; v < ncols; v++ )
{
if( aggtypes[v] != NOAGG )
{
SCIP_Bool infeasible;
SCIP_Bool redundant;
SCIP_Bool aggregated;
SCIP_Real ub;
SCIP_Real lb;
ub = SCIPmatrixGetColUb(matrix, v);
lb = SCIPmatrixGetColLb(matrix, v);
/* aggregate variable */
assert(binvars[v] != NULL);
if( aggtypes[v] == BIN0UBOUND )
{
SCIP_CALL( SCIPaggregateVars(scip, SCIPmatrixGetVar(matrix, v), binvars[v], 1.0, ub-lb,
ub, &infeasible, &redundant, &aggregated) );
}
else
{
assert(aggtypes[v] == BIN0LBOUND);
SCIP_CALL( SCIPaggregateVars(scip, SCIPmatrixGetVar(matrix, v), binvars[v], 1.0, lb-ub,
lb, &infeasible, &redundant, &aggregated) );
}
/* infeasible aggregation */
if( infeasible )
{
SCIPdebugMessage(" -> infeasible aggregation\n");
*result = SCIP_CUTOFF;
return SCIP_OKAY;
}
if( aggregated )
(*naggrvars)++;
}
}
/* set result pointer */
if( (*naggrvars) > 0 )
*result = SCIP_SUCCESS;
}
SCIPfreeBufferArray(scip, &binvars);
SCIPfreeBufferArray(scip, &aggtypes);
}
SCIPmatrixFree(scip, &matrix);
return SCIP_OKAY;
}
/** 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;
}
/* Read SAT formula in "CNF File Format".
*
* The specification is taken from the
*
* Satisfiability Suggested Format
*
* Online available at http://www.intellektik.informatik.tu-darmstadt.de/SATLIB/Benchmarks/SAT/satformat.ps
*
* The method reads all files of CNF format. Other formats (SAT, SATX, SATE) are not supported.
*/
static
SCIP_RETCODE readCnf(
SCIP* scip, /**< SCIP data structure */
SCIP_FILE* file /**< input file */
)
{
SCIP_RETCODE retcode;
SCIP_VAR** vars;
SCIP_VAR** clausevars;
SCIP_CONS* cons;
int* varsign;
char* tok;
char* nexttok;
char line[MAXLINELEN];
char format[SCIP_MAXSTRLEN];
char varname[SCIP_MAXSTRLEN];
char s[SCIP_MAXSTRLEN];
SCIP_Bool dynamicconss;
SCIP_Bool dynamiccols;
SCIP_Bool dynamicrows;
SCIP_Bool useobj;
int linecount;
int clauselen;
int clausenum;
int nvars;
int nclauses;
int varnum;
int v;
assert(scip != NULL);
assert(file != NULL);
retcode = SCIP_OKAY;
linecount = 0;
/* read header */
SCIP_CALL( readCnfLine(scip, file, line, (int) sizeof(line), &linecount) );
if( *line != 'p' )
{
readError(scip, linecount, "problem declaration line expected");
return SCIP_READERROR;
}
if( sscanf(line, "p %8s %d %d", format, &nvars, &nclauses) != 3 )
{
readError(scip, linecount, "invalid problem declaration (must be 'p cnf <nvars> <nclauses>')");
return SCIP_READERROR;
}
if( strcmp(format, "cnf") != 0 )
{
(void) SCIPsnprintf(s, SCIP_MAXSTRLEN, "invalid format tag <%s> (must be 'cnf')", format);
readError(scip, linecount, s);
return SCIP_READERROR;
}
if( nvars <= 0 )
{
(void) SCIPsnprintf(s, SCIP_MAXSTRLEN, "invalid number of variables <%d> (must be positive)", nvars);
readError(scip, linecount, s);
return SCIP_READERROR;
}
if( nclauses <= 0 )
{
(void) SCIPsnprintf(s, SCIP_MAXSTRLEN, "invalid number of clauses <%d> (must be positive)", nclauses);
readError(scip, linecount, s);
return SCIP_READERROR;
}
/* get parameter values */
SCIP_CALL( SCIPgetBoolParam(scip, "reading/cnfreader/dynamicconss", &dynamicconss) );
SCIP_CALL( SCIPgetBoolParam(scip, "reading/cnfreader/dynamiccols", &dynamiccols) );
SCIP_CALL( SCIPgetBoolParam(scip, "reading/cnfreader/dynamicrows", &dynamicrows) );
SCIP_CALL( SCIPgetBoolParam(scip, "reading/cnfreader/useobj", &useobj) );
/* get temporary memory */
SCIP_CALL( SCIPallocBufferArray(scip, &vars, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &clausevars, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &varsign, nvars) );
/* create the variables */
for( v = 0; v < nvars; ++v )
{
(void) SCIPsnprintf(varname, SCIP_MAXSTRLEN, "x%d", v+1);
SCIP_CALL( SCIPcreateVar(scip, &vars[v], varname, 0.0, 1.0, 0.0, SCIP_VARTYPE_BINARY, !dynamiccols, dynamiccols,
NULL, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPaddVar(scip, vars[v]) );
varsign[v] = 0;
}
/* read clauses */
clausenum = 0;
clauselen = 0;
do
{
retcode = readCnfLine(scip, file, line, (int) sizeof(line), &linecount);
if( retcode != SCIP_OKAY )
goto TERMINATE;
if( *line != '\0' && *line != '%' )
{
tok = SCIPstrtok(line, " \f\n\r\t", &nexttok);
while( tok != NULL )
{
/* parse literal and check for errors */
if( sscanf(tok, "%d", &v) != 1 )
{
(void) SCIPsnprintf(s, SCIP_MAXSTRLEN, "invalid literal <%s>", tok);
readError(scip, linecount, s);
retcode = SCIP_READERROR;
goto TERMINATE;
}
/* interpret literal number: v == 0: end of clause, v < 0: negated literal, v > 0: positive literal */
if( v == 0 )
{
/* end of clause: construct clause and add it to SCIP */
if( clauselen == 0 )
readWarning(scip, linecount, "empty clause detected in line -- problem infeasible");
clausenum++;
(void) SCIPsnprintf(s, SCIP_MAXSTRLEN, "c%d", clausenum);
if( SCIPfindConshdlr(scip, "logicor") != NULL )
{
/* if the constraint handler logicor exit create a logicor constraint */
SCIP_CALL( SCIPcreateConsLogicor(scip, &cons, s, clauselen, clausevars,
!dynamicrows, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, dynamicconss, dynamicrows, FALSE) );
}
else if( SCIPfindConshdlr(scip, "setppc") != NULL )
{
/* if the constraint handler logicor does not exit but constraint
* handler setppc create a setppc constraint */
SCIP_CALL( SCIPcreateConsSetcover(scip, &cons, s, clauselen, clausevars,
!dynamicrows, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, dynamicconss, dynamicrows, FALSE) );
}
else
{
/* if none of the previous constraint handler exits create a linear
* constraint */
SCIP_Real* vals;
int i;
SCIP_CALL( SCIPallocBufferArray(scip, &vals, clauselen) );
for( i = 0; i < clauselen; ++i )
vals[i] = 1.0;
SCIP_CALL( SCIPcreateConsLinear(scip, &cons, s, clauselen, clausevars, vals, 1.0, SCIPinfinity(scip),
!dynamicrows, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, dynamicconss, dynamicrows, FALSE) );
SCIPfreeBufferArray(scip, &vals);
}
SCIP_CALL( SCIPaddCons(scip, cons) );
SCIP_CALL( SCIPreleaseCons(scip, &cons) );
clauselen = 0;
}
else if( v >= -nvars && v <= nvars )
{
if( clauselen >= nvars )
{
readError(scip, linecount, "too many literals in clause");
retcode = SCIP_READERROR;
goto TERMINATE;
}
/* add literal to clause */
varnum = ABS(v)-1;
if( v < 0 )
{
SCIP_CALL( SCIPgetNegatedVar(scip, vars[varnum], &clausevars[clauselen]) );
varsign[varnum]--;
}
else
{
clausevars[clauselen] = vars[varnum];
varsign[varnum]++;
}
clauselen++;
}
else
{
(void) SCIPsnprintf(s, SCIP_MAXSTRLEN, "invalid variable number <%d>", ABS(v));
readError(scip, linecount, s);
retcode = SCIP_READERROR;
goto TERMINATE;
}
/* get next token */
tok = SCIPstrtok(NULL, " \f\n\r\t", &nexttok);
}
}
}
while( *line != '\0' && *line != '%' );
/* check for additional literals */
if( clauselen > 0 )
{
SCIPwarningMessage(scip, "found %d additional literals after last clause\n", clauselen);
}
/* check number of clauses */
if( clausenum != nclauses )
{
SCIPwarningMessage(scip, "expected %d clauses, but found %d\n", nclauses, clausenum);
}
TERMINATE:
/* change objective values and release variables */
SCIP_CALL( SCIPsetObjsense(scip, SCIP_OBJSENSE_MAXIMIZE) );
if( useobj )
{
for( v = 0; v < nvars; ++v )
{
SCIP_CALL( SCIPchgVarObj(scip, vars[v], (SCIP_Real)varsign[v]) );
SCIP_CALL( SCIPreleaseVar(scip, &vars[v]) );
}
}
/* free temporary memory */
SCIPfreeBufferArray(scip, &varsign);
SCIPfreeBufferArray(scip, &clausevars);
SCIPfreeBufferArray(scip, &vars);
return retcode;
}
/** 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;
}