/** destructor of constraint handler to free constraint handler data (called when SCIP is exiting) */
static
SCIP_DECL_CONSFREE(consFreeOrigbranch)
{ /*lint --e{715}*/
SCIP_CONSHDLRDATA* conshdlrData;
assert(scip != NULL);
assert(conshdlr != NULL);
assert(strcmp(SCIPconshdlrGetName(conshdlr), CONSHDLR_NAME) == 0);
conshdlrData = SCIPconshdlrGetData(conshdlr);
assert(conshdlrData != NULL);
SCIPdebugMessage("freeing branch orig constraint handler\n");
/* free constraint handler storage */
assert(conshdlrData->stack == NULL);
if( conshdlrData->rootcons != NULL )
{
SCIP_CALL( SCIPreleaseCons(scip, &conshdlrData->rootcons) );
}
SCIPfreeMemory(scip, &conshdlrData);
return SCIP_OKAY;
}
/** frees the memory of the given problem data */
static
SCIP_RETCODE probdataFree(
SCIP* scip, /**< SCIP data structure */
SCIP_PROBDATA** probdata /**< pointer to problem data */
)
{
int i;
assert(scip != NULL);
assert(probdata != NULL);
/* release all variables */
for( i = 0; i < (*probdata)->nvars; ++i )
{
SCIP_CALL( SCIPreleaseVar(scip, &(*probdata)->vars[i]) );
}
/* release all constraints */
for( i = 0; i < (*probdata)->nitems; ++i )
{
SCIP_CALL( SCIPreleaseCons(scip, &(*probdata)->conss[i]) );
}
/* free memory of arrays */
SCIPfreeMemoryArray(scip, &(*probdata)->vars);
SCIPfreeMemoryArray(scip, &(*probdata)->conss);
SCIPfreeMemoryArray(scip, &(*probdata)->weights);
SCIPfreeMemoryArray(scip, &(*probdata)->ids);
/* free probdata */
SCIPfreeMemory(scip, probdata);
return SCIP_OKAY;
}
/** initialization method of variable pricer (called after problem was transformed) */
static
SCIP_DECL_PRICERINIT(pricerInitBinpacking)
{ /*lint --e{715}*/
SCIP_PRICERDATA* pricerdata;
SCIP_CONS* cons;
int c;
assert(scip != NULL);
assert(pricer != NULL);
pricerdata = SCIPpricerGetData(pricer);
assert(pricerdata != NULL);
/* get transformed constraints */
for( c = 0; c < pricerdata->nitems; ++c )
{
cons = pricerdata->conss[c];
/* release original constraint */
SCIP_CALL( SCIPreleaseCons(scip, &pricerdata->conss[c]) );
/* get transformed constraint */
SCIP_CALL( SCIPgetTransformedCons(scip, cons, &pricerdata->conss[c]) );
/* capture transformed constraint */
SCIP_CALL( SCIPcaptureCons(scip, pricerdata->conss[c]) );
}
return SCIP_OKAY;
}
/** solving process initialization method of constraint handler (called when branch and bound process is about to begin) */
static
SCIP_DECL_CONSINITSOL(consInitsolOrigbranch)
{ /*lint --e{715}*/
SCIP_CONSHDLRDATA* conshdlrData;
assert(scip != NULL);
assert(conshdlr != NULL);
assert(strcmp(SCIPconshdlrGetName(conshdlr), CONSHDLR_NAME) == 0);
conshdlrData = SCIPconshdlrGetData(conshdlr);
assert(conshdlrData != NULL);
/* prepare stack */
SCIP_CALL( SCIPallocMemoryArray(scip, &conshdlrData->stack, conshdlrData->maxstacksize) );
assert( conshdlrData->nstack >= 0 );
/* check consistency */
if( conshdlrData->rootcons != NULL )
{
SCIP_CALL( SCIPreleaseCons(scip, &conshdlrData->rootcons) );
conshdlrData->rootcons = NULL;
--(conshdlrData->nstack);
}
GCGconsOrigbranchCheckConsistency(scip);
return SCIP_OKAY;
}
/** deletes the transformed problem */
static
SCIP_DECL_PROBDELTRANS(probdeltransColoring)
{
int i;
assert(scip != NULL);
assert(probdata != NULL);
/* relese constraints and free array for constraints */
for ( i = 0; i < tcliqueGetNNodes((*probdata)->graph); i++)
{
SCIP_CALL( SCIPreleaseCons(scip, &((*probdata)->constraints[i])) );
}
SCIPfreeMemoryArray(scip, &((*probdata)->constraints));
/* free the arrays for the stable sets and relese the related variables */
for ( i = (*probdata)->nstablesets-1; i >= 0; i-- )
{
SCIPfreeBlockMemoryArray(scip, &((*probdata)->stablesets[i]), (*probdata)->stablesetlengths[i]); /*lint !e866*/
SCIP_CALL( SCIPreleaseVar(scip, &((*probdata)->stablesetvars[i])) );
}
SCIPfreeMemoryArray(scip, &((*probdata)->new2oldnode));
SCIPfreeMemoryArray(scip, &((*probdata)->deletednodes));
SCIPfreeMemoryArray(scip, &((*probdata)->stablesetvars));
SCIPfreeMemoryArray(scip, &((*probdata)->stablesetlengths));
SCIPfreeMemoryArray(scip, &((*probdata)->stablesets));
tcliqueFree(&(*probdata)->graph);
SCIPfreeMemory(scip, probdata);
return SCIP_OKAY;
}
/** 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;
}
/** presolving method of constraint handler */
static
SCIP_DECL_CONSPRESOL(consPresolConjunction)
{ /*lint --e{715}*/
SCIP_CONSDATA* consdata;
int c;
int i;
assert(result != NULL);
*result = SCIP_DIDNOTFIND;
/* all constraints in a conjunction constraint of the global problem can be added directly to the problem and
* removed from the conjunction constraint;
* an unmodifiable conjunction constraint can be deleted
*/
for( c = 0; c < nconss; ++c )
{
consdata = SCIPconsGetData(conss[c]);
assert(consdata != NULL);
/* add all inactive constraints to the global problem */
for( i = 0; i < consdata->nconss; ++i )
{
/* update check flag for sub constraints when upgrade takes place */
if( SCIPconsIsChecked(conss[c]) )
{
/* make sure, the constraint is checked for feasibility */
SCIP_CALL( SCIPsetConsChecked(scip, consdata->conss[i], TRUE) );
}
/* add constraint, if it is not active yet */
if( !SCIPconsIsActive(consdata->conss[i]) )
{
SCIPdebugMessage("adding constraint <%s> from add conjunction <%s>\n",
SCIPconsGetName(consdata->conss[i]), SCIPconsGetName(conss[c]));
SCIP_CALL( SCIPaddCons(scip, consdata->conss[i]) );
*result = SCIP_SUCCESS;
}
/* release constraint because it will be removed from the conjunction constraint */
SCIP_CALL( SCIPreleaseCons(scip, &(consdata->conss[i])) );
}
/* all constraints where removed, so we need to clear the array */
consdata->nconss = 0;
/* delete conjunction constraint, if it is unmodifiable */
if( !SCIPconsIsModifiable(conss[c]) )
{
SCIP_CALL( SCIPdelCons(scip, conss[c]) );
}
}
return SCIP_OKAY;
}
/** exit method of constraint handler (called before problem is free transformed) */
static
SCIP_DECL_CONSEXIT(consExitOrigbranch)
{ /*lint --e{715}*/
SCIP_CONSHDLRDATA* conshdlrdata;
assert(conshdlr != NULL);
assert(scip != NULL);
conshdlrdata = SCIPconshdlrGetData(conshdlr);
assert(conshdlrdata != NULL);
SCIPdebugMessage("exiting transformed branch orig constraint handler\n");
if( conshdlrdata->rootcons != NULL )
{
SCIP_CALL( SCIPreleaseCons(scip, &conshdlrdata->rootcons) );
conshdlrdata->rootcons = NULL;
}
return SCIP_OKAY;
}
/** presolving method of constraint handler */
static
SCIP_DECL_CONSPRESOL(consPresolDisjunction)
{ /*lint --e{715}*/
SCIP_CONSDATA* consdata;
int oldndelconss;
int c;
assert(result != NULL);
*result = SCIP_DIDNOTFIND;
oldndelconss = *ndelconss;
/* all disjunction constraints with one constraint can be replaced with that corresponding constraint */
for( c = 0; c < nconss; ++c )
{
consdata = SCIPconsGetData(conss[c]);
assert(consdata != NULL);
if( !SCIPconsIsModifiable(conss[c]) && consdata->nconss == 1 )
{
/* add constraint to the problem */
if( !SCIPconsIsActive(consdata->conss[0]) )
{
SCIP_CALL( SCIPaddCons(scip, consdata->conss[0]) );
/* release constraint from the disjunction constraint */
SCIP_CALL( SCIPreleaseCons(scip, &consdata->conss[0]) );
}
/* remove disjunction constraint */
SCIP_CALL( SCIPdelCons(scip, conss[0]) );
*result = SCIP_SUCCESS;
}
/* propagate constraint */
SCIP_CALL( propagateCons(scip, conss[c], ndelconss) );
}
if( *ndelconss > oldndelconss )
*result = SCIP_SUCCESS;
return SCIP_OKAY;
}
/** solving process deinitialization method of variable pricer (called before branch and bound process data is freed) */
static
SCIP_DECL_PRICEREXITSOL(pricerExitsolBinpacking) {
SCIP_PRICERDATA* pricerdata;
int c;
assert(scip != NULL);
assert(pricer != NULL);
pricerdata = SCIPpricerGetData(pricer);
assert(pricerdata != NULL);
/* get release constraints */
for (c = 0; c < pricerdata->nitems + pricerdata->nbins; ++c) {
/* release constraint */
SCIP_CALL(SCIPreleaseCons(scip, &(pricerdata->conss[c])));
}
return SCIP_OKAY;
}
/** create linear ordering problem model */
SCIP_RETCODE LOPgenerateModel(
SCIP* scip /**< SCIP data structure */
)
{
SCIP_PROBDATA* probdata;
SCIP_CONS* cons;
int i, j;
/* get problem data */
probdata = SCIPgetProbData(scip);
assert( probdata != NULL );
/* generate variables */
SCIP_CALL( SCIPallocMemoryArray(scip, &probdata->vars, probdata->n) );
for (i = 0; i < probdata->n; ++i)
{
SCIP_CALL( SCIPallocMemoryArray(scip, &(probdata->vars[i]), probdata->n) ); /*lint !e866*/
for (j = 0; j < probdata->n; ++j)
{
if (j != i)
{
char s[SCIP_MAXSTRLEN];
(void) SCIPsnprintf(s, SCIP_MAXSTRLEN, "x#%d#%d", i, j);
SCIP_CALL( SCIPcreateVar(scip, &(probdata->vars[i][j]), s, 0.0, 1.0, probdata->W[i][j], SCIP_VARTYPE_BINARY,
TRUE, FALSE, NULL, NULL, NULL, NULL, NULL));
SCIP_CALL( SCIPaddVar(scip, probdata->vars[i][j]) );
}
else
probdata->vars[i][j] = NULL;
}
}
/* generate linear ordering constraint */
SCIP_CALL( SCIPcreateConsLinearOrdering(scip, &cons, "LOP", probdata->n, probdata->vars, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE,
FALSE, FALSE, FALSE, FALSE));
SCIP_CALL( SCIPaddCons(scip, cons) );
SCIP_CALL( SCIPreleaseCons(scip, &cons) );
/* set maximization */
SCIP_CALL( SCIPsetObjsense(scip, SCIP_OBJSENSE_MAXIMIZE) );
return SCIP_OKAY;
}
/** frees constraint data and releases all constraints in conjunction */
static
SCIP_RETCODE consdataFree(
SCIP* scip, /**< SCIP data structure */
SCIP_CONSDATA** consdata /**< pointer to constraint data */
)
{
int c;
assert(consdata != NULL);
assert(*consdata != NULL);
/* release constraints */
for( c = 0; c < (*consdata)->nconss; ++c )
{
SCIP_CALL( SCIPreleaseCons(scip, &(*consdata)->conss[c]) );
}
/* free memory */
SCIPfreeBlockMemoryArrayNull(scip, &(*consdata)->conss, (*consdata)->consssize);
SCIPfreeBlockMemory(scip, consdata);
return SCIP_OKAY;
}
static
SCIP_DECL_PROBDELORIG(probdelorigColoring)
{
int i;
assert(probdata != NULL);
assert(*probdata != NULL);
SCIPfreeMemoryArray(scip, &((*probdata)->new2oldnode));
SCIPfreeMemoryArray(scip, &((*probdata)->deletednodes));
for ( i = (*probdata)->nstablesets-1; i >= 0; i-- )
{
SCIPfreeBlockMemoryArray(scip, &((*probdata)->stablesets[i]), (*probdata)->stablesetlengths[i]); /*lint !e866*/
SCIP_CALL( SCIPreleaseVar(scip, &((*probdata)->stablesetvars[i])) );
}
SCIPfreeMemoryArray(scip, &((*probdata)->stablesetvars));
SCIPfreeMemoryArray(scip, &((*probdata)->stablesetlengths));
SCIPfreeMemoryArray(scip, &((*probdata)->stablesets));
/* release Constraints */
for ( i = 0; i < tcliqueGetNNodes((*probdata)->graph); i++ )
{
SCIP_CALL( SCIPreleaseCons(scip, &((*probdata)->constraints[i])) );
}
SCIPfreeMemoryArray(scip, &((*probdata)->constraints));
/* free memory used for graph */
tcliqueFree(&((*probdata)->graph));
tcliqueFree(&((*probdata)->oldgraph));
/* free probdata */
SCIPfreeMemory(scip, probdata);
return SCIP_OKAY;
}
/** read constraint */
static
SCIP_RETCODE getConstraint(
SCIP* scip, /**< SCIP data structure */
CIPINPUT* cipinput, /**< CIP parsing data */
SCIP_Bool initial, /**< should the LP relaxation of constraint be in the initial LP?
* Usually set to TRUE. Set to FALSE for 'lazy constraints'. */
SCIP_Bool dynamic, /**< Is constraint subject to aging?
* Usually set to FALSE. Set to TRUE for own cuts which
* are separated as constraints. */
SCIP_Bool 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'. */
)
{
SCIP_CONS* cons;
char* buf;
char* copybuf;
SCIP_RETCODE retcode;
SCIP_Bool separate;
SCIP_Bool enforce;
SCIP_Bool check;
SCIP_Bool propagate;
SCIP_Bool local;
SCIP_Bool modifiable;
SCIP_Bool success;
int len;
buf = cipinput->strbuf;
if( strncmp(buf, "END", 3) == 0 )
{
cipinput->section = CIP_END;
return SCIP_OKAY;
}
SCIPdebugMessage("parse constraints in line %d\n", cipinput->linenumber);
separate = TRUE;
enforce = TRUE;
check = TRUE;
propagate = TRUE;
local = FALSE;
modifiable = FALSE;
/* get length of line and check for correct ending of constraint line */
len = (int)strlen(buf);
if( len < 1 )
{
SCIPerrorMessage("syntax error: expected constraint in line %d.\n", cipinput->linenumber);
cipinput->haserror = TRUE;
return SCIP_OKAY;
}
if ( buf[len - 1] != ';' )
{
SCIPerrorMessage("syntax error: line has to end with ';' (line: %d)\n", cipinput->linenumber);
cipinput->haserror = TRUE;
return SCIP_OKAY;
}
/* copy buffer for working purpose */
SCIP_CALL( SCIPduplicateMemoryArray(scip, ©buf, buf, len) );
copybuf[len - 1] = '\0';
/* parse the constraint */
retcode = SCIPparseCons(scip, &cons, copybuf,
initial, separate, enforce, check, propagate, local, modifiable, dynamic, removable, FALSE, &success);
/* free temporary buffer */
SCIPfreeMemoryArray(scip, ©buf);
SCIP_CALL( retcode );
if( !success )
{
SCIPerrorMessage("syntax error when reading constraint (line: %d):\n%s\n", cipinput->linenumber, cipinput->strbuf);
cipinput->haserror = TRUE;
return SCIP_OKAY;
}
SCIP_CALL( SCIPaddCons(scip, cons) );
SCIPdebugPrintCons(scip, cons, NULL);
SCIP_CALL( SCIPreleaseCons(scip, &cons) );
return SCIP_OKAY;
}
/** 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;
}
/** LP solution separation method of separator */
static
SCIP_DECL_SEPAEXECLP(sepaExeclpRapidlearning)
{/*lint --e{715}*/
SCIP* subscip; /* the subproblem created by rapid learning */
SCIP_SEPADATA* sepadata; /* separator's private data */
SCIP_VAR** vars; /* original problem's variables */
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_HASHMAP* varmapbw; /* mapping of sub-SCIP variables to SCIP variables */
SCIP_CONSHDLR** conshdlrs; /* array of constraint handler's that might that might obtain conflicts */
int* oldnconss; /* number of constraints without rapid learning conflicts */
SCIP_Longint nodelimit; /* node limit for the subproblem */
SCIP_Real timelimit; /* time limit for the subproblem */
SCIP_Real memorylimit; /* memory limit for the subproblem */
int nconshdlrs; /* size of conshdlr and oldnconss array */
int nfixedvars; /* number of variables that could be fixed by rapid learning */
int nvars; /* number of variables */
int restartnum; /* maximal number of conflicts that should be created */
int i; /* counter */
SCIP_Bool success; /* was problem creation / copying constraint successful? */
SCIP_RETCODE retcode; /* used for catching sub-SCIP errors in debug mode */
int nconflicts; /* statistic: number of conflicts applied */
int nbdchgs; /* statistic: number of bound changes applied */
int n1startinfers; /* statistic: number of one side infer values */
int n2startinfers; /* statistic: number of both side infer values */
SCIP_Bool soladded; /* statistic: was a new incumbent found? */
SCIP_Bool dualboundchg; /* statistic: was a new dual bound found? */
SCIP_Bool disabledualreductions; /* TRUE, if dual reductions in sub-SCIP are not valid for original SCIP,
* e.g., because a constraint could not be copied or a primal solution
* could not be copied back
*/
int ndiscvars;
soladded = FALSE;
assert(sepa != NULL);
assert(scip != NULL);
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
ndiscvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip)+SCIPgetNImplVars(scip);
/* only run when still not fixed binary variables exists */
if( ndiscvars == 0 )
return SCIP_OKAY;
/* get separator's data */
sepadata = SCIPsepaGetData(sepa);
assert(sepadata != NULL);
/* only run for integer programs */
if( !sepadata->contvars && ndiscvars != SCIPgetNVars(scip) )
return SCIP_OKAY;
/* only run if there are few enough continuous variables */
if( sepadata->contvars && SCIPgetNContVars(scip) > sepadata->contvarsquot * SCIPgetNVars(scip) )
return SCIP_OKAY;
/* do not run if pricers are present */
if( SCIPgetNActivePricers(scip) > 0 )
return SCIP_OKAY;
/* if the separator should be exclusive to the root node, this prevents multiple calls due to restarts */
if( SCIPsepaGetFreq(sepa) == 0 && SCIPsepaGetNCalls(sepa) > 0)
return SCIP_OKAY;
/* call separator at most once per node */
if( SCIPsepaGetNCallsAtNode(sepa) > 0 )
return SCIP_OKAY;
/* do not call rapid learning, if the problem is too big */
if( SCIPgetNVars(scip) > sepadata->maxnvars || SCIPgetNConss(scip) > sepadata->maxnconss )
return SCIP_OKAY;
if( SCIPisStopped(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* initializing the subproblem */
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
SCIP_CALL( SCIPcreate(&subscip) );
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
success = FALSE;
/* copy the subproblem */
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "rapid", FALSE, FALSE, &success) );
if( sepadata->copycuts )
{
/** copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, FALSE) );
}
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) (size_t) SCIPhashmapGetImage(varmapfw, vars[i]);
SCIPhashmapFree(&varmapfw);
/* this avoids dual presolving */
if( !success )
{
for( i = 0; i < nvars; i++ )
{
SCIP_CALL( SCIPaddVarLocks(subscip, subvars[i], 1, 1 ) );
}
}
SCIPdebugMessage("Copying SCIP was%s successful.\n", success ? "" : " not");
/* mimic an FD solver: DFS, no LP solving, 1-FUIP instead of all-FUIP */
SCIP_CALL( SCIPsetIntParam(subscip, "lp/solvefreq", -1) );
SCIP_CALL( SCIPsetIntParam(subscip, "conflict/fuiplevels", 1) );
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/dfs/stdpriority", INT_MAX/4) );
SCIP_CALL( SCIPsetBoolParam(subscip, "constraints/disableenfops", TRUE) );
SCIP_CALL( SCIPsetIntParam(subscip, "propagating/pseudoobj/freq", -1) );
/* use inference branching */
SCIP_CALL( SCIPsetBoolParam(subscip, "branching/inference/useweightedsum", FALSE) );
/* only create short conflicts */
SCIP_CALL( SCIPsetRealParam(subscip, "conflict/maxvarsfac", 0.05) );
/* set limits for the subproblem */
nodelimit = SCIPgetNLPIterations(scip);
nodelimit = MAX(sepadata->minnodes, nodelimit);
nodelimit = MIN(sepadata->maxnodes, nodelimit);
restartnum = 1000;
/* check whether there is enough time and memory left */
SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
if( !SCIPisInfinity(scip, timelimit) )
timelimit -= SCIPgetSolvingTime(scip);
SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
if( !SCIPisInfinity(scip, memorylimit) )
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
if( timelimit <= 0.0 || memorylimit <= 0.0 )
goto TERMINATE;
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nodelimit/5) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
SCIP_CALL( SCIPsetIntParam(subscip, "limits/restarts", 0) );
SCIP_CALL( SCIPsetIntParam(subscip, "conflict/restartnum", restartnum) );
/* forbid recursive call of heuristics and separators solving subMIPs */
SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
/* disable cutting plane separation */
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
/* disable expensive presolving */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );
/* do not abort subproblem on CTRL-C */
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
#ifndef SCIP_DEBUG
/* disable output to console */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
#endif
/* add an objective cutoff */
SCIP_CALL( SCIPsetObjlimit(subscip, SCIPgetUpperbound(scip)) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapbw, SCIPblkmem(scip), SCIPcalcHashtableSize(5 * nvars)) );
/* store reversing mapping of variables */
SCIP_CALL( SCIPtransformProb(subscip) );
for( i = 0; i < nvars; ++i)
{
SCIP_CALL( SCIPhashmapInsert(varmapbw, SCIPvarGetTransVar(subvars[i]), vars[i]) );
}
/** allocate memory for constraints storage. Each constraint that will be created from now on will be a conflict.
* Therefore, we need to remember oldnconss to get the conflicts from the FD search.
*/
nconshdlrs = 4;
SCIP_CALL( SCIPallocBufferArray(scip, &conshdlrs, nconshdlrs) );
SCIP_CALL( SCIPallocBufferArray(scip, &oldnconss, nconshdlrs) );
/* store number of constraints before rapid learning search */
conshdlrs[0] = SCIPfindConshdlr(subscip, "bounddisjunction");
conshdlrs[1] = SCIPfindConshdlr(subscip, "setppc");
conshdlrs[2] = SCIPfindConshdlr(subscip, "linear");
conshdlrs[3] = SCIPfindConshdlr(subscip, "logicor");
/* redundant constraints might be eliminated in presolving */
SCIP_CALL( SCIPpresolve(subscip));
for( i = 0; i < nconshdlrs; ++i)
{
if( conshdlrs[i] != NULL )
oldnconss[i] = SCIPconshdlrGetNConss(conshdlrs[i]);
}
nfixedvars = SCIPgetNFixedVars(scip);
/* solve the subproblem */
retcode = SCIPsolve(subscip);
/* Errors in solving the subproblem should not kill the overall solving process
* Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage("Error while solving subproblem in rapid learning separator; sub-SCIP terminated with code <%d>\n",retcode);
}
/* abort solving, if limit of applied conflicts is reached */
if( SCIPgetNConflictConssApplied(subscip) >= restartnum )
{
SCIPdebugMessage("finish after %lld successful conflict calls.\n", SCIPgetNConflictConssApplied(subscip));
}
/* if the first 20% of the solution process were successful, proceed */
else if( (sepadata->applyprimalsol && SCIPgetNSols(subscip) > 0 && SCIPisFeasLT(scip, SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip) ) )
|| (sepadata->applybdchgs && SCIPgetNFixedVars(subscip) > nfixedvars)
|| (sepadata->applyconflicts && SCIPgetNConflictConssApplied(subscip) > 0) )
{
SCIPdebugMessage("proceed solving after the first 20%% of the solution process, since:\n");
if( SCIPgetNSols(subscip) > 0 && SCIPisFeasLE(scip, SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip) ) )
{
SCIPdebugMessage(" - there was a better solution (%f < %f)\n",SCIPgetUpperbound(subscip), SCIPgetUpperbound(scip));
}
if( SCIPgetNFixedVars(subscip) > nfixedvars )
{
SCIPdebugMessage(" - there were %d variables fixed\n", SCIPgetNFixedVars(scip)-nfixedvars );
}
if( SCIPgetNConflictConssFound(subscip) > 0 )
{
SCIPdebugMessage(" - there were %lld conflict constraints created\n", SCIPgetNConflictConssApplied(subscip));
}
/* set node limit to 100% */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nodelimit) );
/* solve the subproblem */
retcode = SCIPsolve(subscip);
/* Errors in solving the subproblem should not kill the overall solving process
* Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage("Error while solving subproblem in rapid learning separator; sub-SCIP terminated with code <%d>\n",retcode);
}
}
else
{
SCIPdebugMessage("do not proceed solving after the first 20%% of the solution process.\n");
}
#ifdef SCIP_DEBUG
SCIP_CALL( SCIPprintStatistics(subscip, NULL) );
#endif
disabledualreductions = FALSE;
/* check, whether a solution was found */
if( sepadata->applyprimalsol && SCIPgetNSols(subscip) > 0 && SCIPfindHeur(scip, "trysol") != NULL )
{
SCIP_HEUR* heurtrysol;
SCIP_SOL** subsols;
int nsubsols;
/* check, whether a solution was found;
* due to numerics, it might happen that not all solutions are feasible -> try all solutions until was declared to be feasible
*/
nsubsols = SCIPgetNSols(subscip);
subsols = SCIPgetSols(subscip);
soladded = FALSE;
heurtrysol = SCIPfindHeur(scip, "trysol");
/* sequentially add solutions to trysol heuristic */
for( i = 0; i < nsubsols && !soladded; ++i )
{
SCIPdebugMessage("Try to create new solution by copying subscip solution.\n");
SCIP_CALL( createNewSol(scip, subscip, subvars, heurtrysol, subsols[i], &soladded) );
}
if( !soladded || !SCIPisEQ(scip, SCIPgetSolOrigObj(subscip, subsols[i-1]), SCIPgetSolOrigObj(subscip, subsols[0])) )
disabledualreductions = TRUE;
}
/* if the sub problem was solved completely, we update the dual bound */
dualboundchg = FALSE;
if( sepadata->applysolved && !disabledualreductions
&& (SCIPgetStatus(subscip) == SCIP_STATUS_OPTIMAL || SCIPgetStatus(subscip) == SCIP_STATUS_INFEASIBLE) )
{
/* we need to multiply the dualbound with the scaling factor and add the offset,
* because this information has been disregarded in the sub-SCIP */
SCIPdebugMessage("Update old dualbound %g to new dualbound %g.\n", SCIPgetDualbound(scip), SCIPgetTransObjscale(scip) * SCIPgetDualbound(subscip) + SCIPgetTransObjoffset(scip));
SCIP_CALL( SCIPupdateLocalDualbound(scip, SCIPgetDualbound(subscip) * SCIPgetTransObjscale(scip) + SCIPgetTransObjoffset(scip)) );
dualboundchg = TRUE;
}
/* check, whether conflicts were created */
nconflicts = 0;
if( sepadata->applyconflicts && !disabledualreductions && SCIPgetNConflictConssApplied(subscip) > 0 )
{
SCIP_HASHMAP* consmap;
int hashtablesize;
assert(SCIPgetNConflictConssApplied(subscip) < (SCIP_Longint) INT_MAX);
hashtablesize = (int) SCIPgetNConflictConssApplied(subscip);
assert(hashtablesize < INT_MAX/5);
hashtablesize *= 5;
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&consmap, SCIPblkmem(scip), SCIPcalcHashtableSize(hashtablesize)) );
/* loop over all constraint handlers that might contain conflict constraints */
for( i = 0; i < nconshdlrs; ++i)
{
/* copy constraints that have been created in FD run */
if( conshdlrs[i] != NULL && SCIPconshdlrGetNConss(conshdlrs[i]) > oldnconss[i] )
{
SCIP_CONS** conss;
int c;
int nconss;
nconss = SCIPconshdlrGetNConss(conshdlrs[i]);
conss = SCIPconshdlrGetConss(conshdlrs[i]);
/* loop over all constraints that have been added in sub-SCIP run, these are the conflicts */
for( c = oldnconss[i]; c < nconss; ++c)
{
SCIP_CONS* cons;
SCIP_CONS* conscopy;
cons = conss[c];
assert(cons != NULL);
success = FALSE;
SCIP_CALL( SCIPgetConsCopy(subscip, scip, cons, &conscopy, conshdlrs[i], varmapbw, consmap, NULL,
SCIPconsIsInitial(cons), SCIPconsIsSeparated(cons), SCIPconsIsEnforced(cons), SCIPconsIsChecked(cons),
SCIPconsIsPropagated(cons), TRUE, FALSE, SCIPconsIsDynamic(cons),
SCIPconsIsRemovable(cons), FALSE, TRUE, &success) );
if( success )
{
nconflicts++;
SCIP_CALL( SCIPaddCons(scip, conscopy) );
SCIP_CALL( SCIPreleaseCons(scip, &conscopy) );
}
else
{
SCIPdebugMessage("failed to copy conflict constraint %s back to original SCIP\n", SCIPconsGetName(cons));
}
}
}
}
SCIPhashmapFree(&consmap);
}
/* check, whether tighter global bounds were detected */
nbdchgs = 0;
if( sepadata->applybdchgs && !disabledualreductions )
for( i = 0; i < nvars; ++i )
{
SCIP_Bool infeasible;
SCIP_Bool tightened;
assert(SCIPisLE(scip, SCIPvarGetLbGlobal(vars[i]), SCIPvarGetLbGlobal(subvars[i])));
assert(SCIPisLE(scip, SCIPvarGetLbGlobal(subvars[i]), SCIPvarGetUbGlobal(subvars[i])));
assert(SCIPisLE(scip, SCIPvarGetUbGlobal(subvars[i]), SCIPvarGetUbGlobal(vars[i])));
/* update the bounds of the original SCIP, if a better bound was proven in the sub-SCIP */
SCIP_CALL( SCIPtightenVarUb(scip, vars[i], SCIPvarGetUbGlobal(subvars[i]), FALSE, &infeasible, &tightened) );
if( tightened )
nbdchgs++;
SCIP_CALL( SCIPtightenVarLb(scip, vars[i], SCIPvarGetLbGlobal(subvars[i]), FALSE, &infeasible, &tightened) );
if( tightened )
nbdchgs++;
}
n1startinfers = 0;
n2startinfers = 0;
/* install start values for inference branching */
if( sepadata->applyinfervals && (!sepadata->reducedinfer || soladded || nbdchgs+nconflicts > 0) )
{
for( i = 0; i < nvars; ++i )
{
SCIP_Real downinfer;
SCIP_Real upinfer;
SCIP_Real downvsids;
SCIP_Real upvsids;
SCIP_Real downconflen;
SCIP_Real upconflen;
/* copy downwards branching statistics */
downvsids = SCIPgetVarVSIDS(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);
downconflen = SCIPgetVarAvgConflictlength(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);
downinfer = SCIPgetVarAvgInferences(subscip, subvars[i], SCIP_BRANCHDIR_DOWNWARDS);
/* copy upwards branching statistics */
upvsids = SCIPgetVarVSIDS(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);
upconflen = SCIPgetVarAvgConflictlength(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);
upinfer = SCIPgetVarAvgInferences(subscip, subvars[i], SCIP_BRANCHDIR_UPWARDS);
/* memorize statistics */
if( downinfer+downconflen+downvsids > 0.0 || upinfer+upconflen+upvsids != 0 )
n1startinfers++;
if( downinfer+downconflen+downvsids > 0.0 && upinfer+upconflen+upvsids != 0 )
n2startinfers++;
SCIP_CALL( SCIPinitVarBranchStats(scip, vars[i], 0.0, 0.0, downvsids, upvsids, downconflen, upconflen, downinfer, upinfer, 0.0, 0.0) );
}
}
SCIPdebugPrintf("XXX Rapidlearning added %d conflicts, changed %d bounds, %s primal solution, %s dual bound improvement.\n", nconflicts, nbdchgs, soladded ? "found" : "no",
dualboundchg ? "found" : "no");
SCIPdebugPrintf("YYY Infervalues initialized on one side: %5.2f %% of variables, %5.2f %% on both sides\n",
100.0 * n1startinfers/(SCIP_Real)nvars, 100.0 * n2startinfers/(SCIP_Real)nvars);
/* change result pointer */
if( nconflicts > 0 || dualboundchg )
*result = SCIP_CONSADDED;
else if( nbdchgs > 0 )
*result = SCIP_REDUCEDDOM;
/* free local data */
SCIPfreeBufferArray(scip, &oldnconss);
SCIPfreeBufferArray(scip, &conshdlrs);
SCIPhashmapFree(&varmapbw);
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/** initializes the pricing problem for the given capacity */
static
SCIP_RETCODE initPricing(
SCIP* scip, /**< SCIP data structure */
SCIP_PRICERDATA* pricerdata, /**< pricer data */
SCIP* subscip, /**< pricing SCIP data structure */
SCIP_VAR** vars /**< variable array for the items */
)
{
SCIP_CONS** conss;
SCIP_Longint* vals;
SCIP_CONS* cons;
SCIP_VAR* var;
SCIP_Longint* weights;
SCIP_Longint capacity;
SCIP_Real dual;
int nitems;
int nvars;
int c;
assert( SCIPgetStage(subscip) == SCIP_STAGE_PROBLEM );
assert(pricerdata != NULL);
nitems = pricerdata->nitems;
conss = pricerdata->conss;
weights = pricerdata->weights;
capacity = pricerdata->capacity;
nvars = 0;
SCIP_CALL( SCIPallocBufferArray(subscip, &vals, nitems) );
/* create for each order, which is not assigned yet, a variable with objective coefficient */
for( c = 0; c < nitems; ++c )
{
cons = conss[c];
/* check if each constraint is setppc constraint */
assert( !strncmp( SCIPconshdlrGetName( SCIPconsGetHdlr(cons) ), "setppc", 6) );
/* constraints which are (locally) disabled/redundant are not of
* interest since the corresponding job is assigned to a packing
*/
if( !SCIPconsIsEnabled(cons) )
continue;
if( SCIPgetNFixedonesSetppc(scip, cons) == 1 )
{
/* disable constraint locally */
SCIP_CALL( SCIPdelConsLocal(scip, cons) );
continue;
}
/* dual value in original SCIP */
dual = SCIPgetDualsolSetppc(scip, cons);
SCIP_CALL( SCIPcreateVarBasic(subscip, &var, SCIPconsGetName(cons), 0.0, 1.0, dual, SCIP_VARTYPE_BINARY) );
SCIP_CALL( SCIPaddVar(subscip, var) );
vals[nvars] = weights[c];
vars[nvars] = var;
nvars++;
/* release variable */
SCIP_CALL( SCIPreleaseVar(subscip, &var) );
}
/* create capacity constraint */
SCIP_CALL( SCIPcreateConsBasicKnapsack(subscip, &cons, "capacity", nvars, vars, vals,
capacity) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
/* add constraint of the branching decisions */
SCIP_CALL( addBranchingDecisionConss(scip, subscip, vars, pricerdata->conshdlr) );
/* avoid to generate columns which are fixed to zero */
SCIP_CALL( addFixedVarsConss(scip, subscip, vars, conss, nitems) );
SCIPfreeBufferArray(subscip, &vals);
return SCIP_OKAY;
}
/** avoid to generate columns which are fixed to zero; therefore add for each variable which is fixed to zero a
* corresponding logicor constraint to forbid this column
*
* @note variable which are fixed locally to zero should not be generated again by the pricing MIP
*/
static
SCIP_RETCODE addFixedVarsConss(
SCIP* scip, /**< SCIP data structure */
SCIP* subscip, /**< pricing SCIP data structure */
SCIP_VAR** vars, /**< variable array of the subscuip */
SCIP_CONS** conss, /**< array of setppc constraint for each item one */
int nitems /**< number of items */
)
{
SCIP_VAR** origvars;
int norigvars;
SCIP_CONS* cons;
int* consids;
int nconsids;
int consid;
int nvars;
SCIP_VAR** logicorvars;
SCIP_VAR* var;
SCIP_VARDATA* vardata;
SCIP_Bool needed;
int nlogicorvars;
int v;
int c;
int o;
/* collect all variable which are currently existing */
origvars = SCIPgetVars(scip);
norigvars = SCIPgetNVars(scip);
/* loop over all these variables and check if they are fixed to zero */
for( v = 0; v < norigvars; ++v )
{
assert(SCIPvarGetType(origvars[v]) == SCIP_VARTYPE_BINARY);
/* if the upper bound is smaller than 0.5 if follows due to the integrality that the binary variable is fixed to zero */
if( SCIPvarGetUbLocal(origvars[v]) < 0.5 )
{
SCIPdebugMessage("variable <%s> glb=[%.15g,%.15g] loc=[%.15g,%.15g] is fixed to zero\n",
SCIPvarGetName(origvars[v]), SCIPvarGetLbGlobal(origvars[v]), SCIPvarGetUbGlobal(origvars[v]),
SCIPvarGetLbLocal(origvars[v]), SCIPvarGetUbLocal(origvars[v]) );
/* coolect the constraints/items the variable belongs to */
vardata = SCIPvarGetData(origvars[v]);
nconsids = SCIPvardataGetNConsids(vardata);
consids = SCIPvardataGetConsids(vardata);
needed = TRUE;
SCIP_CALL( SCIPallocBufferArray(subscip, &logicorvars, nitems) );
nlogicorvars = 0;
consid = consids[0];
nvars = 0;
/* loop over these items and create a linear (logicor) constraint which forbids this item combination in the
* pricing problem; thereby check if this item combination is already forbidden
*/
for( c = 0, o = 0; o < nitems && needed; ++o )
{
assert(o <= consid);
cons = conss[o];
if( SCIPconsIsEnabled(cons) )
{
assert( SCIPgetNFixedonesSetppc(scip, cons) == 0 );
var = vars[nvars];
nvars++;
assert(var != NULL);
if( o == consid )
{
SCIP_CALL( SCIPgetNegatedVar(subscip, var, &var) );
}
logicorvars[nlogicorvars] = var;
nlogicorvars++;
}
else if( o == consid )
needed = FALSE;
if( o == consid )
{
c++;
if ( c == nconsids )
consid = nitems + 100;
else
{
assert(consid < consids[c]);
consid = consids[c];
}
}
}
if( needed )
{
SCIP_CALL( SCIPcreateConsBasicLogicor(subscip, &cons, SCIPvarGetName(origvars[v]), nlogicorvars, logicorvars) );
SCIP_CALL( SCIPsetConsInitial(subscip, cons, FALSE) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
}
SCIPfreeBufferArray(subscip, &logicorvars);
}
}
return SCIP_OKAY;
}
/** 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;
}
/** 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;
}
/* 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;
}
/** 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;
}
/** 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;
}
/** 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;
}
/** constraint copying method of constraint handler */
static
SCIP_DECL_CONSCOPY(consCopyConjunction)
{ /*lint --e{715}*/
SCIP_CONSDATA* sourcedata;
SCIP_CONS** sourceconss;
SCIP_CONS** conss;
int nconss;
int c;
*valid = TRUE;
sourcedata = SCIPconsGetData(sourcecons);
assert(sourcedata != NULL);
sourceconss = sourcedata->conss;
nconss = sourcedata->nconss;
if( nconss > 0 )
{
assert(sourceconss != NULL);
SCIP_CALL( SCIPallocBufferArray(scip, &conss, nconss) );
/* copy each constraint one by one */
for( c = 0; c < nconss && (*valid); ++c )
{
SCIP_CALL( SCIPgetConsCopy(sourcescip, scip, sourceconss[c], &conss[c], SCIPconsGetHdlr(sourceconss[c]),
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 )
{
if( name == NULL )
{
SCIP_CALL( SCIPcreateConsConjunction(scip, cons, SCIPconsGetName(sourcecons), nconss, conss,
enforce, check, local, modifiable, dynamic) );
}
else
{
SCIP_CALL( SCIPcreateConsConjunction(scip, cons, name, nconss, conss,
enforce, check, local, modifiable, dynamic) );
}
}
/* release the copied constraints */
for( c = (*valid ? c - 1 : c - 2); c >= 0; --c )
{
assert(conss[c] != NULL);
SCIP_CALL( SCIPreleaseCons(scip, &conss[c]) );
}
SCIPfreeBufferArray(scip, &conss);
}
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;
}
/** add branching decisions constraints to the sub SCIP */
static
SCIP_RETCODE addBranchingDecisionConss(
SCIP* scip, /**< SCIP data structure */
SCIP* subscip, /**< pricing SCIP data structure */
SCIP_VAR** vars, /**< variable array of the subscuip oder variables */
SCIP_CONSHDLR* conshdlr /**< constraint handler for branching data */
)
{
SCIP_CONS** conss;
SCIP_CONS* cons;
int nconss;
int id1;
int id2;
CONSTYPE type;
SCIP_Real vbdcoef;
SCIP_Real lhs;
SCIP_Real rhs;
int c;
assert( scip != NULL );
assert( subscip != NULL );
assert( conshdlr != NULL );
/* collect all branching decision constraints */
conss = SCIPconshdlrGetConss(conshdlr);
nconss = SCIPconshdlrGetNConss(conshdlr);
/* loop over all branching decision constraints and apply the branching decision if the corresponding constraint is
* active
*/
for( c = 0; c < nconss; ++c )
{
cons = conss[c];
/* ignore constraints which are not active since these are not laying on the current active path of the search
* tree
*/
if( !SCIPconsIsActive(cons) )
continue;
/* collect the two item ids and the branching type (SAME or DIFFER) on which the constraint branched */
id1 = SCIPgetItemid1Samediff(scip, cons);
id2 = SCIPgetItemid2Samediff(scip, cons);
type = SCIPgetTypeSamediff(scip, cons);
SCIPdebugMessage("create varbound for %s(%d,%d)\n", type == SAME ? "same" : "diff",
SCIPprobdataGetIds(SCIPgetProbData(scip))[id1], SCIPprobdataGetIds(SCIPgetProbData(scip))[id2]);
/* depending on the branching type select the correct left and right hand side for the linear constraint which
* enforces this branching decision in the pricing problem MIP
*/
if( type == SAME )
{
lhs = 0.0;
rhs = 0.0;
vbdcoef = -1.0;
}
else if( type == DIFFER )
{
lhs = -SCIPinfinity(scip);
rhs = 1.0;
vbdcoef = 1.0;
}
else
{
SCIPerrorMessage("unknow constraint type <%d>\n, type");
return SCIP_INVALIDDATA;
}
/* add linear (in that case a variable bound) constraint to pricing MIP depending on the branching type:
*
* - branching type SAME: x1 = x2 <=> x1 - x2 = 0 <=> 0 <= x1 - x2 <= 0
*
* - branching type DIFFER: x1 - x2 <= 1 <=> -inf <= x1 - x2 <= 1
*
*/
SCIP_CALL( SCIPcreateConsBasicVarbound(subscip, &cons, SCIPconsGetName(conss[c]),
vars[id1], vars[id2], vbdcoef, lhs, rhs) );
SCIPdebug( SCIPprintCons(subscip, cons, NULL) );
SCIP_CALL( SCIPaddCons(subscip, cons) );
SCIP_CALL( SCIPreleaseCons(subscip, &cons) );
}
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;
}
/** creates a cumulative scheduling problem */
SCIP_RETCODE SCIPcreateSchedulingProblem(
SCIP* scip, /**< SCIP data structure */
const char* problemname, /**< problem name */
const char** jobnames, /**< job names, or NULL */
const char** resourcenames, /**< resource names, or NULL */
int** demands, /**< demand matrix resource job demand */
SCIP_DIGRAPH* precedencegraph, /**< direct graph to store the precedence conditions */
int* durations, /**< array to store the processing for each job */
int* capacities, /**< array to store the different capacities */
int njobs, /**< number of jobs to be parsed */
int nresources /**< number of capacities to be parsed */
)
{
SCIP_VAR** jobs;
SCIP_VAR** vars;
SCIP_VAR* var;
SCIP_CONS* cons;
char name[SCIP_MAXSTRLEN];
int* consdurations;
int* consdemands;
int nvars;
int ubmakespan;
int i;
int j;
int r;
assert( scip != NULL );
assert( njobs >= 0 );
SCIPdebugMessage( "start method SCIPcreateSchedulingSMProblem\n");
/* create SCIP data structure */
SCIP_CALL( SCIPcreateProb(scip, problemname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );
/* compute a feasible upper bound on the makespan */
ubmakespan = computeUbmakespan(durations, njobs);
ubmakespan *= 100;
/* allocate buffer for jobs and precedence constraints */
SCIP_CALL( SCIPallocBufferArray(scip, &jobs, njobs) );
/* create an activity constraint for each activity */
for( j = 0; j < njobs - 1; ++j ) /* but not for last job which is the makespan (-1) */
{
/* construct variable name */
if( jobnames != NULL )
(void)SCIPsnprintf(name, SCIP_MAXSTRLEN, "start_%s", jobnames[j]);
else
(void)SCIPsnprintf(name, SCIP_MAXSTRLEN, "start_%d", j);
/* create integer starting variable */
SCIP_CALL( SCIPcreateVar(scip, &var, name, 0.0, (SCIP_Real)ubmakespan, 0.0, SCIP_VARTYPE_INTEGER,
TRUE, FALSE, NULL, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPaddVar(scip, var) );
SCIP_CALL( SCIPmarkDoNotMultaggrVar(scip, var) );
jobs[j] = var;
SCIP_CALL( SCIPreleaseVar(scip, &var) );
}
/* create makespan variable */
SCIP_CALL( SCIPcreateVar(scip, &var, "makespan", 0.0, (SCIP_Real)ubmakespan, 1.0, SCIP_VARTYPE_INTEGER,
TRUE, FALSE, NULL, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPaddVar(scip, var) );
SCIP_CALL( SCIPmarkDoNotMultaggrVar(scip, var) );
jobs[njobs-1] = var;
SCIP_CALL( SCIPreleaseVar(scip, &var) );
/* precedence constraints */
for( j = 0; j < njobs - 1; ++j )
{
SCIP_VAR* predvar;
int nsuccessors;
nsuccessors = SCIPdigraphGetNSuccessors(precedencegraph, j);
predvar = jobs[j];
assert(predvar != NULL);
if( nsuccessors > 0 )
{
int* successors;
void** distances;
successors = SCIPdigraphGetSuccessors(precedencegraph, j);
distances = SCIPdigraphGetSuccessorsDatas(precedencegraph, j);
for( i = 0; i < nsuccessors; ++i )
{
SCIP_VAR* succvar;
int distance;
succvar = jobs[successors[i]];
assert(succvar != NULL);
(void)SCIPsnprintf(name, SCIP_MAXSTRLEN, "precedences_(%d,%d)", j, successors[i]);
distance = (int)(size_t)distances[i];
if( distance == INT_MAX )
distance = durations[j];
SCIP_CALL( SCIPcreateConsVarbound(scip, &cons, name, predvar, succvar, -1.0,
-SCIPinfinity(scip), -distance,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE) );
SCIP_CALL( SCIPaddCons(scip, cons) );
SCIP_CALL( SCIPreleaseCons(scip, &cons) );
}
}
else
{
/* add precedence constraints for those jobs without successor */
(void)SCIPsnprintf(name, SCIP_MAXSTRLEN, "precedences_(%d,%d)", j, njobs);
SCIP_CALL( SCIPcreateConsVarbound(scip, &cons, name, predvar, jobs[njobs-1], -1.0,
-SCIPinfinity(scip), -durations[j],
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE) );
SCIP_CALL( SCIPaddCons(scip, cons) );
SCIP_CALL( SCIPreleaseCons(scip, &cons) );
}
}
SCIP_CALL( SCIPallocBufferArray(scip, &vars, njobs) );
SCIP_CALL( SCIPallocBufferArray(scip, &consdemands, njobs) );
SCIP_CALL( SCIPallocBufferArray(scip, &consdurations, njobs) );
/* create resource constraints */
for( r = 0; r < nresources; ++r )
{
nvars = 0;
for( j = 0; j < njobs; ++j ) /* also makespan constraint! */
{
if( demands[j][r] > 0 )
{
vars[nvars] = jobs[j];
consdemands[nvars] = demands[j][r];
consdurations[nvars] = durations[j];
nvars++;
}
}
if( nvars > 0 )
{
/* construct constraint name */
if( resourcenames != NULL )
(void)SCIPsnprintf(name, SCIP_MAXSTRLEN, "R%s", resourcenames[r]);
else
(void)SCIPsnprintf(name, SCIP_MAXSTRLEN, "R%d", r);
SCIP_CALL( SCIPcreateConsCumulative(scip, &cons, name,
nvars, vars, consdurations, consdemands, capacities[r],
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE) );
SCIP_CALL( SCIPaddCons(scip, cons) );
SCIP_CALL( SCIPreleaseCons(scip, &cons) );
}
}
/* initialize the problem specific heuristic */
SCIP_CALL( SCIPinitializeHeurListScheduling(scip, precedencegraph, jobs,
durations, demands, capacities, njobs, nresources) );
/* free buffer array */
SCIPfreeBufferArray(scip, &consdurations);
SCIPfreeBufferArray(scip, &consdemands);
SCIPfreeBufferArray(scip, &vars);
SCIPfreeBufferArray(scip, &jobs);
return SCIP_OKAY;
}
