SCIP_VAR* scip_dvar(SCIP* scip, SCIP_VAR* a, SCIP_VAR* b)
{
assert(a != b);
static unsigned int n = 0;
SCIP_CONS* cons;
SCIP_VAR* rval;
char cons_id[64], rval_id[64];
SCIP_VAR* vars[3] = {b, a, NULL};
SCIP_Real coefs[3] = {1, -1, 1};
SCIP_Real oo = SCIPinfinity(scip);
sprintf(rval_id, "dvar%d", n);
sprintf(cons_id, "deq%d", n++);
sa(SCIPcreateVarBasic(scip, &rval, rval_id, -oo, oo, 0,
SCIP_VARTYPE_INTEGER));
sa(SCIPaddVar(scip, rval));
vars[2] = rval;
sa(SCIPcreateConsLinear
(scip, &cons, cons_id, 3, vars, coefs, 0, 0,
TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, FALSE, FALSE, FALSE, FALSE));
sa(SCIPaddCons(scip, cons));
return rval;
}
/** 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;
}
void SCIPSolver::add_in_constraint(LinearConstraint *con, double coef){
DBG("Creating a SCIP representation of a constriant%s\n", "");
double *weights = new double[con->_coefficients.size()];
SCIP_VAR** vars = new SCIP_VAR*[con->_variables.size()];
for(unsigned int i = 0; i < con->_variables.size(); ++i){
DBG("\tAdding variable to SCIP\n%s", "");
if(con->_variables[i]->_var == NULL){
SCIP_VAR* var_ptr;
SCIP_VARTYPE type;
if(con->_variables[i]->_continuous) type = SCIP_VARTYPE_CONTINUOUS;
else type = SCIP_VARTYPE_INTEGER;
SCIP_CALL_EXC(SCIPcreateVar(_scip, &var_ptr,
"SCIP_Var",
con->_variables[i]->_lower, // LB
con->_variables[i]->_upper, // UB
coef * con->_coefficients[i], // ective
type,
TRUE, FALSE, NULL, NULL, NULL, NULL, NULL) );
SCIP_CALL_EXC( SCIPaddVar(_scip, var_ptr) );
con->_variables[i]->_var = (void*) var_ptr;
vars[i] = var_ptr;
weights[i] = con->_coefficients[i];
} else {
vars[i] = (SCIP_VAR*) con->_variables[i]->_var;
weights[i] = con->_coefficients[i];
}
}
SCIP_CONS *scip_con;
SCIP_CALL_EXC( SCIPcreateConsLinear(_scip, &scip_con,"constraint",
con->_variables.size(), // # vars
vars, // variables
weights, // values
con->_lhs, // LHS
con->_rhs, // RHS
TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, FALSE, FALSE, FALSE, FALSE) );
SCIP_CALL_EXC( SCIPaddCons(_scip, scip_con) );
}
/* 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;
}
/** 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;
}
/** 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;
}
/* standard "main" method for mex interface */
void mexFunction(
int nlhs, /* number of expected outputs */
mxArray* plhs[], /* array of pointers to output arguments */
int nrhs, /* number of inputs */
const mxArray* prhs[] /* array of pointers to input arguments */
)
{
SCIP* scip;
SCIP_VAR** vars;
SCIP_Real* objs;
SCIP_Real* lhss;
SCIP_Real* rhss;
SCIP_Real* lbs;
SCIP_Real* ubs;
SCIP_Real* matrix;
SCIP_Real* bestsol;
SCIP_Real* objval;
char* vartypes;
char objsense[SCIP_MAXSTRLEN];
int nvars;
int nconss;
int stringsize;
int i;
if( SCIPmajorVersion() < 2 )
{
mexErrMsgTxt("SCIP versions less than 2.0 are not supported\n");
return;
}
/* initialize SCIP */
SCIP_CALL_ABORT( SCIPcreate(&scip) );
/* output SCIP information */
SCIPprintVersion(scip, NULL);
/* include default SCIP plugins */
SCIP_CALL_ABORT( SCIPincludeDefaultPlugins(scip) );
if( nlhs != 2 || nrhs != 8 )
mexErrMsgTxt("invalid number of parameters. Call as [bestsol, objval] = matscip(matrix, lhs, rhs, obj, lb, ub, vartype, objsense)\n");
if( mxIsSparse(prhs[0]) )
mexErrMsgTxt("sparse matrices are not supported yet"); /* ???????? of course this has to change */
/* get linear constraint coefficient matrix */
matrix = mxGetPr(prhs[0]);
if( matrix == NULL )
mexErrMsgTxt("matrix must not be NULL");
if( mxGetNumberOfDimensions(prhs[0]) != 2 )
mexErrMsgTxt("matrix must have exactly two dimensions");
/* get dimensions of matrix */
nconss = mxGetM(prhs[0]);
nvars = mxGetN(prhs[0]);
assert(nconss > 0);
assert(nvars > 0);
/* get left hand sides of linear constraints */
lhss = mxGetPr(prhs[1]);
if( mxGetM(prhs[1]) != nconss )
mexErrMsgTxt("dimension of left hand side vector does not match matrix dimension");
assert(lhss != NULL);
/* get right hand sides of linear constraints */
rhss = mxGetPr(prhs[2]);
if( mxGetM(prhs[2]) != nconss )
mexErrMsgTxt("dimension of right hand side vector does not match matrix dimension");
assert(rhss != NULL);
/* get objective coefficients */
objs = mxGetPr(prhs[3]);
if( mxGetM(prhs[3]) != nvars )
mexErrMsgTxt("dimension of objective coefficient vector does not match matrix dimension");
/* get lower bounds of variables */
lbs = mxGetPr(prhs[4]);
if( mxGetM(prhs[4]) != nvars )
mexErrMsgTxt("dimension of lower bound vector does not match matrix dimension");
/* get upper bounds of variables */
ubs = mxGetPr(prhs[5]);
if( mxGetM(prhs[5]) != nvars )
mexErrMsgTxt("dimension of upper bound vector does not match matrix dimension");
/* allocate memory for variable type characters */
SCIP_CALL_ABORT( SCIPallocMemoryArray(scip, &vartypes, nvars+1) );
/* get variable types */
if( mxGetString(prhs[6], vartypes, nvars+1) != 0 )
mexErrMsgTxt("Error when parsing variable types, maybe a wrong vector dimension?");
/* get objective sense */
stringsize = mxGetNumberOfElements(prhs[7]);
if( stringsize != 3 )
mexErrMsgTxt("objective sense must be a three character word: \"max\" or \"min\"");
if( mxGetString(prhs[7], objsense, stringsize+1) != 0)
mexErrMsgTxt("Error when parsing objective sense string");
if( strcmp(objsense,"max") != 0 && strcmp(objsense,"min") != 0 )
mexErrMsgTxt("objective sense must be either \"max\" or \"min\"");
/* get output parameters */
plhs[0] = mxCreateDoubleMatrix(nvars, 1, mxREAL);
bestsol = mxGetPr(plhs[0]);
plhs[1] = mxCreateDoubleScalar(mxREAL);
objval = mxGetPr(plhs[1]);
/* create SCIP problem */
SCIP_CALL_ABORT( SCIPcreateProb(scip, "mex_prob", NULL, NULL, NULL, NULL, NULL, NULL, NULL) );
/* allocate memory for variable array */
SCIP_CALL_ABORT( SCIPallocMemoryArray(scip, &vars, nvars) );
/* create variables */
for( i = 0; i < nvars; ++i)
{
SCIP_VARTYPE vartype;
char varname[SCIP_MAXSTRLEN];
/* convert vartype character to SCIP vartype */
if( vartypes[i] == 'i' )
vartype = SCIP_VARTYPE_INTEGER;
else if( vartypes[i] == 'b' )
vartype = SCIP_VARTYPE_BINARY;
else if( vartypes[i] == 'c' )
vartype = SCIP_VARTYPE_CONTINUOUS;
else
mexErrMsgTxt("unkown variable type");
/* variables get canonic names x_i */
(void) SCIPsnprintf(varname, SCIP_MAXSTRLEN, "x_%d", i);
/* create variable object and add it to SCIP */
SCIP_CALL_ABORT( SCIPcreateVar(scip, &vars[i], varname, lbs[i], ubs[i], objs[i],
vartype, TRUE, FALSE, NULL, NULL, NULL, NULL, NULL) );
assert(vars[i] != NULL);
SCIP_CALL_ABORT( SCIPaddVar(scip, vars[i]) );
}
/* create linear constraints */
for( i = 0; i < nconss; ++i )
{
SCIP_CONS* cons;
char consname[SCIP_MAXSTRLEN];
int j;
/* constraints get canonic names cons_i */
(void) SCIPsnprintf(consname, SCIP_MAXSTRLEN, "cons_%d", i);
/* create empty linear constraint */
SCIP_CALL_ABORT( SCIPcreateConsLinear(scip, &cons, consname, 0, NULL, NULL, lhss[i], rhss[i],
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE) );
/* add non-zero coefficients to linear constraint */
for( j = 0; j < nvars; ++j )
{
if( !SCIPisFeasZero(scip, matrix[i+j*nconss]) )
{
SCIP_CALL_ABORT( SCIPaddCoefLinear(scip, cons, vars[j], matrix[i+j*nconss]) );
}
}
/* add constraint to SCIP and release it */
SCIP_CALL_ABORT( SCIPaddCons(scip, cons) );
SCIP_CALL_ABORT( SCIPreleaseCons(scip, &cons) );
}
/* set objective sense in SCIP */
if( strcmp(objsense,"max") == 0)
{
SCIP_CALL_ABORT( SCIPsetObjsense(scip, SCIP_OBJSENSE_MAXIMIZE) );
}
else if( strcmp(objsense,"min") == 0)
{
SCIP_CALL_ABORT( SCIPsetObjsense(scip, SCIP_OBJSENSE_MINIMIZE) );
}
else
/* this should have been caught earlier when parsing objsense */
mexErrMsgTxt("unkown objective sense");
/* solve SCIP problem */
SCIP_CALL_ABORT( SCIPsolve(scip) );
/* if SCIP found a solution, pass it back into MATLAB output parameters */
if( SCIPgetNSols > 0 )
{
SCIP_SOL* scipbestsol;
/* get incumbent solution vector */
scipbestsol = SCIPgetBestSol(scip);
assert(scipbestsol != NULL);
/* get objective value of incumbent solution */
*objval = SCIPgetSolOrigObj(scip, scipbestsol);
assert(!SCIPisInfinity(scip, REALABS(*objval)));
/* copy solution values into output vector */
for( i = 0; i < nvars; ++i )
bestsol[i] = SCIPgetSolVal(scip,scipbestsol,vars[i]);
}
/* release variables */
for( i = 0; i < nvars; ++i )
{
SCIP_CALL_ABORT( SCIPreleaseVar(scip, &vars[i]) );
}
/* free memory for variable arrays */
SCIPfreeMemoryArray(scip, &vartypes);
SCIPfreeMemoryArray(scip, &vars);
/* deinitialize SCIP */
SCIP_CALL_ABORT( SCIPfree(&scip) );
/* check for memory leaks */
BMScheckEmptyMemory();
return;
}
/** read fixed variable */
static
SCIP_RETCODE getFixedVariable(
SCIP* scip, /**< SCIP data structure */
CIPINPUT* cipinput /**< CIP parsing data */
)
{
SCIP_Bool success;
SCIP_VAR* var;
char* buf;
char* endptr;
char name[SCIP_MAXSTRLEN];
buf = cipinput->strbuf;
if( strncmp(buf, "CONSTRAINTS", 11) == 0 )
cipinput->section = CIP_CONSTRAINTS;
else if( strncmp(buf, "END", 3) == 0 )
cipinput->section = CIP_END;
if( cipinput->section != CIP_FIXEDVARS )
return SCIP_OKAY;
SCIPdebugMessage("parse fixed variable\n");
/* parse the variable */
SCIP_CALL( SCIPparseVar(scip, &var, buf, TRUE, FALSE, NULL, NULL, NULL, NULL, NULL, &endptr, &success) );
if( !success )
{
SCIPerrorMessage("syntax error in variable information (line: %d):\n%s\n", cipinput->linenumber, cipinput->strbuf);
cipinput->haserror = TRUE;
return SCIP_OKAY;
}
/* skip intermediate stuff */
buf = endptr;
while ( *buf != '\0' && (*buf == ' ' || *buf == ',') )
++buf;
/* check whether variable is fixed */
if ( strncmp(buf, "fixed:", 6) == 0 )
{
SCIP_CALL( SCIPaddVar(scip, var) );
SCIPdebug( SCIP_CALL( SCIPprintVar(scip, var, NULL) ) );
}
else if ( strncmp(buf, "negated:", 8) == 0 )
{
SCIP_CONS* lincons;
SCIP_VAR* negvar;
SCIP_Real vals[2];
SCIP_VAR* vars[2];
buf += 8;
/* we can just parse the next variable (ignoring all other information in between) */
SCIP_CALL( SCIPparseVarName(scip, buf, &negvar, &endptr) );
if ( negvar == NULL )
{
SCIPerrorMessage("could not parse negated variable (line: %d):\n%s\n", cipinput->linenumber, cipinput->strbuf);
cipinput->haserror = TRUE;
return SCIP_OKAY;
}
assert(SCIPvarIsBinary(var));
assert(SCIPvarIsBinary(negvar));
SCIP_CALL( SCIPaddVar(scip, var) );
SCIPdebugMessage("creating negated variable <%s> (of <%s>) ...\n", SCIPvarGetName(var), SCIPvarGetName(negvar) );
SCIPdebug( SCIP_CALL( SCIPprintVar(scip, var, NULL) ) );
/* add linear constraint for negation */
(void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "neg_%s", SCIPvarGetName(var) );
vars[0] = var;
vars[1] = negvar;
vals[0] = 1.0;
vals[1] = 1.0;
SCIPdebugMessage("coupling constraint:\n");
SCIP_CALL( SCIPcreateConsLinear(scip, &lincons, name, 2, vars, vals, 1.0, 1.0, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, FALSE) );
SCIPdebugPrintCons(scip, lincons, NULL);
SCIP_CALL( SCIPaddCons(scip, lincons) );
SCIP_CALL( SCIPreleaseCons(scip, &lincons) );
}
else if ( strncmp(buf, "aggregated:", 11) == 0 )
{
/* handle (multi-)aggregated variables */
SCIP_CONS* lincons;
SCIP_Real* vals;
SCIP_VAR** vars;
SCIP_Real rhs = 0.0;
const char* str;
int nvarssize = 20;
int requsize;
int nvars;
buf += 11;
SCIPdebugMessage("parsing aggregated variable <%s> ...\n", SCIPvarGetName(var));
/* first parse constant */
if ( ! SCIPstrToRealValue(buf, &rhs, &endptr) )
{
SCIPerrorMessage("expected constant when aggregated variable information (line: %d):\n%s\n", cipinput->linenumber, buf);
cipinput->haserror = TRUE;
return SCIP_OKAY;
}
/* check whether constant is 0.0 */
str = endptr;
while ( *str != '\0' && isspace(*str) )
++str;
/* if next char is '<' we found a variable -> constant is 0 */
if ( *str != '<' )
{
SCIPdebugMessage("constant: %f\n", rhs);
buf = endptr;
}
else
{
/* otherwise keep buf */
rhs = 0.0;
}
/* initialize buffers for storing the variables and values */
SCIP_CALL( SCIPallocBufferArray(scip, &vars, nvarssize) );
SCIP_CALL( SCIPallocBufferArray(scip, &vals, nvarssize) );
vars[0] = var;
vals[0] = -1.0;
--nvarssize;
/* parse linear sum to get variables and coefficients */
SCIP_CALL( SCIPparseVarsLinearsum(scip, buf, &(vars[1]), &(vals[1]), &nvars, nvarssize, &requsize, &endptr, &success) );
if ( success && requsize > nvarssize )
{
/* realloc buffers and try again */
nvarssize = requsize;
SCIP_CALL( SCIPreallocBufferArray(scip, &vars, nvarssize + 1) );
SCIP_CALL( SCIPreallocBufferArray(scip, &vals, nvarssize + 1) );
SCIP_CALL( SCIPparseVarsLinearsum(scip, buf, &(vars[1]), &(vals[1]), &nvars, nvarssize, &requsize, &endptr, &success) );
assert( ! success || requsize <= nvarssize); /* if successful, then should have had enough space now */
}
if( success )
{
/* add aggregated variable */
SCIP_CALL( SCIPaddVar(scip, var) );
/* special handling of variables that seem to be slack variables of indicator constraints */
str = SCIPvarGetName(var);
if ( strncmp(str, "indslack", 8) == 0 )
{
(void) strcpy(name, "indlin");
(void) strncat(name, str+8, SCIP_MAXSTRLEN-7);
}
else if ( strncmp(str, "t_indslack", 10) == 0 )
{
(void) strcpy(name, "indlin");
(void) strncat(name, str+10, SCIP_MAXSTRLEN-7);
}
else
(void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "%s", SCIPvarGetName(var) );
/* add linear constraint for (multi-)aggregation */
SCIPdebugMessage("coupling constraint:\n");
SCIP_CALL( SCIPcreateConsLinear(scip, &lincons, name, nvars + 1, vars, vals, -rhs, -rhs, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, FALSE) );
SCIPdebugPrintCons(scip, lincons, NULL);
SCIP_CALL( SCIPaddCons(scip, lincons) );
SCIP_CALL( SCIPreleaseCons(scip, &lincons) );
}
else
{
SCIPwarningMessage(scip, "Could not read (multi-)aggregated variable <%s>: dependent variables unkown - consider changing the order (line: %d):\n%s\n",
SCIPvarGetName(var), cipinput->linenumber, buf);
}
SCIPfreeBufferArray(scip, &vals);
SCIPfreeBufferArray(scip, &vars);
}
else
{
SCIPerrorMessage("unknown section when parsing variables (line: %d):\n%s\n", cipinput->linenumber, buf);
cipinput->haserror = TRUE;
return SCIP_OKAY;
}
SCIP_CALL( SCIPreleaseVar(scip, &var) );
return SCIP_OKAY;
}
/** creates a subproblem for subscip by fixing a number of variables */
static
SCIP_RETCODE createSubproblem(
SCIP* scip, /**< original SCIP data structure */
SCIP* subscip, /**< SCIP data structure for the subproblem */
SCIP_VAR** subvars, /**< the variables of the subproblem */
SCIP_Real minfixingrate, /**< percentage of integer variables that have to be fixed */
SCIP_Bool binarybounds, /**< should general integers get binary bounds [floor(.),ceil(.)] ? */
SCIP_Bool uselprows, /**< should subproblem be created out of the rows in the LP rows? */
SCIP_Bool* success /**< pointer to store whether the problem was created successfully */
)
{
SCIP_VAR** vars; /* original SCIP variables */
SCIP_Real fixingrate;
int nvars;
int nbinvars;
int nintvars;
int i;
int fixingcounter;
assert(scip != NULL);
assert(subscip != NULL);
assert(subvars != NULL);
assert(0.0 <= minfixingrate && minfixingrate <= 1.0);
/* get required variable data */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
fixingcounter = 0;
/* change bounds of variables of the subproblem */
for( i = 0; i < nbinvars + nintvars; i++ )
{
SCIP_Real lpsolval;
SCIP_Real lb;
SCIP_Real ub;
/* get the current LP solution for each variable */
lpsolval = SCIPgetRelaxSolVal(scip, vars[i]);
if( SCIPisFeasIntegral(scip, lpsolval) )
{
/* fix variables to current LP solution if it is integral,
* use exact integral value, if the variable is only integral within numerical tolerances
*/
lb = SCIPfloor(scip, lpsolval+0.5);
ub = lb;
fixingcounter++;
}
else if( binarybounds )
{
/* if the sub problem should be a binary problem, change the bounds to nearest integers */
lb = SCIPfeasFloor(scip,lpsolval);
ub = SCIPfeasCeil(scip,lpsolval);
}
else
{
/* otherwise just copy bounds */
lb = SCIPvarGetLbGlobal(vars[i]);
ub = SCIPvarGetUbGlobal(vars[i]);
}
/* perform the bound change */
SCIP_CALL( SCIPchgVarLbGlobal(subscip, subvars[i], lb) );
SCIP_CALL( SCIPchgVarUbGlobal(subscip, subvars[i], ub) );
}
/* abort, if all integer variables were fixed (which should not happen for MIP) */
if( fixingcounter == nbinvars + nintvars )
{
*success = FALSE;
return SCIP_OKAY;
}
else
fixingrate = fixingcounter / (SCIP_Real)(MAX(nbinvars + nintvars, 1));
SCIPdebugMessage("fixing rate: %g = %d of %d\n", fixingrate, fixingcounter, nbinvars + nintvars);
/* abort, if the amount of fixed variables is insufficient */
if( fixingrate < minfixingrate )
{
*success = FALSE;
return SCIP_OKAY;
}
if( uselprows )
{
SCIP_ROW** rows; /* original scip rows */
int nrows;
/* get the rows and their number */
SCIP_CALL( SCIPgetLPRowsData(scip, &rows, &nrows) );
/* copy all rows to linear constraints */
for( i = 0; i < nrows; i++ )
{
SCIP_CONS* cons;
SCIP_VAR** consvars;
SCIP_COL** cols;
SCIP_Real constant;
SCIP_Real lhs;
SCIP_Real rhs;
SCIP_Real* vals;
int nnonz;
int j;
/* ignore rows that are only locally valid */
if( SCIProwIsLocal(rows[i]) )
continue;
/* get the row's data */
constant = SCIProwGetConstant(rows[i]);
lhs = SCIProwGetLhs(rows[i]) - constant;
rhs = SCIProwGetRhs(rows[i]) - constant;
vals = SCIProwGetVals(rows[i]);
nnonz = SCIProwGetNNonz(rows[i]);
cols = SCIProwGetCols(rows[i]);
assert( lhs <= rhs );
/* allocate memory array to be filled with the corresponding subproblem variables */
SCIP_CALL( SCIPallocBufferArray(subscip, &consvars, nnonz) );
for( j = 0; j < nnonz; j++ )
consvars[j] = subvars[SCIPvarGetProbindex(SCIPcolGetVar(cols[j]))];
/* create a new linear constraint and add it to the subproblem */
SCIP_CALL( SCIPcreateConsLinear(subscip, &cons, SCIProwGetName(rows[i]), nnonz, consvars, vals, lhs, rhs,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
/* free temporary memory */
SCIPfreeBufferArray(subscip, &consvars);
}
}
*success = TRUE;
return SCIP_OKAY;
}
/** create the extra constraint of local branching and add it to subscip */
static
SCIP_RETCODE addLocalBranchingConstraint(
SCIP* scip, /**< SCIP data structure of the original problem */
SCIP* subscip, /**< SCIP data structure of the subproblem */
SCIP_VAR** subvars, /**< variables of the subproblem */
SCIP_HEURDATA* heurdata /**< heuristic's data structure */
)
{
SCIP_CONS* cons; /* local branching constraint to create */
SCIP_VAR** consvars;
SCIP_VAR** vars;
SCIP_SOL* bestsol;
int nbinvars;
int i;
SCIP_Real lhs;
SCIP_Real rhs;
SCIP_Real* consvals;
char consname[SCIP_MAXSTRLEN];
(void) SCIPsnprintf(consname, SCIP_MAXSTRLEN, "%s_localbranchcons", SCIPgetProbName(scip));
/* get the data of the variables and the best solution */
SCIP_CALL( SCIPgetVarsData(scip, &vars, NULL, &nbinvars, NULL, NULL, NULL) );
bestsol = SCIPgetBestSol(scip);
assert( bestsol != NULL );
/* memory allocation */
SCIP_CALL( SCIPallocBufferArray(scip, &consvars, nbinvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &consvals, nbinvars) );
/* set initial left and right hand sides of local branching constraint */
lhs = (SCIP_Real)heurdata->emptyneighborhoodsize + 1.0;
rhs = (SCIP_Real)heurdata->curneighborhoodsize;
/* create the distance (to incumbent) function of the binary variables */
for( i = 0; i < nbinvars; i++ )
{
SCIP_Real solval;
solval = SCIPgetSolVal(scip, bestsol, vars[i]);
assert( SCIPisFeasIntegral(scip,solval) );
/* is variable i part of the binary support of bestsol? */
if( SCIPisFeasEQ(scip,solval,1.0) )
{
consvals[i] = -1.0;
rhs -= 1.0;
lhs -= 1.0;
}
else
consvals[i] = 1.0;
consvars[i] = subvars[i];
assert( SCIPvarGetType(consvars[i]) == SCIP_VARTYPE_BINARY );
}
/* creates localbranching constraint and adds it to subscip */
SCIP_CALL( SCIPcreateConsLinear(subscip, &cons, consname, nbinvars, consvars, consvals,
lhs, rhs, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
/* free local memory */
SCIPfreeBufferArray(scip, &consvals);
SCIPfreeBufferArray(scip, &consvars);
return SCIP_OKAY;
}
/** branching execution method for fractional LP solutions */
static
SCIP_DECL_BRANCHEXECLP(branchExeclpStp)
{ /*lint --e{715}*/
SCIP_PROBDATA* probdata;
SCIP_CONS* consin;
SCIP_CONS* consout;
SCIP_NODE* vertexin;
SCIP_NODE* vertexout;
SCIP_VAR** edgevars;
SCIP_Real estimatein;
SCIP_Real estimateout;
GRAPH* g;
int e;
int branchvertex;
assert(branchrule != NULL);
assert(strcmp(SCIPbranchruleGetName(branchrule), BRANCHRULE_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
SCIPdebugMessage("Execlp method of Stp branching\n ");
estimatein = SCIPgetUpperbound(scip);
estimateout = SCIPgetUpperbound(scip);
*result = SCIP_DIDNOTRUN;
/* get problem data */
probdata = SCIPgetProbData(scip);
assert(probdata != NULL);
/* get graph */
g = SCIPprobdataGetGraph(probdata);
assert(g != NULL);
/* get vertex to branch on */
SCIP_CALL( selectBranchingVertex(scip, &branchvertex) );
if( branchvertex == UNKNOWN )
{
SCIPdebugMessage("Branching did not run \n");
return SCIP_OKAY;
}
edgevars = SCIPprobdataGetEdgeVars(scip);
/* create constraints */
SCIP_CALL( SCIPcreateConsLinear(scip, &consin, "consin", 0,
NULL, NULL, 1.0, 1.0,
TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE) );
SCIP_CALL( SCIPcreateConsLinear(scip, &consout, "consout", 0,
NULL, NULL, 0.0, 0.0,
TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE) );
for( e = g->inpbeg[branchvertex]; e != EAT_LAST; e = g->ieat[e] )
{
SCIP_CALL( SCIPaddCoefLinear(scip, consin, edgevars[e], 1.0) );
SCIP_CALL( SCIPaddCoefLinear(scip, consout, edgevars[e], 1.0) );
SCIP_CALL( SCIPaddCoefLinear(scip, consout, edgevars[flipedge(e)], 1.0) );
}
/* create the child nodes */
SCIP_CALL( SCIPcreateChild(scip, &vertexin, 1.0, estimatein) );
SCIP_CALL( SCIPcreateChild(scip, &vertexout, 1.0, estimateout) );
assert(vertexin != NULL);
assert(vertexout != NULL);
SCIP_CALL( SCIPaddConsNode(scip, vertexin, consin, NULL) );
SCIP_CALL( SCIPaddConsNode(scip, vertexout, consout, NULL) );
/* relase constraints */
SCIP_CALL( SCIPreleaseCons(scip, &consin) );
SCIP_CALL( SCIPreleaseCons(scip, &consout) );
SCIPdebugMessage("Branched on stp vertex %d \n", branchvertex);
*result = SCIP_BRANCHED;
return SCIP_OKAY;
}
