/** problem writing method of reader */
static
SCIP_DECL_READERWRITE(readerWriteRlp)
{ /*lint --e{715}*/
if( genericnames )
{
SCIP_CALL( SCIPwriteLp(scip, file, name, transformed, objsense, objscale, objoffset, vars,
nvars, nbinvars, nintvars, nimplvars, ncontvars, conss, nconss, result) );
}
else
{
SCIPwarningMessage(scip, "RLP format is LP format with generic variable and constraint names\n");
if( transformed )
{
SCIPwarningMessage(scip, "write transformed problem with generic variable and constraint names\n");
SCIP_CALL( SCIPprintTransProblem(scip, file, "rlp", TRUE) );
}
else
{
SCIPwarningMessage(scip, "write original problem with generic variable and constraint names\n");
SCIP_CALL( SCIPprintOrigProblem(scip, file, "rlp", TRUE) );
}
*result = SCIP_SUCCESS;
}
return SCIP_OKAY;
}
static
void readWarning(
SCIP* scip, /**< SCIP data structure */
int linecount, /**< line number of error */
const char* warningmsg /**< warning message */
)
{
SCIPwarningMessage(scip, "Line <%d>: %s\n", linecount, warningmsg);
}
/** read the problem name out of the statistics */
static
SCIP_RETCODE getStatistic(
SCIP* scip, /**< SCIP data structure */
CIPINPUT* cipinput /**< CIP parsing data */
)
{
char* buf;
buf = cipinput->strbuf;
if( strncmp(buf, "OBJECTIVE", 9) == 0 )
{
cipinput->section = CIP_OBJECTIVE;
return SCIP_OKAY;
}
SCIPdebugMessage("parse statistic\n");
if( strncmp(buf, " Problem name", 14) == 0 )
{
char* name;
char* s;
name = strchr(buf, ':');
if( name == NULL )
{
SCIPwarningMessage(scip, "did not find problem name\n");
return SCIP_OKAY; /* no error, might work with empty problem name */
}
/* skip ':' */
++name;
/* remove tabs new line form string */
if( NULL != (s = strpbrk(name, "#\r\n")) )
*s = '\0';
/* remove white space in front of the name */
while(isspace((unsigned char)*name))
name++;
/* set problem name */
SCIP_CALL( SCIPsetProbName(scip, name) );
SCIPdebugMessage("problem name <%s>\n", name);
}
return SCIP_OKAY;
}
/** read the problem name out of the statistics */
static
SCIP_RETCODE getStatistics(
SCIP* scip, /**< SCIP data structure */
CIPINPUT* cipinput /**< CIP parsing data */
)
{
char* buf;
buf = cipinput->strbuf;
if( strncmp(buf, "OBJECTIVE", 9) == 0 )
{
cipinput->section = CIP_OBJECTIVE;
return SCIP_OKAY;
}
SCIPdebugMessage("parse statistics\n");
if( strncmp(buf, " Problem name", 14) == 0 )
{
char* name;
char* s;
name = strchr(buf, ':');
if( name == NULL )
{
SCIPwarningMessage(scip, "did not find problem name (line: %d):\n%s\n", cipinput->linenumber, cipinput->strbuf);
return SCIP_OKAY; /* no error, might work with empty problem name */
}
/* skip ':' */
++name;
/* make sure that we terminate the string at comments ('#') or newline ('\r', '\n')*/
if( NULL != (s = strpbrk(name, "#\r\n")) )
*s = '\0';
/* remove white space (tabs, ' ') in front of the name */
while( isspace((unsigned char)* name) )
++name;
/* set problem name */
SCIP_CALL( SCIPsetProbName(scip, name) );
SCIPdebugMessage("problem name <%s>\n", name);
}
return SCIP_OKAY;
}
/** reads the masterconss section */
static
SCIP_RETCODE readMasterconss(
SCIP* scip, /**< SCIP data structure */
DECINPUT* decinput, /**< DEC reading data */
SCIP_READERDATA* readerdata /**< reader data */
)
{
assert(scip != NULL);
assert(decinput != NULL);
assert(readerdata != NULL);
while( getNextToken(decinput) )
{
SCIP_CONS* cons;
/* check if we reached a new section */
if( isNewSection(scip, decinput) )
break;
/* the token must be the name of an existing constraint */
cons = SCIPfindCons(scip, decinput->token);
if( cons == NULL )
{
syntaxError(scip, decinput, "unknown constraint in masterconss section");
break;
}
else
{
if( !SCIPhashmapExists( readerdata->constoblock, cons) )
{
SCIPwarningMessage(scip, "Cons <%s> has been deleted by presolving, skipping.\n", SCIPconsGetName(cons));
continue;
}
assert(SCIPhashmapGetImage(readerdata->constoblock, cons) == (void*)(size_t) LINKINGVALUE);
SCIPdebugMessage("cons %s is linking constraint\n", decinput->token);
}
}
return SCIP_OKAY;
}
/** farkas pricing method of variable pricer for infeasible LPs */
static
SCIP_DECL_PRICERFARKAS(pricerFarkasBinpacking)
{ /*lint --e{715}*/
/** @note In case of this binpacking example, the master LP should not get infeasible after branching, because of the
* way branching is performed. Therefore, the Farkas pricing is not implemented.
* 1. In case of Ryan/Foster branching, the two items are selected in a way such that the sum of the LP values
* of all columns/packings containing both items is fractional. Hence, it exists at least one
* column/packing which contains both items and also at least one column/packing for each item containing
* this but not the other item. That means, branching in the "same" direction stays LP feasible since there
* exists at least one column/packing with both items and branching in the "differ" direction stays LP
* feasible since there exists at least one column/packing containing one item, but not the other.
* 2. In case of variable branching, we only branch on fractional variables. If a variable is fixed to one,
* there is no issue. If a variable is fixed to zero, then we know that for each item which is part of
* that column/packing, there exists at least one other column/packing containing this particular item due
* to the covering constraints.
*/
SCIPwarningMessage(scip, "Current master LP is infeasible, but Farkas pricing was not implemented\n");
SCIPABORT();
return SCIP_OKAY;
}
/** initialization method of primal heuristic (called after problem was transformed) */
static
SCIP_DECL_HEURINIT(heurInitIndicator)
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
assert( heur != NULL );
assert( scip != NULL );
/* get heuristic data */
heurdata = SCIPheurGetData(heur);
assert( heurdata != NULL );
if ( heurdata->indicatorconshdlr != NULL )
{
heurdata->indicatorconshdlr = SCIPfindConshdlr(scip, "indicator");
if ( heurdata->indicatorconshdlr == NULL )
{
SCIPwarningMessage(scip, "Could not find indicator constraint handler.\n");
}
}
return SCIP_OKAY;
}
/** write a DEC file for a given decomposition */
SCIP_RETCODE GCGwriteDecomp(
SCIP* scip, /**< SCIP data structure */
FILE* file, /**< File pointer to write to */
DEC_DECOMP* decdecomp /**< Decomposition pointer */
)
{
char outname[SCIP_MAXSTRLEN];
assert(scip != NULL);
if( decdecomp == NULL )
{
SCIPwarningMessage(scip, "Cannot write decomposed problem if decomposition structure is empty!\n");
(void) SCIPsnprintf(outname, SCIP_MAXSTRLEN, "%s", SCIPgetProbName(scip));
}
else
{
(void) SCIPsnprintf(outname, SCIP_MAXSTRLEN, "%s_%d", SCIPgetProbName(scip), DECdecompGetNBlocks(decdecomp));
SCIP_CALL( writeData(scip, file, decdecomp) );
}
return SCIP_OKAY;
}
/** transforms given solution of the master problem into solution of the original problem
* @todo think about types of epsilons used in this method
*/
SCIP_RETCODE GCGrelaxTransformMastersolToOrigsol(
SCIP* scip, /**< SCIP data structure */
SCIP_SOL* mastersol, /**< solution of the master problem, or NULL for current LP solution */
SCIP_SOL** origsol /**< pointer to store the new created original problem's solution */
)
{
SCIP* masterprob;
int npricingprobs;
int* blocknrs;
SCIP_Real* blockvalue;
SCIP_Real increaseval;
SCIP_VAR** mastervars;
SCIP_Real* mastervals;
int nmastervars;
SCIP_VAR** vars;
int nvars;
SCIP_Real feastol;
int i;
int j;
assert(scip != NULL);
assert(origsol != NULL);
masterprob = GCGrelaxGetMasterprob(scip);
npricingprobs = GCGrelaxGetNPricingprobs(scip);
assert( !SCIPisInfinity(scip, SCIPgetSolOrigObj(masterprob, mastersol)) );
SCIP_CALL( SCIPcreateSol(scip, origsol, GCGrelaxGetProbingheur(scip)) );
SCIP_CALL( SCIPallocBufferArray(scip, &blockvalue, npricingprobs) );
SCIP_CALL( SCIPallocBufferArray(scip, &blocknrs, npricingprobs) );
/* get variables of the master problem and their solution values */
SCIP_CALL( SCIPgetVarsData(masterprob, &mastervars, &nmastervars, NULL, NULL, NULL, NULL) );
assert(mastervars != NULL);
assert(nmastervars >= 0);
SCIP_CALL( SCIPallocBufferArray(scip, &mastervals, nmastervars) );
SCIP_CALL( SCIPgetSolVals(masterprob, mastersol, nmastervars, mastervars, mastervals) );
/* initialize the block values for the pricing problems */
for( i = 0; i < npricingprobs; i++ )
{
blockvalue[i] = 0.0;
blocknrs[i] = 0;
}
/* loop over all given master variables */
for( i = 0; i < nmastervars; i++ )
{
SCIP_VAR** origvars;
int norigvars;
SCIP_Real* origvals;
SCIP_Bool isray;
int blocknr;
origvars = GCGmasterVarGetOrigvars(mastervars[i]);
norigvars = GCGmasterVarGetNOrigvars(mastervars[i]);
origvals = GCGmasterVarGetOrigvals(mastervars[i]);
blocknr = GCGvarGetBlock(mastervars[i]);
isray = GCGmasterVarIsRay(mastervars[i]);
assert(GCGvarIsMaster(mastervars[i]));
assert(!SCIPisFeasNegative(scip, mastervals[i]));
/** @todo handle infinite master solution values */
assert(!SCIPisInfinity(scip, mastervals[i]));
/* first of all, handle variables representing rays */
if( isray )
{
assert(blocknr >= 0);
/* we also want to take into account variables representing rays, that have a small value (between normal and feas eps),
* so we do no feas comparison here */
if( SCIPisPositive(scip, mastervals[i]) )
{
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
if( SCIPisZero(scip, origvals[j]) )
break;
assert(!SCIPisZero(scip, origvals[j]));
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done later) */
if( GCGvarIsLinking(origvars[j]) )
continue;
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[j]), origvals[j] * mastervals[i], SCIPvarGetName(mastervars[i]));
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[j], origvals[j] * mastervals[i]) );
}
}
mastervals[i] = 0.0;
continue;
}
/* handle the variables with value >= 1 to get integral values in original solution */
while( SCIPisFeasGE(scip, mastervals[i], 1.0) )
{
/* variable was directly transferred to the master problem (only in linking conss or linking variable) */
/** @todo this may be the wrong place for this case, handle it before the while loop
* and remove the similar case in the next while loop */
if( blocknr == -1 )
{
assert(norigvars == 1);
assert(origvals[0] == 1.0);
/* increase the corresponding value */
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[0]), origvals[0] * mastervals[i], SCIPvarGetName(mastervars[i]));
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[0], origvals[0] * mastervals[i]) );
mastervals[i] = 0.0;
}
else
{
assert(blocknr >= 0);
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
SCIP_VAR* pricingvar;
int norigpricingvars;
SCIP_VAR** origpricingvars;
if( SCIPisZero(scip, origvals[j]) )
break;
assert(!SCIPisZero(scip, origvals[j]));
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done above) */
if( GCGvarIsLinking(origvars[j]) )
continue;
pricingvar = GCGoriginalVarGetPricingVar(origvars[j]);
assert(GCGvarIsPricing(pricingvar));
norigpricingvars = GCGpricingVarGetNOrigvars(pricingvar);
origpricingvars = GCGpricingVarGetOrigvars(pricingvar);
/* just in case a variable has a value higher than the number of blocks, it represents */
if( norigpricingvars <= blocknrs[blocknr] )
{
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[norigpricingvars-1]), mastervals[i] * origvals[j], SCIPvarGetName(mastervars[i]));
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[norigpricingvars-1], mastervals[i] * origvals[j]) );
mastervals[i] = 1.0;
}
/* this should be default */
else
{
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[blocknrs[blocknr]]), origvals[j], SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[blocknrs[blocknr]], origvals[j]) );
}
}
mastervals[i] = mastervals[i] - 1.0;
blocknrs[blocknr]++;
}
}
}
/* loop over all given master variables */
for( i = 0; i < nmastervars; i++ )
{
SCIP_VAR** origvars;
int norigvars;
SCIP_Real* origvals;
int blocknr;
origvars = GCGmasterVarGetOrigvars(mastervars[i]);
norigvars = GCGmasterVarGetNOrigvars(mastervars[i]);
origvals = GCGmasterVarGetOrigvals(mastervars[i]);
blocknr = GCGvarGetBlock(mastervars[i]);
if( SCIPisFeasZero(scip, mastervals[i]) )
{
continue;
}
assert(SCIPisFeasGE(scip, mastervals[i], 0.0) && SCIPisFeasLT(scip, mastervals[i], 1.0));
while( SCIPisFeasPositive(scip, mastervals[i]) )
{
assert(GCGvarIsMaster(mastervars[i]));
assert(!GCGmasterVarIsRay(mastervars[i]));
if( blocknr == -1 )
{
assert(norigvars == 1);
assert(origvals[0] == 1.0);
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origvars[0]), origvals[0] * mastervals[i], SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origvars[0], origvals[0] * mastervals[i]) );
mastervals[i] = 0.0;
}
else
{
increaseval = MIN(mastervals[i], 1.0 - blockvalue[blocknr]);
/* loop over all original variables contained in the current master variable */
for( j = 0; j < norigvars; j++ )
{
SCIP_VAR* pricingvar;
int norigpricingvars;
SCIP_VAR** origpricingvars;
if( SCIPisZero(scip, origvals[j]) )
continue;
/* the original variable is a linking variable: just transfer the solution value of the direct copy (this is done above) */
if( GCGvarIsLinking(origvars[j]) )
continue;
pricingvar = GCGoriginalVarGetPricingVar(origvars[j]);
assert(GCGvarIsPricing(pricingvar));
norigpricingvars = GCGpricingVarGetNOrigvars(pricingvar);
origpricingvars = GCGpricingVarGetOrigvars(pricingvar);
if( norigpricingvars <= blocknrs[blocknr] )
{
increaseval = mastervals[i];
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[norigpricingvars-1]), origvals[j] * increaseval, SCIPvarGetName(mastervars[i]) );
/* increase the corresponding value */
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[norigpricingvars-1], origvals[j] * increaseval) );
}
else
{
/* increase the corresponding value */
SCIPdebugMessage("Increasing value of %s by %f because of %s\n", SCIPvarGetName(origpricingvars[blocknrs[blocknr]]), origvals[j] * increaseval, SCIPvarGetName(mastervars[i]) );
SCIP_CALL( SCIPincSolVal(scip, *origsol, origpricingvars[blocknrs[blocknr]], origvals[j] * increaseval) );
}
}
mastervals[i] = mastervals[i] - increaseval;
if( SCIPisFeasZero(scip, mastervals[i]) )
{
mastervals[i] = 0.0;
}
blockvalue[blocknr] += increaseval;
/* if the value assigned to the block is equal to 1, this block is full and we take the next block */
if( SCIPisFeasGE(scip, blockvalue[blocknr], 1.0) )
{
blockvalue[blocknr] = 0.0;
blocknrs[blocknr]++;
}
}
}
}
SCIPfreeBufferArray(scip, &mastervals);
SCIPfreeBufferArray(scip, &blocknrs);
SCIPfreeBufferArray(scip, &blockvalue);
/* if the solution violates one of its bounds by more than feastol
* and less than 10*feastol, round it and print a warning
*/
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
SCIP_CALL( SCIPgetRealParam(scip, "numerics/feastol", &feastol) );
for( i = 0; i < nvars; ++i )
{
SCIP_Real solval;
SCIP_Real lb;
SCIP_Real ub;
solval = SCIPgetSolVal(scip, *origsol, vars[i]);
lb = SCIPvarGetLbLocal(vars[i]);
ub = SCIPvarGetUbLocal(vars[i]);
if( SCIPisFeasGT(scip, solval, ub) && EPSEQ(solval, ub, 10 * feastol) )
{
SCIP_CALL( SCIPsetSolVal(scip, *origsol, vars[i], ub) );
SCIPwarningMessage(scip, "Variable %s rounded from %g to %g in relaxation solution\n",
SCIPvarGetName(vars[i]), solval, ub);
}
else if( SCIPisFeasLT(scip, solval, lb) && EPSEQ(solval, lb, 10 * feastol) )
{
SCIP_CALL( SCIPsetSolVal(scip, *origsol, vars[i], lb) );
SCIPwarningMessage(scip, "Variable %s rounded from %g to %g in relaxation solution\n",
SCIPvarGetName(vars[i]), solval, lb);
}
}
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecObjpscostdiving) /*lint --e{715}*/
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_LPSOLSTAT lpsolstat;
SCIP_VAR* var;
SCIP_VAR** lpcands;
SCIP_Real* lpcandssol;
SCIP_Real* lpcandsfrac;
SCIP_Real primsol;
SCIP_Real frac;
SCIP_Real pscostquot;
SCIP_Real bestpscostquot;
SCIP_Real oldobj;
SCIP_Real newobj;
SCIP_Real objscale;
SCIP_Bool bestcandmayrounddown;
SCIP_Bool bestcandmayroundup;
SCIP_Bool bestcandroundup;
SCIP_Bool mayrounddown;
SCIP_Bool mayroundup;
SCIP_Bool roundup;
SCIP_Bool lperror;
SCIP_Longint ncalls;
SCIP_Longint nsolsfound;
SCIP_Longint nlpiterations;
SCIP_Longint maxnlpiterations;
int* roundings;
int nvars;
int varidx;
int nlpcands;
int startnlpcands;
int depth;
int maxdepth;
int maxdivedepth;
int divedepth;
int bestcand;
int c;
assert(heur != NULL);
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
assert(SCIPhasCurrentNodeLP(scip));
*result = SCIP_DELAYED;
/* do not call heuristic of node was already detected to be infeasible */
if( nodeinfeasible )
return SCIP_OKAY;
/* only call heuristic, if an optimal LP solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call heuristic, if the LP objective value is smaller than the cutoff bound */
if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
return SCIP_OKAY;
/* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */
if( !SCIPisLPSolBasic(scip) )
return SCIP_OKAY;
/* don't dive two times at the same node */
if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* only apply heuristic, if only a few solutions have been found */
if( heurdata->maxsols >= 0 && SCIPgetNSolsFound(scip) >= heurdata->maxsols )
return SCIP_OKAY;
/* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */
depth = SCIPgetDepth(scip);
maxdepth = SCIPgetMaxDepth(scip);
maxdepth = MAX(maxdepth, 30);
if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth )
return SCIP_OKAY;
/* calculate the maximal number of LP iterations until heuristic is aborted */
nlpiterations = SCIPgetNNodeLPIterations(scip);
ncalls = SCIPheurGetNCalls(heur);
nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess;
maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations);
maxnlpiterations += heurdata->maxlpiterofs;
/* don't try to dive, if we took too many LP iterations during diving */
if( heurdata->nlpiterations >= maxnlpiterations )
return SCIP_OKAY;
/* allow at least a certain number of LP iterations in this dive */
maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER);
/* get fractional variables that should be integral */
SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) );
/* don't try to dive, if there are no fractional variables */
if( nlpcands == 0 )
return SCIP_OKAY;
/* calculate the maximal diving depth */
nvars = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip);
if( SCIPgetNSolsFound(scip) == 0 )
maxdivedepth = (int)(heurdata->depthfacnosol * nvars);
else
maxdivedepth = (int)(heurdata->depthfac * nvars);
maxdivedepth = MIN(maxdivedepth, 10*maxdepth);
*result = SCIP_DIDNOTFIND;
/* get temporary memory for remembering the current soft roundings */
SCIP_CALL( SCIPallocBufferArray(scip, &roundings, nvars) );
BMSclearMemoryArray(roundings, nvars);
/* start diving */
SCIP_CALL( SCIPstartDive(scip) );
SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") executing objpscostdiving heuristic: depth=%d, %d fractionals, dualbound=%g, maxnlpiterations=%"SCIP_LONGINT_FORMAT", maxdivedepth=%d\n",
SCIPgetNNodes(scip), SCIPgetDepth(scip), nlpcands, SCIPgetDualbound(scip), maxnlpiterations, maxdivedepth);
/* dive as long we are in the given diving depth and iteration limits and fractional variables exist, but
* - if the last objective change was in a direction, that corresponds to a feasible rounding, we continue in any case
* - if possible, we dive at least with the depth 10
* - if the number of fractional variables decreased at least with 1 variable per 2 dive depths, we continue diving
*/
lperror = FALSE;
lpsolstat = SCIP_LPSOLSTAT_OPTIMAL;
divedepth = 0;
bestcandmayrounddown = FALSE;
bestcandmayroundup = FALSE;
startnlpcands = nlpcands;
while( !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL && nlpcands > 0
&& (divedepth < 10
|| nlpcands <= startnlpcands - divedepth/2
|| (divedepth < maxdivedepth && nlpcands <= startnlpcands - divedepth/10
&& heurdata->nlpiterations < maxnlpiterations)) && !SCIPisStopped(scip) )
{
SCIP_RETCODE retcode;
divedepth++;
/* choose variable for objective change:
* - prefer variables that may not be rounded without destroying LP feasibility:
* - of these variables, change objective value of variable with largest rel. difference of pseudo cost values
* - if all remaining fractional variables may be rounded without destroying LP feasibility:
* - change objective value of variable with largest rel. difference of pseudo cost values
*/
bestcand = -1;
bestpscostquot = -1.0;
bestcandmayrounddown = TRUE;
bestcandmayroundup = TRUE;
bestcandroundup = FALSE;
for( c = 0; c < nlpcands; ++c )
{
var = lpcands[c];
mayrounddown = SCIPvarMayRoundDown(var);
mayroundup = SCIPvarMayRoundUp(var);
primsol = lpcandssol[c];
frac = lpcandsfrac[c];
if( mayrounddown || mayroundup )
{
/* the candidate may be rounded: choose this candidate only, if the best candidate may also be rounded */
if( bestcandmayrounddown || bestcandmayroundup )
{
/* choose rounding direction:
* - if variable may be rounded in both directions, round corresponding to the pseudo cost values
* - otherwise, round in the infeasible direction, because feasible direction is tried by rounding
* the current fractional solution
*/
roundup = FALSE;
if( mayrounddown && mayroundup )
calcPscostQuot(scip, var, primsol, frac, 0, &pscostquot, &roundup);
else if( mayrounddown )
calcPscostQuot(scip, var, primsol, frac, +1, &pscostquot, &roundup);
else
calcPscostQuot(scip, var, primsol, frac, -1, &pscostquot, &roundup);
/* prefer variables, that have already been soft rounded but failed to get integral */
varidx = SCIPvarGetProbindex(var);
assert(0 <= varidx && varidx < nvars);
if( roundings[varidx] != 0 )
pscostquot *= 1000.0;
/* check, if candidate is new best candidate */
if( pscostquot > bestpscostquot )
{
bestcand = c;
bestpscostquot = pscostquot;
bestcandmayrounddown = mayrounddown;
bestcandmayroundup = mayroundup;
bestcandroundup = roundup;
}
}
}
else
{
/* the candidate may not be rounded: calculate pseudo cost quotient and preferred direction */
calcPscostQuot(scip, var, primsol, frac, 0, &pscostquot, &roundup);
/* prefer variables, that have already been soft rounded but failed to get integral */
varidx = SCIPvarGetProbindex(var);
assert(0 <= varidx && varidx < nvars);
if( roundings[varidx] != 0 )
pscostquot *= 1000.0;
/* check, if candidate is new best candidate: prefer unroundable candidates in any case */
if( bestcandmayrounddown || bestcandmayroundup || pscostquot > bestpscostquot )
{
bestcand = c;
bestpscostquot = pscostquot;
bestcandmayrounddown = FALSE;
bestcandmayroundup = FALSE;
bestcandroundup = roundup;
}
}
}
assert(bestcand != -1);
/* if all candidates are roundable, try to round the solution */
if( bestcandmayrounddown || bestcandmayroundup )
{
SCIP_Bool success;
/* create solution from diving LP and try to round it */
SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) );
if( success )
{
SCIPdebugMessage("objpscostdiving found roundable primal solution: obj=%g\n",
SCIPgetSolOrigObj(scip, heurdata->sol));
/* try to add solution to SCIP */
SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );
/* check, if solution was feasible and good enough */
if( success )
{
SCIPdebugMessage(" -> solution was feasible and good enough\n");
*result = SCIP_FOUNDSOL;
}
}
}
var = lpcands[bestcand];
/* check, if the best candidate was already subject to soft rounding */
varidx = SCIPvarGetProbindex(var);
assert(0 <= varidx && varidx < nvars);
if( roundings[varidx] == +1 )
{
/* variable was already soft rounded upwards: hard round it downwards */
SCIP_CALL( SCIPchgVarUbDive(scip, var, SCIPfeasFloor(scip, lpcandssol[bestcand])) );
SCIPdebugMessage(" dive %d/%d: var <%s>, round=%u/%u, sol=%g, was already soft rounded upwards -> bounds=[%g,%g]\n",
divedepth, maxdivedepth, SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var));
}
else if( roundings[varidx] == -1 )
{
/* variable was already soft rounded downwards: hard round it upwards */
SCIP_CALL( SCIPchgVarLbDive(scip, var, SCIPfeasCeil(scip, lpcandssol[bestcand])) );
SCIPdebugMessage(" dive %d/%d: var <%s>, round=%u/%u, sol=%g, was already soft rounded downwards -> bounds=[%g,%g]\n",
divedepth, maxdivedepth, SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var));
}
else
{
assert(roundings[varidx] == 0);
/* apply soft rounding of best candidate via a change in the objective value */
objscale = divedepth * 1000.0;
oldobj = SCIPgetVarObjDive(scip, var);
if( bestcandroundup )
{
/* soft round variable up: make objective value (more) negative */
if( oldobj < 0.0 )
newobj = objscale * oldobj;
else
newobj = -objscale * oldobj;
newobj = MIN(newobj, -objscale);
/* remember, that this variable was soft rounded upwards */
roundings[varidx] = +1;
}
else
{
/* soft round variable down: make objective value (more) positive */
if( oldobj > 0.0 )
newobj = objscale * oldobj;
else
newobj = -objscale * oldobj;
newobj = MAX(newobj, objscale);
/* remember, that this variable was soft rounded downwards */
roundings[varidx] = -1;
}
SCIP_CALL( SCIPchgVarObjDive(scip, var, newobj) );
SCIPdebugMessage(" dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT": var <%s>, round=%u/%u, sol=%g, bounds=[%g,%g], obj=%g, newobj=%g\n",
divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations,
SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
lpcandssol[bestcand], SCIPgetVarLbDive(scip, var), SCIPgetVarUbDive(scip, var), oldobj, newobj);
}
/* resolve the diving LP */
nlpiterations = SCIPgetNLPIterations(scip);
retcode = SCIPsolveDiveLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, NULL);
lpsolstat = SCIPgetLPSolstat(scip);
/* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic.
* Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
if( lpsolstat != SCIP_LPSOLSTAT_UNBOUNDEDRAY )
{
SCIP_CALL( retcode );
}
#endif
SCIPwarningMessage(scip, "Error while solving LP in Objpscostdiving heuristic; LP solve terminated with code <%d>\n", retcode);
SCIPwarningMessage(scip, "This does not affect the remaining solution procedure --> continue\n");
}
if( lperror )
break;
/* update iteration count */
heurdata->nlpiterations += SCIPgetNLPIterations(scip) - nlpiterations;
/* get LP solution status and fractional variables, that should be integral */
if( lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
{
/* get new fractional variables */
SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) );
}
SCIPdebugMessage(" -> lpsolstat=%d, nfrac=%d\n", lpsolstat, nlpcands);
}
/* check if a solution has been found */
if( nlpcands == 0 && !lperror && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
{
SCIP_Bool success;
/* create solution from diving LP */
SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
SCIPdebugMessage("objpscostdiving found primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol));
/* try to add solution to SCIP */
SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );
/* check, if solution was feasible and good enough */
if( success )
{
SCIPdebugMessage(" -> solution was feasible and good enough\n");
*result = SCIP_FOUNDSOL;
}
}
/* end diving */
SCIP_CALL( SCIPendDive(scip) );
if( *result == SCIP_FOUNDSOL )
heurdata->nsuccess++;
/* free temporary memory for remembering the current soft roundings */
SCIPfreeBufferArray(scip, &roundings);
SCIPdebugMessage("objpscostdiving heuristic finished\n");
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecActconsdiving) /*lint --e{715}*/
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_LPSOLSTAT lpsolstat;
SCIP_VAR* var;
SCIP_VAR** lpcands;
SCIP_Real* lpcandssol;
SCIP_Real* lpcandsfrac;
SCIP_Real searchubbound;
SCIP_Real searchavgbound;
SCIP_Real searchbound;
SCIP_Real objval;
SCIP_Real oldobjval;
SCIP_Real frac;
SCIP_Real bestfrac;
SCIP_Bool bestcandmayrounddown;
SCIP_Bool bestcandmayroundup;
SCIP_Bool bestcandroundup;
SCIP_Bool mayrounddown;
SCIP_Bool mayroundup;
SCIP_Bool roundup;
SCIP_Bool lperror;
SCIP_Bool cutoff;
SCIP_Bool backtracked;
SCIP_Longint ncalls;
SCIP_Longint nsolsfound;
SCIP_Longint nlpiterations;
SCIP_Longint maxnlpiterations;
int nlpcands;
int startnlpcands;
int depth;
int maxdepth;
int maxdivedepth;
int divedepth;
SCIP_Real actscore;
SCIP_Real downscore;
SCIP_Real upscore;
SCIP_Real bestactscore;
int bestcand;
int c;
assert(heur != NULL);
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
assert(SCIPhasCurrentNodeLP(scip));
*result = SCIP_DELAYED;
/* do not call heuristic of node was already detected to be infeasible */
if( nodeinfeasible )
return SCIP_OKAY;
/* only call heuristic, if an optimal LP solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call heuristic, if the LP objective value is smaller than the cutoff bound */
if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
return SCIP_OKAY;
/* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */
if( !SCIPisLPSolBasic(scip) )
return SCIP_OKAY;
/* don't dive two times at the same node */
if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */
depth = SCIPgetDepth(scip);
maxdepth = SCIPgetMaxDepth(scip);
maxdepth = MAX(maxdepth, 30);
if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth )
return SCIP_OKAY;
/* calculate the maximal number of LP iterations until heuristic is aborted */
nlpiterations = SCIPgetNNodeLPIterations(scip);
ncalls = SCIPheurGetNCalls(heur);
nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess;
maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations);
maxnlpiterations += heurdata->maxlpiterofs;
/* don't try to dive, if we took too many LP iterations during diving */
if( heurdata->nlpiterations >= maxnlpiterations )
return SCIP_OKAY;
/* allow at least a certain number of LP iterations in this dive */
maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER);
/* get fractional variables that should be integral */
SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) );
/* don't try to dive, if there are no fractional variables */
if( nlpcands == 0 )
return SCIP_OKAY;
/* calculate the objective search bound */
if( SCIPgetNSolsFound(scip) == 0 )
{
if( heurdata->maxdiveubquotnosol > 0.0 )
searchubbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveubquotnosol * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip));
else
searchubbound = SCIPinfinity(scip);
if( heurdata->maxdiveavgquotnosol > 0.0 )
searchavgbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveavgquotnosol * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip));
else
searchavgbound = SCIPinfinity(scip);
}
else
{
if( heurdata->maxdiveubquot > 0.0 )
searchubbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveubquot * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip));
else
searchubbound = SCIPinfinity(scip);
if( heurdata->maxdiveavgquot > 0.0 )
searchavgbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveavgquot * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip));
else
searchavgbound = SCIPinfinity(scip);
}
searchbound = MIN(searchubbound, searchavgbound);
if( SCIPisObjIntegral(scip) )
searchbound = SCIPceil(scip, searchbound);
/* calculate the maximal diving depth: 10 * min{number of integer variables, max depth} */
maxdivedepth = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip);
maxdivedepth = MIN(maxdivedepth, maxdepth);
maxdivedepth *= 10;
*result = SCIP_DIDNOTFIND;
/* start diving */
SCIP_CALL( SCIPstartProbing(scip) );
/* enables collection of variable statistics during probing */
SCIPenableVarHistory(scip);
/* get LP objective value */
lpsolstat = SCIP_LPSOLSTAT_OPTIMAL;
objval = SCIPgetLPObjval(scip);
SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") executing actconsdiving heuristic: depth=%d, %d fractionals, dualbound=%g, avgbound=%g, cutoffbound=%g, searchbound=%g\n",
SCIPgetNNodes(scip), SCIPgetDepth(scip), nlpcands, SCIPgetDualbound(scip), SCIPgetAvgDualbound(scip),
SCIPretransformObj(scip, SCIPgetCutoffbound(scip)), SCIPretransformObj(scip, searchbound));
/* dive as long we are in the given objective, depth and iteration limits and fractional variables exist, but
* - if possible, we dive at least with the depth 10
* - if the number of fractional variables decreased at least with 1 variable per 2 dive depths, we continue diving
*/
lperror = FALSE;
cutoff = FALSE;
divedepth = 0;
bestcandmayrounddown = FALSE;
bestcandmayroundup = FALSE;
startnlpcands = nlpcands;
while( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL && nlpcands > 0
&& (divedepth < 10
|| nlpcands <= startnlpcands - divedepth/2
|| (divedepth < maxdivedepth && heurdata->nlpiterations < maxnlpiterations && objval < searchbound))
&& !SCIPisStopped(scip) )
{
divedepth++;
SCIP_CALL( SCIPnewProbingNode(scip) );
/* choose variable fixing:
* - prefer variables that may not be rounded without destroying LP feasibility:
* - of these variables, round variable with least number of locks in corresponding direction
* - if all remaining fractional variables may be rounded without destroying LP feasibility:
* - round variable with least number of locks in opposite of its feasible rounding direction
*/
bestcand = -1;
bestactscore = -1.0;
bestfrac = SCIP_INVALID;
bestcandmayrounddown = TRUE;
bestcandmayroundup = TRUE;
bestcandroundup = FALSE;
for( c = 0; c < nlpcands; ++c )
{
var = lpcands[c];
mayrounddown = SCIPvarMayRoundDown(var);
mayroundup = SCIPvarMayRoundUp(var);
frac = lpcandsfrac[c];
if( mayrounddown || mayroundup )
{
/* the candidate may be rounded: choose this candidate only, if the best candidate may also be rounded */
if( bestcandmayrounddown || bestcandmayroundup )
{
/* choose rounding direction:
* - if variable may be rounded in both directions, round corresponding to the fractionality
* - otherwise, round in the infeasible direction, because feasible direction is tried by rounding
* the current fractional solution
*/
if( mayrounddown && mayroundup )
roundup = (frac > 0.5);
else
roundup = mayrounddown;
if( roundup )
frac = 1.0 - frac;
actscore = getNActiveConsScore(scip, var, &downscore, &upscore);
/* penalize too small fractions */
if( frac < 0.01 )
actscore *= 0.01;
/* prefer decisions on binary variables */
if( !SCIPvarIsBinary(var) )
actscore *= 0.01;
/* check, if candidate is new best candidate */
assert(0.0 < frac && frac < 1.0);
if( SCIPisGT(scip, actscore, bestactscore) || (SCIPisGE(scip, actscore, bestactscore) && frac < bestfrac) )
{
bestcand = c;
bestactscore = actscore;
bestfrac = frac;
bestcandmayrounddown = mayrounddown;
bestcandmayroundup = mayroundup;
bestcandroundup = roundup;
}
}
}
else
{
/* the candidate may not be rounded */
actscore = getNActiveConsScore(scip, var, &downscore, &upscore);
roundup = (downscore < upscore);
if( roundup )
frac = 1.0 - frac;
/* penalize too small fractions */
if( frac < 0.01 )
actscore *= 0.01;
/* prefer decisions on binary variables */
if( !SCIPvarIsBinary(var) )
actscore *= 0.01;
/* check, if candidate is new best candidate: prefer unroundable candidates in any case */
assert(0.0 < frac && frac < 1.0);
if( bestcandmayrounddown || bestcandmayroundup || SCIPisGT(scip, actscore, bestactscore) ||
(SCIPisGE(scip, actscore, bestactscore) && frac < bestfrac) )
{
bestcand = c;
bestactscore = actscore;
bestfrac = frac;
bestcandmayrounddown = FALSE;
bestcandmayroundup = FALSE;
bestcandroundup = roundup;
}
assert(bestfrac < SCIP_INVALID);
}
}
assert(bestcand != -1);
/* if all candidates are roundable, try to round the solution */
if( bestcandmayrounddown || bestcandmayroundup )
{
SCIP_Bool success;
/* create solution from diving LP and try to round it */
SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) );
if( success )
{
SCIPdebugMessage("actconsdiving found roundable primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol));
/* try to add solution to SCIP */
SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );
/* check, if solution was feasible and good enough */
if( success )
{
SCIPdebugMessage(" -> solution was feasible and good enough\n");
*result = SCIP_FOUNDSOL;
}
}
}
assert(bestcand != -1);
var = lpcands[bestcand];
backtracked = FALSE;
do
{
/* if the variable is already fixed or if the solution value is outside the domain, numerical troubles may have
* occured or variable was fixed by propagation while backtracking => Abort diving!
*/
if( SCIPvarGetLbLocal(var) >= SCIPvarGetUbLocal(var) - 0.5 )
{
SCIPdebugMessage("Selected variable <%s> already fixed to [%g,%g] (solval: %.9f), diving aborted \n",
SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), lpcandssol[bestcand]);
cutoff = TRUE;
break;
}
if( SCIPisFeasLT(scip, lpcandssol[bestcand], SCIPvarGetLbLocal(var)) || SCIPisFeasGT(scip, lpcandssol[bestcand], SCIPvarGetUbLocal(var)) )
{
SCIPdebugMessage("selected variable's <%s> solution value is outside the domain [%g,%g] (solval: %.9f), diving aborted\n",
SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), lpcandssol[bestcand]);
assert(backtracked);
break;
}
/* apply rounding of best candidate */
if( bestcandroundup == !backtracked )
{
/* round variable up */
SCIPdebugMessage(" dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT": var <%s>, round=%u/%u, sol=%g, oldbounds=[%g,%g], newbounds=[%g,%g]\n",
divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations,
SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
lpcandssol[bestcand], SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var),
SCIPfeasCeil(scip, lpcandssol[bestcand]), SCIPvarGetUbLocal(var));
SCIP_CALL( SCIPchgVarLbProbing(scip, var, SCIPfeasCeil(scip, lpcandssol[bestcand])) );
}
else
{
/* round variable down */
SCIPdebugMessage(" dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT": var <%s>, round=%u/%u, sol=%g, oldbounds=[%g,%g], newbounds=[%g,%g]\n",
divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations,
SCIPvarGetName(var), bestcandmayrounddown, bestcandmayroundup,
lpcandssol[bestcand], SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var),
SCIPvarGetLbLocal(var), SCIPfeasFloor(scip, lpcandssol[bestcand]));
SCIP_CALL( SCIPchgVarUbProbing(scip, lpcands[bestcand], SCIPfeasFloor(scip, lpcandssol[bestcand])) );
}
/* apply domain propagation */
SCIP_CALL( SCIPpropagateProbing(scip, 0, &cutoff, NULL) );
if( !cutoff )
{
/* resolve the diving LP */
/* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic.
* Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
#ifdef NDEBUG
SCIP_RETCODE retstat;
nlpiterations = SCIPgetNLPIterations(scip);
retstat = SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff);
if( retstat != SCIP_OKAY )
{
SCIPwarningMessage(scip, "Error while solving LP in Actconsdiving heuristic; LP solve terminated with code <%d>\n",retstat);
}
#else
nlpiterations = SCIPgetNLPIterations(scip);
SCIP_CALL( SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff) );
#endif
if( lperror )
break;
/* update iteration count */
heurdata->nlpiterations += SCIPgetNLPIterations(scip) - nlpiterations;
/* get LP solution status, objective value, and fractional variables, that should be integral */
lpsolstat = SCIPgetLPSolstat(scip);
assert(cutoff || (lpsolstat != SCIP_LPSOLSTAT_OBJLIMIT && lpsolstat != SCIP_LPSOLSTAT_INFEASIBLE &&
(lpsolstat != SCIP_LPSOLSTAT_OPTIMAL || SCIPisLT(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)))));
}
/* perform backtracking if a cutoff was detected */
if( cutoff && !backtracked && heurdata->backtrack )
{
SCIPdebugMessage(" *** cutoff detected at level %d - backtracking\n", SCIPgetProbingDepth(scip));
SCIP_CALL( SCIPbacktrackProbing(scip, SCIPgetProbingDepth(scip)-1) );
SCIP_CALL( SCIPnewProbingNode(scip) );
backtracked = TRUE;
}
else
backtracked = FALSE;
}
while( backtracked );
if( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
{
/* get new objective value */
oldobjval = objval;
objval = SCIPgetLPObjval(scip);
/* update pseudo cost values */
if( SCIPisGT(scip, objval, oldobjval) )
{
if( bestcandroundup )
{
SCIP_CALL( SCIPupdateVarPseudocost(scip, lpcands[bestcand], 1.0-lpcandsfrac[bestcand],
objval - oldobjval, 1.0) );
}
else
{
SCIP_CALL( SCIPupdateVarPseudocost(scip, lpcands[bestcand], 0.0-lpcandsfrac[bestcand],
objval - oldobjval, 1.0) );
}
}
/* get new fractional variables */
SCIP_CALL( SCIPgetLPBranchCands(scip, &lpcands, &lpcandssol, &lpcandsfrac, &nlpcands, NULL, NULL) );
}
SCIPdebugMessage(" -> lpsolstat=%d, objval=%g/%g, nfrac=%d\n", lpsolstat, objval, searchbound, nlpcands);
}
/* check if a solution has been found */
if( nlpcands == 0 && !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
{
SCIP_Bool success;
/* create solution from diving LP */
SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
SCIPdebugMessage("actconsdiving found primal solution: obj=%g\n", SCIPgetSolOrigObj(scip, heurdata->sol));
/* try to add solution to SCIP */
SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );
/* check, if solution was feasible and good enough */
if( success )
{
SCIPdebugMessage(" -> solution was feasible and good enough\n");
*result = SCIP_FOUNDSOL;
}
}
/* end diving */
SCIP_CALL( SCIPendProbing(scip) );
if( *result == SCIP_FOUNDSOL )
heurdata->nsuccess++;
SCIPdebugMessage("(node %"SCIP_LONGINT_FORMAT") finished actconsdiving heuristic: %d fractionals, dive %d/%d, LP iter %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT", objval=%g/%g, lpsolstat=%d, cutoff=%u\n",
SCIPgetNNodes(scip), nlpcands, divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations,
SCIPretransformObj(scip, objval), SCIPretransformObj(scip, searchbound), lpsolstat, cutoff);
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecOneopt)
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_SOL* bestsol; /* incumbent solution */
SCIP_SOL* worksol; /* heuristic's working solution */
SCIP_VAR** vars; /* SCIP variables */
SCIP_VAR** shiftcands; /* shiftable variables */
SCIP_ROW** lprows; /* SCIP LP rows */
SCIP_Real* activities; /* row activities for working solution */
SCIP_Real* shiftvals;
SCIP_Real lb;
SCIP_Real ub;
SCIP_Bool localrows;
SCIP_Bool valid;
int nchgbound;
int nbinvars;
int nintvars;
int nvars;
int nlprows;
int i;
int nshiftcands;
int shiftcandssize;
SCIP_RETCODE retcode;
assert(heur != NULL);
assert(scip != NULL);
assert(result != NULL);
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
*result = SCIP_DELAYED;
/* we only want to process each solution once */
bestsol = SCIPgetBestSol(scip);
if( bestsol == NULL || heurdata->lastsolindex == SCIPsolGetIndex(bestsol) )
return SCIP_OKAY;
/* reset the timing mask to its default value (at the root node it could be different) */
if( SCIPgetNNodes(scip) > 1 )
SCIPheurSetTimingmask(heur, HEUR_TIMING);
/* get problem variables */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
nintvars += nbinvars;
/* do not run if there are no discrete variables */
if( nintvars == 0 )
{
*result = SCIP_DIDNOTRUN;
return SCIP_OKAY;
}
if( heurtiming == SCIP_HEURTIMING_BEFOREPRESOL )
{
SCIP* subscip; /* the subproblem created by zeroobj */
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_Real* subsolvals; /* solution values of the subproblem */
SCIP_Real timelimit; /* time limit for zeroobj subproblem */
SCIP_Real memorylimit; /* memory limit for zeroobj subproblem */
SCIP_SOL* startsol;
SCIP_SOL** subsols;
int nsubsols;
if( !heurdata->beforepresol )
return SCIP_OKAY;
/* check whether there is enough time and memory left */
timelimit = 0.0;
memorylimit = 0.0;
SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
if( !SCIPisInfinity(scip, timelimit) )
timelimit -= SCIPgetSolvingTime(scip);
SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
/* substract the memory already used by the main SCIP and the estimated memory usage of external software */
if( !SCIPisInfinity(scip, memorylimit) )
{
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
}
/* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
return SCIP_OKAY;
/* initialize the subproblem */
SCIP_CALL( SCIPcreate(&subscip) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
/* copy complete SCIP instance */
valid = FALSE;
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "oneopt", TRUE, FALSE, TRUE, &valid) );
SCIP_CALL( SCIPtransformProb(subscip) );
/* get variable image */
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
/* copy the solution */
SCIP_CALL( SCIPallocBufferArray(scip, &subsolvals, nvars) );
SCIP_CALL( SCIPgetSolVals(scip, bestsol, nvars, vars, subsolvals) );
/* create start solution for the subproblem */
SCIP_CALL( SCIPcreateOrigSol(subscip, &startsol, NULL) );
SCIP_CALL( SCIPsetSolVals(subscip, startsol, nvars, subvars, subsolvals) );
/* try to add new solution to sub-SCIP and free it immediately */
valid = FALSE;
SCIP_CALL( SCIPtrySolFree(subscip, &startsol, FALSE, FALSE, FALSE, FALSE, &valid) );
SCIPfreeBufferArray(scip, &subsolvals);
SCIPhashmapFree(&varmapfw);
/* disable statistic timing inside sub SCIP */
SCIP_CALL( SCIPsetBoolParam(subscip, "timing/statistictiming", FALSE) );
/* deactivate basically everything except oneopt in the sub-SCIP */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
SCIP_CALL( SCIPsetHeuristics(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", 1LL) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
/* if necessary, some of the parameters have to be unfixed first */
if( SCIPisParamFixed(subscip, "lp/solvefreq") )
{
SCIPwarningMessage(scip, "unfixing parameter lp/solvefreq in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "lp/solvefreq") );
}
SCIP_CALL( SCIPsetIntParam(subscip, "lp/solvefreq", -1) );
if( SCIPisParamFixed(subscip, "heuristics/oneopt/freq") )
{
SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/freq in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/freq") );
}
SCIP_CALL( SCIPsetIntParam(subscip, "heuristics/oneopt/freq", 1) );
if( SCIPisParamFixed(subscip, "heuristics/oneopt/forcelpconstruction") )
{
SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/forcelpconstruction in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/forcelpconstruction") );
}
SCIP_CALL( SCIPsetBoolParam(subscip, "heuristics/oneopt/forcelpconstruction", TRUE) );
/* avoid recursive call, which would lead to an endless loop */
if( SCIPisParamFixed(subscip, "heuristics/oneopt/beforepresol") )
{
SCIPwarningMessage(scip, "unfixing parameter heuristics/oneopt/beforepresol in subscip of oneopt heuristic\n");
SCIP_CALL( SCIPunfixParam(subscip, "heuristics/oneopt/beforepresol") );
}
SCIP_CALL( SCIPsetBoolParam(subscip, "heuristics/oneopt/beforepresol", FALSE) );
if( valid )
{
retcode = SCIPsolve(subscip);
/* errors in solving the subproblem should not kill the overall solving process;
* hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage(scip, "Error while solving subproblem in zeroobj heuristic; sub-SCIP terminated with code <%d>\n",retcode);
}
#ifdef SCIP_DEBUG
SCIP_CALL( SCIPprintStatistics(subscip, NULL) );
#endif
}
/* check, whether a solution was found;
* due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
*/
nsubsols = SCIPgetNSols(subscip);
subsols = SCIPgetSols(subscip);
valid = FALSE;
for( i = 0; i < nsubsols && !valid; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &valid) );
if( valid )
*result = SCIP_FOUNDSOL;
}
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/* we can only work on solutions valid in the transformed space */
if( SCIPsolIsOriginal(bestsol) )
return SCIP_OKAY;
if( heurtiming == SCIP_HEURTIMING_BEFORENODE && (SCIPhasCurrentNodeLP(scip) || heurdata->forcelpconstruction) )
{
SCIP_Bool cutoff;
cutoff = FALSE;
SCIP_CALL( SCIPconstructLP(scip, &cutoff) );
SCIP_CALL( SCIPflushLP(scip) );
/* get problem variables again, SCIPconstructLP() might have added new variables */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
nintvars += nbinvars;
}
/* we need an LP */
if( SCIPgetNLPRows(scip) == 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
nchgbound = 0;
/* initialize data */
nshiftcands = 0;
shiftcandssize = 8;
heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
SCIP_CALL( SCIPcreateSolCopy(scip, &worksol, bestsol) );
SCIPsolSetHeur(worksol,heur);
SCIPdebugMessage("Starting bound adjustment in 1-opt heuristic\n");
/* maybe change solution values due to global bound changes first */
for( i = nvars - 1; i >= 0; --i )
{
SCIP_VAR* var;
SCIP_Real solval;
var = vars[i];
lb = SCIPvarGetLbGlobal(var);
ub = SCIPvarGetUbGlobal(var);
solval = SCIPgetSolVal(scip, bestsol,var);
/* old solution value is smaller than the actual lower bound */
if( SCIPisFeasLT(scip, solval, lb) )
{
/* set the solution value to the global lower bound */
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, lb) );
++nchgbound;
SCIPdebugMessage("var <%s> type %d, old solval %g now fixed to lb %g\n", SCIPvarGetName(var), SCIPvarGetType(var), solval, lb);
}
/* old solution value is greater than the actual upper bound */
else if( SCIPisFeasGT(scip, solval, SCIPvarGetUbGlobal(var)) )
{
/* set the solution value to the global upper bound */
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, ub) );
++nchgbound;
SCIPdebugMessage("var <%s> type %d, old solval %g now fixed to ub %g\n", SCIPvarGetName(var), SCIPvarGetType(var), solval, ub);
}
}
SCIPdebugMessage("number of bound changes (due to global bounds) = %d\n", nchgbound);
SCIP_CALL( SCIPgetLPRowsData(scip, &lprows, &nlprows) );
SCIP_CALL( SCIPallocBufferArray(scip, &activities, nlprows) );
localrows = FALSE;
valid = TRUE;
/* initialize activities */
for( i = 0; i < nlprows; ++i )
{
SCIP_ROW* row;
row = lprows[i];
assert(SCIProwGetLPPos(row) == i);
if( !SCIProwIsLocal(row) )
{
activities[i] = SCIPgetRowSolActivity(scip, row, worksol);
SCIPdebugMessage("Row <%s> has activity %g\n", SCIProwGetName(row), activities[i]);
if( SCIPisFeasLT(scip, activities[i], SCIProwGetLhs(row)) || SCIPisFeasGT(scip, activities[i], SCIProwGetRhs(row)) )
{
valid = FALSE;
SCIPdebug( SCIP_CALL( SCIPprintRow(scip, row, NULL) ) );
SCIPdebugMessage("row <%s> activity %g violates bounds, lhs = %g, rhs = %g\n", SCIProwGetName(row), activities[i], SCIProwGetLhs(row), SCIProwGetRhs(row));
break;
}
}
else
localrows = TRUE;
}
if( !valid )
{
/** @todo try to correct lp rows */
SCIPdebugMessage("Some global bound changes were not valid in lp rows.\n");
goto TERMINATE;
}
SCIP_CALL( SCIPallocBufferArray(scip, &shiftcands, shiftcandssize) );
SCIP_CALL( SCIPallocBufferArray(scip, &shiftvals, shiftcandssize) );
SCIPdebugMessage("Starting 1-opt heuristic\n");
/* enumerate all integer variables and find out which of them are shiftable */
for( i = 0; i < nintvars; i++ )
{
if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
{
SCIP_Real shiftval;
SCIP_Real solval;
/* find out whether the variable can be shifted */
solval = SCIPgetSolVal(scip, worksol, vars[i]);
shiftval = calcShiftVal(scip, vars[i], solval, activities);
/* insert the variable into the list of shifting candidates */
if( !SCIPisFeasZero(scip, shiftval) )
{
SCIPdebugMessage(" -> Variable <%s> can be shifted by <%1.1f> \n", SCIPvarGetName(vars[i]), shiftval);
if( nshiftcands == shiftcandssize)
{
shiftcandssize *= 8;
SCIP_CALL( SCIPreallocBufferArray(scip, &shiftcands, shiftcandssize) );
SCIP_CALL( SCIPreallocBufferArray(scip, &shiftvals, shiftcandssize) );
}
shiftcands[nshiftcands] = vars[i];
shiftvals[nshiftcands] = shiftval;
nshiftcands++;
}
}
}
/* if at least one variable can be shifted, shift variables sorted by their objective */
if( nshiftcands > 0 )
{
SCIP_Real shiftval;
SCIP_Real solval;
SCIP_VAR* var;
/* the case that exactly one variable can be shifted is slightly easier */
if( nshiftcands == 1 )
{
var = shiftcands[0];
assert(var != NULL);
solval = SCIPgetSolVal(scip, worksol, var);
shiftval = shiftvals[0];
assert(!SCIPisFeasZero(scip,shiftval));
SCIPdebugMessage(" Only one shiftcand found, var <%s>, which is now shifted by<%1.1f> \n",
SCIPvarGetName(var), shiftval);
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, solval+shiftval) );
}
else
{
SCIP_Real* objcoeffs;
SCIP_CALL( SCIPallocBufferArray(scip, &objcoeffs, nshiftcands) );
SCIPdebugMessage(" %d shiftcands found \n", nshiftcands);
/* sort the variables by their objective, optionally weighted with the shiftval */
if( heurdata->weightedobj )
{
for( i = 0; i < nshiftcands; ++i )
objcoeffs[i] = SCIPvarGetObj(shiftcands[i])*shiftvals[i];
}
else
{
for( i = 0; i < nshiftcands; ++i )
objcoeffs[i] = SCIPvarGetObj(shiftcands[i]);
}
/* sort arrays with respect to the first one */
SCIPsortRealPtr(objcoeffs, (void**)shiftcands, nshiftcands);
/* try to shift each variable -> Activities have to be updated */
for( i = 0; i < nshiftcands; ++i )
{
var = shiftcands[i];
assert(var != NULL);
solval = SCIPgetSolVal(scip, worksol, var);
shiftval = calcShiftVal(scip, var, solval, activities);
SCIPdebugMessage(" -> Variable <%s> is now shifted by <%1.1f> \n", SCIPvarGetName(vars[i]), shiftval);
assert(i > 0 || !SCIPisFeasZero(scip, shiftval));
assert(SCIPisFeasGE(scip, solval+shiftval, SCIPvarGetLbGlobal(var)) && SCIPisFeasLE(scip, solval+shiftval, SCIPvarGetUbGlobal(var)));
SCIP_CALL( SCIPsetSolVal(scip, worksol, var, solval+shiftval) );
SCIP_CALL( updateRowActivities(scip, activities, var, shiftval) );
}
SCIPfreeBufferArray(scip, &objcoeffs);
}
/* if the problem is a pure IP, try to install the solution, if it is a MIP, solve LP again to set the continuous
* variables to the best possible value
*/
if( nvars == nintvars || !SCIPhasCurrentNodeLP(scip) || SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
{
SCIP_Bool success;
/* since we ignore local rows, we cannot guarantee their feasibility and have to set the checklprows flag to
* TRUE if local rows are present
*/
SCIP_CALL( SCIPtrySol(scip, worksol, FALSE, FALSE, FALSE, localrows, &success) );
if( success )
{
SCIPdebugMessage("found feasible shifted solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, worksol, NULL, FALSE) ) );
heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
*result = SCIP_FOUNDSOL;
}
}
else
{
SCIP_Bool lperror;
#ifdef NDEBUG
SCIP_RETCODE retstat;
#endif
SCIPdebugMessage("shifted solution should be feasible -> solve LP to fix continuous variables to best values\n");
/* start diving to calculate the LP relaxation */
SCIP_CALL( SCIPstartDive(scip) );
/* set the bounds of the variables: fixed for integers, global bounds for continuous */
for( i = 0; i < nvars; ++i )
{
if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
{
SCIP_CALL( SCIPchgVarLbDive(scip, vars[i], SCIPvarGetLbGlobal(vars[i])) );
SCIP_CALL( SCIPchgVarUbDive(scip, vars[i], SCIPvarGetUbGlobal(vars[i])) );
}
}
/* apply this after global bounds to not cause an error with intermediate empty domains */
for( i = 0; i < nintvars; ++i )
{
if( SCIPvarGetStatus(vars[i]) == SCIP_VARSTATUS_COLUMN )
{
solval = SCIPgetSolVal(scip, worksol, vars[i]);
SCIP_CALL( SCIPchgVarLbDive(scip, vars[i], solval) );
SCIP_CALL( SCIPchgVarUbDive(scip, vars[i], solval) );
}
}
/* solve LP */
SCIPdebugMessage(" -> old LP iterations: %" SCIP_LONGINT_FORMAT "\n", SCIPgetNLPIterations(scip));
/**@todo in case of an MINLP, if SCIPisNLPConstructed() is TRUE, say, rather solve the NLP instead of the LP */
/* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic.
* Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
#ifdef NDEBUG
retstat = SCIPsolveDiveLP(scip, -1, &lperror, NULL);
if( retstat != SCIP_OKAY )
{
SCIPwarningMessage(scip, "Error while solving LP in Oneopt heuristic; LP solve terminated with code <%d>\n",retstat);
}
#else
SCIP_CALL( SCIPsolveDiveLP(scip, -1, &lperror, NULL) );
#endif
SCIPdebugMessage(" -> new LP iterations: %" SCIP_LONGINT_FORMAT "\n", SCIPgetNLPIterations(scip));
SCIPdebugMessage(" -> error=%u, status=%d\n", lperror, SCIPgetLPSolstat(scip));
/* check if this is a feasible solution */
if( !lperror && SCIPgetLPSolstat(scip) == SCIP_LPSOLSTAT_OPTIMAL )
{
SCIP_Bool success;
/* copy the current LP solution to the working solution */
SCIP_CALL( SCIPlinkLPSol(scip, worksol) );
SCIP_CALL( SCIPtrySol(scip, worksol, FALSE, FALSE, FALSE, FALSE, &success) );
/* check solution for feasibility */
if( success )
{
SCIPdebugMessage("found feasible shifted solution:\n");
SCIPdebug( SCIP_CALL( SCIPprintSol(scip, worksol, NULL, FALSE) ) );
heurdata->lastsolindex = SCIPsolGetIndex(bestsol);
*result = SCIP_FOUNDSOL;
}
}
/* terminate the diving */
SCIP_CALL( SCIPendDive(scip) );
}
}
SCIPdebugMessage("Finished 1-opt heuristic\n");
SCIPfreeBufferArray(scip, &shiftvals);
SCIPfreeBufferArray(scip, &shiftcands);
TERMINATE:
SCIPfreeBufferArray(scip, &activities);
SCIP_CALL( SCIPfreeSol(scip, &worksol) );
return SCIP_OKAY;
}
/** reads an BLK file */
static
SCIP_RETCODE readBLKFile(
SCIP* scip, /**< SCIP data structure */
SCIP_READER* reader, /**< reader data structure */
BLKINPUT* blkinput, /**< BLK reading data */
const char* filename /**< name of the input file */
)
{
DEC_DECOMP *decdecomp;
int i;
int nconss;
int nblocksread;
int nvars;
SCIP_READERDATA* readerdata;
SCIP_CONS** conss;
nblocksread = FALSE;
assert(scip != NULL);
assert(reader != NULL);
assert(blkinput != NULL);
if( SCIPgetStage(scip) < SCIP_STAGE_TRANSFORMED )
SCIP_CALL( SCIPtransformProb(scip) );
readerdata = SCIPreaderGetData(reader);
assert(readerdata != NULL);
readerdata->nlinkingcons = SCIPgetNConss(scip);
readerdata->nlinkingvars = 0;
nvars = SCIPgetNVars(scip);
conss = SCIPgetConss(scip);
nconss = SCIPgetNConss(scip);
/* alloc: var -> block mapping */
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->varstoblock, nvars) );
for( i = 0; i < nvars; i ++ )
{
readerdata->varstoblock[i] = NOVALUE;
}
/* alloc: linkingvar -> blocks mapping */
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->linkingvarsblocks, nvars) );
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->nlinkingvarsblocks, nvars) );
BMSclearMemoryArray(readerdata->linkingvarsblocks, nvars);
BMSclearMemoryArray(readerdata->nlinkingvarsblocks, nvars);
/* cons -> block mapping */
SCIP_CALL( SCIPhashmapCreate(&readerdata->constoblock, SCIPblkmem(scip), nconss) );
for( i = 0; i < SCIPgetNConss(scip); i ++ )
{
SCIP_CALL( SCIPhashmapInsert(readerdata->constoblock, conss[i], (void*)(size_t) NOVALUE) );
}
/* open file */
blkinput->file = SCIPfopen(filename, "r");
if( blkinput->file == NULL )
{
SCIPerrorMessage("cannot open file <%s> for reading\n", filename);
SCIPprintSysError(filename);
return SCIP_NOFILE;
}
/* parse the file */
blkinput->section = BLK_START;
while( blkinput->section != BLK_END && !hasError(blkinput) )
{
switch( blkinput->section )
{
case BLK_START:
SCIP_CALL( readStart(scip, blkinput) );
break;
case BLK_PRESOLVED:
SCIP_CALL( readPresolved(scip, blkinput) );
if( blkinput->presolved && SCIPgetStage(scip) < SCIP_STAGE_PRESOLVED )
{
assert(blkinput->haspresolvesection);
/** @bug GCG should be able to presolve the problem first */
SCIPverbMessage(scip, SCIP_VERBLEVEL_MINIMAL, NULL, "decomposition belongs to the presolved problem, please presolve the problem first.\n");
goto TERMINATE;
}
break;
case BLK_NBLOCKS:
SCIP_CALL( readNBlocks(scip, blkinput) );
if( blkinput->haspresolvesection && !blkinput->presolved && SCIPgetStage(scip) >= SCIP_STAGE_PRESOLVED )
{
SCIPverbMessage(scip, SCIP_VERBLEVEL_MINIMAL, NULL, "decomposition belongs to the unpresolved problem, please re-read the problem and read the decomposition without presolving.\n");
goto TERMINATE;
}
if( !blkinput->haspresolvesection )
{
SCIPwarningMessage(scip, "decomposition has no presolve section at beginning. The behaviour is undefined. See the FAQ for further information.\n");
}
break;
case BLK_BLOCK:
if( nblocksread == FALSE )
{
/* alloc n vars per block */
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->nblockvars, blkinput->nblocks) );
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->nblockcons, blkinput->nblocks) );
SCIP_CALL( SCIPallocMemoryArray(scip, &readerdata->blockcons, blkinput->nblocks) );
for( i = 0; i < blkinput->nblocks; ++i )
{
readerdata->nblockvars[i] = 0;
readerdata->nblockcons[i] = 0;
SCIP_CALL( SCIPallocMemoryArray(scip, &(readerdata->blockcons[i]), nconss) ); /*lint !e866*/
}
nblocksread = TRUE;
}
SCIP_CALL( readBlock(scip, blkinput, readerdata) );
break;
case BLK_MASTERCONSS:
SCIP_CALL( readMasterconss(scip, blkinput, readerdata) );
break;
case BLK_END: /* this is already handled in the while() loop */
default:
SCIPerrorMessage("invalid BLK file section <%d>\n", blkinput->section);
return SCIP_INVALIDDATA;
}
}
SCIP_CALL( DECdecompCreate(scip, &decdecomp) );
/* fill decomp */
SCIP_CALL( fillDecompStruct(scip, blkinput, decdecomp, readerdata) );
/* add decomp to cons_decomp */
SCIP_CALL( SCIPconshdlrDecompAddDecdecomp(scip, decdecomp) );
for( i = 0; i < nvars; ++i )
{
assert(readerdata->linkingvarsblocks[i] != NULL || readerdata->nlinkingvarsblocks[i] == 0);
if( readerdata->nlinkingvarsblocks[i] > 0 )
{
SCIPfreeMemoryArray(scip, &readerdata->linkingvarsblocks[i]);
}
}
TERMINATE:
if( nblocksread )
{
for( i = blkinput->nblocks - 1; i >= 0; --i )
{
SCIPfreeMemoryArray(scip, &(readerdata->blockcons[i]));
}
SCIPfreeMemoryArray(scip, &readerdata->blockcons);
SCIPfreeMemoryArray(scip, &readerdata->nblockcons);
SCIPfreeMemoryArray(scip, &readerdata->nblockvars);
}
SCIPhashmapFree(&readerdata->constoblock);
SCIPfreeMemoryArray(scip, &readerdata->nlinkingvarsblocks);
SCIPfreeMemoryArray(scip, &readerdata->linkingvarsblocks);
SCIPfreeMemoryArray(scip, &readerdata->varstoblock);
/* close file */
SCIPfclose(blkinput->file);
return SCIP_OKAY;
}
/** writes problem to file */
SCIP_RETCODE SCIPwritePpm(
SCIP* scip, /**< SCIP data structure */
FILE* file, /**< output file, or NULL if standard output should be used */
const char* name, /**< problem name */
SCIP_READERDATA* readerdata, /**< information for reader */
SCIP_Bool transformed, /**< TRUE iff problem is the transformed problem */
SCIP_VAR** vars, /**< array with active variables ordered binary, integer, implicit, continuous */
int nvars, /**< number of active variables in the problem */
SCIP_CONS** conss, /**< array with constraints of the problem */
int nconss, /**< number of constraints in the problem */
SCIP_RESULT* result /**< pointer to store the result of the file writing call */
)
{ /*lint --e{715}*/
int c;
int v;
int i;
int linecnt;
char linebuffer[PPM_MAX_LINELEN];
SCIP_CONSHDLR* conshdlr;
const char* conshdlrname;
SCIP_CONS* cons;
SCIP_VAR** consvars;
SCIP_Real* consvals;
int nconsvars;
int i_max = 1;
SCIP_Real maxcoef = 0;
SCIP_Bool printbool = FALSE;
assert( scip != NULL );
assert(readerdata != NULL);
/* print statistics as comment to file */
if(readerdata->rgb_ascii)
SCIPinfoMessage(scip, file, "P6\n");
else
SCIPinfoMessage(scip, file, "P3\n");
SCIPinfoMessage(scip, file, "# %s\n", name);
SCIPinfoMessage(scip, file, "%d %d\n", nvars, nconss);
SCIPinfoMessage(scip, file, "255\n");
clearLine(linebuffer, &linecnt);
if(!(readerdata->rgb_relativ))
{
i_max = 2;
}
for(i = 0; i < i_max; ++i)
{
if(i)
{
printbool = TRUE;
SCIPdebugPrintf("Maximal coefficient = %g\n", maxcoef);
}
for(c = 0; c < nconss; ++c)
{
cons = conss[c];
assert( cons != NULL);
/* in case the transformed is written only constraint are posted which are enabled in the current node */
assert(!transformed || SCIPconsIsEnabled(cons));
conshdlr = SCIPconsGetHdlr(cons);
assert( conshdlr != NULL );
conshdlrname = SCIPconshdlrGetName(conshdlr);
assert( transformed == SCIPconsIsTransformed(cons) );
if( strcmp(conshdlrname, "linear") == 0 )
{
consvars = SCIPgetVarsLinear(scip, cons);
nconsvars = SCIPgetNVarsLinear(scip, cons);
assert( consvars != NULL || nconsvars == 0 );
if( nconsvars > 0 )
{
SCIP_CALL( printLinearCons(scip, file, readerdata, consvars, SCIPgetValsLinear(scip, cons),
nconsvars, nvars, transformed, &maxcoef, printbool) );
}
}
else if( strcmp(conshdlrname, "setppc") == 0 )
{
consvars = SCIPgetVarsSetppc(scip, cons);
nconsvars = SCIPgetNVarsSetppc(scip, cons);
assert( consvars != NULL || nconsvars == 0 );
if( nconsvars > 0 )
{
SCIP_CALL( printLinearCons(scip, file, readerdata, consvars, NULL,
nconsvars, nvars, transformed, &maxcoef, printbool) );
}
}
else if( strcmp(conshdlrname, "logicor") == 0 )
{
consvars = SCIPgetVarsLogicor(scip, cons);
nconsvars = SCIPgetNVarsLogicor(scip, cons);
assert( consvars != NULL || nconsvars == 0 );
if( nconsvars > 0 )
{
SCIP_CALL( printLinearCons(scip, file, readerdata, consvars, NULL,
nconsvars, nvars, transformed, &maxcoef, printbool) );
}
}
else if( strcmp(conshdlrname, "knapsack") == 0 )
{
SCIP_Longint* weights;
consvars = SCIPgetVarsKnapsack(scip, cons);
nconsvars = SCIPgetNVarsKnapsack(scip, cons);
assert( consvars != NULL || nconsvars == 0 );
/* copy Longint array to SCIP_Real array */
weights = SCIPgetWeightsKnapsack(scip, cons);
SCIP_CALL( SCIPallocBufferArray(scip, &consvals, nconsvars) );
for( v = 0; v < nconsvars; ++v )
consvals[v] = (SCIP_Real)weights[v];
if( nconsvars > 0 )
{
SCIP_CALL( printLinearCons(scip, file, readerdata, consvars, consvals, nconsvars, nvars, transformed, &maxcoef, printbool) );
}
SCIPfreeBufferArray(scip, &consvals);
}
else if( strcmp(conshdlrname, "varbound") == 0 )
{
SCIP_CALL( SCIPallocBufferArray(scip, &consvars, 2) );
SCIP_CALL( SCIPallocBufferArray(scip, &consvals, 2) );
consvars[0] = SCIPgetVarVarbound(scip, cons);
consvars[1] = SCIPgetVbdvarVarbound(scip, cons);
consvals[0] = 1.0;
consvals[1] = SCIPgetVbdcoefVarbound(scip, cons);
SCIP_CALL( printLinearCons(scip, file, readerdata, consvars, consvals, 2, nvars, transformed, &maxcoef, printbool) );
SCIPfreeBufferArray(scip, &consvars);
SCIPfreeBufferArray(scip, &consvals);
}
else
{
SCIPwarningMessage(scip, "constraint handler <%s> cannot print requested format\n", conshdlrname );
SCIPinfoMessage(scip, file, "\\ ");
SCIP_CALL( SCIPprintCons(scip, cons, file) );
SCIPinfoMessage(scip, file, ";\n");
}
}
}
*result = SCIP_SUCCESS;
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;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecIntdiving) /*lint --e{715}*/
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata;
SCIP_LPSOLSTAT lpsolstat;
SCIP_VAR** pseudocands;
SCIP_VAR** fixcands;
SCIP_Real* fixcandscores;
SCIP_Real searchubbound;
SCIP_Real searchavgbound;
SCIP_Real searchbound;
SCIP_Real objval;
SCIP_Bool lperror;
SCIP_Bool cutoff;
SCIP_Bool backtracked;
SCIP_Longint ncalls;
SCIP_Longint nsolsfound;
SCIP_Longint nlpiterations;
SCIP_Longint maxnlpiterations;
int nfixcands;
int nbinfixcands;
int depth;
int maxdepth;
int maxdivedepth;
int divedepth;
int nextcand;
int c;
assert(heur != NULL);
assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
assert(scip != NULL);
assert(result != NULL);
assert(SCIPhasCurrentNodeLP(scip));
*result = SCIP_DELAYED;
/* do not call heuristic of node was already detected to be infeasible */
if( nodeinfeasible )
return SCIP_OKAY;
/* only call heuristic, if an optimal LP solution is at hand */
if( SCIPgetLPSolstat(scip) != SCIP_LPSOLSTAT_OPTIMAL )
return SCIP_OKAY;
/* only call heuristic, if the LP objective value is smaller than the cutoff bound */
if( SCIPisGE(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)) )
return SCIP_OKAY;
/* only call heuristic, if the LP solution is basic (which allows fast resolve in diving) */
if( !SCIPisLPSolBasic(scip) )
return SCIP_OKAY;
/* don't dive two times at the same node */
if( SCIPgetLastDivenode(scip) == SCIPgetNNodes(scip) && SCIPgetDepth(scip) > 0 )
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
/* only try to dive, if we are in the correct part of the tree, given by minreldepth and maxreldepth */
depth = SCIPgetDepth(scip);
maxdepth = SCIPgetMaxDepth(scip);
maxdepth = MAX(maxdepth, 100);
if( depth < heurdata->minreldepth*maxdepth || depth > heurdata->maxreldepth*maxdepth )
return SCIP_OKAY;
/* calculate the maximal number of LP iterations until heuristic is aborted */
nlpiterations = SCIPgetNNodeLPIterations(scip);
ncalls = SCIPheurGetNCalls(heur);
nsolsfound = 10*SCIPheurGetNBestSolsFound(heur) + heurdata->nsuccess;
maxnlpiterations = (SCIP_Longint)((1.0 + 10.0*(nsolsfound+1.0)/(ncalls+1.0)) * heurdata->maxlpiterquot * nlpiterations);
maxnlpiterations += heurdata->maxlpiterofs;
/* don't try to dive, if we took too many LP iterations during diving */
if( heurdata->nlpiterations >= maxnlpiterations )
return SCIP_OKAY;
/* allow at least a certain number of LP iterations in this dive */
maxnlpiterations = MAX(maxnlpiterations, heurdata->nlpiterations + MINLPITER);
/* get unfixed integer variables */
SCIP_CALL( SCIPgetPseudoBranchCands(scip, &pseudocands, &nfixcands, NULL) );
/* don't try to dive, if there are no fractional variables */
if( nfixcands == 0 )
return SCIP_OKAY;
/* calculate the objective search bound */
if( SCIPgetNSolsFound(scip) == 0 )
{
if( heurdata->maxdiveubquotnosol > 0.0 )
searchubbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveubquotnosol * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip));
else
searchubbound = SCIPinfinity(scip);
if( heurdata->maxdiveavgquotnosol > 0.0 )
searchavgbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveavgquotnosol * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip));
else
searchavgbound = SCIPinfinity(scip);
}
else
{
if( heurdata->maxdiveubquot > 0.0 )
searchubbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveubquot * (SCIPgetCutoffbound(scip) - SCIPgetLowerbound(scip));
else
searchubbound = SCIPinfinity(scip);
if( heurdata->maxdiveavgquot > 0.0 )
searchavgbound = SCIPgetLowerbound(scip)
+ heurdata->maxdiveavgquot * (SCIPgetAvgLowerbound(scip) - SCIPgetLowerbound(scip));
else
searchavgbound = SCIPinfinity(scip);
}
searchbound = MIN(searchubbound, searchavgbound);
if( SCIPisObjIntegral(scip) )
searchbound = SCIPceil(scip, searchbound);
/* calculate the maximal diving depth: 10 * min{number of integer variables, max depth} */
maxdivedepth = SCIPgetNBinVars(scip) + SCIPgetNIntVars(scip);
maxdivedepth = MIN(maxdivedepth, maxdepth);
maxdivedepth *= 10;
*result = SCIP_DIDNOTFIND;
/* start diving */
SCIP_CALL( SCIPstartProbing(scip) );
/* enables collection of variable statistics during probing */
SCIPenableVarHistory(scip);
SCIPdebugMessage("(node %" SCIP_LONGINT_FORMAT ") executing intdiving heuristic: depth=%d, %d non-fixed, dualbound=%g, searchbound=%g\n",
SCIPgetNNodes(scip), SCIPgetDepth(scip), nfixcands, SCIPgetDualbound(scip), SCIPretransformObj(scip, searchbound));
/* copy the pseudo candidates into own array, because we want to reorder them */
SCIP_CALL( SCIPduplicateBufferArray(scip, &fixcands, pseudocands, nfixcands) );
/* sort non-fixed variables by non-increasing inference score, but prefer binaries over integers in any case */
SCIP_CALL( SCIPallocBufferArray(scip, &fixcandscores, nfixcands) );
nbinfixcands = 0;
for( c = 0; c < nfixcands; ++c )
{
SCIP_VAR* var;
SCIP_Real score;
int colveclen;
int left;
int right;
int i;
assert(c >= nbinfixcands);
var = fixcands[c];
assert(SCIPvarIsIntegral(var));
colveclen = (SCIPvarGetStatus(var) == SCIP_VARSTATUS_COLUMN ? SCIPcolGetNNonz(SCIPvarGetCol(var)) : 0);
if( SCIPvarIsBinary(var) )
{
score = 500.0 * SCIPvarGetNCliques(var, TRUE) + 100.0 * SCIPvarGetNImpls(var, TRUE)
+ SCIPgetVarAvgInferenceScore(scip, var) + (SCIP_Real)colveclen/100.0;
/* shift the non-binary variables one slot to the right */
for( i = c; i > nbinfixcands; --i )
{
fixcands[i] = fixcands[i-1];
fixcandscores[i] = fixcandscores[i-1];
}
/* put the new candidate into the first nbinfixcands slot */
left = 0;
right = nbinfixcands;
nbinfixcands++;
}
else
{
score = 5.0 * (SCIPvarGetNCliques(var, FALSE) + SCIPvarGetNCliques(var, TRUE))
+ SCIPvarGetNImpls(var, FALSE) + SCIPvarGetNImpls(var, TRUE) + SCIPgetVarAvgInferenceScore(scip, var)
+ (SCIP_Real)colveclen/10000.0;
/* put the new candidate in the slots after the binary candidates */
left = nbinfixcands;
right = c;
}
for( i = right; i > left && score > fixcandscores[i-1]; --i )
{
fixcands[i] = fixcands[i-1];
fixcandscores[i] = fixcandscores[i-1];
}
fixcands[i] = var;
fixcandscores[i] = score;
SCIPdebugMessage(" <%s>: ncliques=%d/%d, nimpls=%d/%d, inferencescore=%g, colveclen=%d -> score=%g\n",
SCIPvarGetName(var), SCIPvarGetNCliques(var, FALSE), SCIPvarGetNCliques(var, TRUE),
SCIPvarGetNImpls(var, FALSE), SCIPvarGetNImpls(var, TRUE), SCIPgetVarAvgInferenceScore(scip, var),
colveclen, score);
}
SCIPfreeBufferArray(scip, &fixcandscores);
/* get LP objective value */
lpsolstat = SCIP_LPSOLSTAT_OPTIMAL;
objval = SCIPgetLPObjval(scip);
/* dive as long we are in the given objective, depth and iteration limits, but if possible, we dive at least with
* the depth 10
*/
lperror = FALSE;
cutoff = FALSE;
divedepth = 0;
nextcand = 0;
while( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL
&& (divedepth < 10
|| (divedepth < maxdivedepth && heurdata->nlpiterations < maxnlpiterations && objval < searchbound))
&& !SCIPisStopped(scip) )
{
SCIP_VAR* var;
SCIP_Real bestsolval;
SCIP_Real bestfixval;
int bestcand;
SCIP_Longint nnewlpiterations;
SCIP_Longint nnewdomreds;
/* open a new probing node if this will not exceed the maximal tree depth, otherwise stop here */
if( SCIPgetDepth(scip) < SCIPgetDepthLimit(scip) )
{
SCIP_CALL( SCIPnewProbingNode(scip) );
divedepth++;
}
else
break;
nnewlpiterations = 0;
nnewdomreds = 0;
/* fix binary variable that is closest to 1 in the LP solution to 1;
* if all binary variables are fixed, fix integer variable with least fractionality in LP solution
*/
bestcand = -1;
bestsolval = -1.0;
bestfixval = 1.0;
/* look in the binary variables for fixing candidates */
for( c = nextcand; c < nbinfixcands; ++c )
{
SCIP_Real solval;
var = fixcands[c];
/* ignore already fixed variables */
if( var == NULL )
continue;
if( SCIPvarGetLbLocal(var) > 0.5 || SCIPvarGetUbLocal(var) < 0.5 )
{
fixcands[c] = NULL;
continue;
}
/* get the LP solution value */
solval = SCIPvarGetLPSol(var);
if( solval > bestsolval )
{
bestcand = c;
bestfixval = 1.0;
bestsolval = solval;
if( SCIPisGE(scip, bestsolval, 1.0) )
{
/* we found an unfixed binary variable with LP solution value of 1.0 - there cannot be a better candidate */
break;
}
else if( SCIPisLE(scip, bestsolval, 0.0) )
{
/* the variable is currently at 0.0 - this is the only situation where we want to fix it to 0.0 */
bestfixval = 0.0;
}
}
}
/* if all binary variables are fixed, look in the integer variables for a fixing candidate */
if( bestcand == -1 )
{
SCIP_Real bestfrac;
bestfrac = SCIP_INVALID;
for( c = MAX(nextcand, nbinfixcands); c < nfixcands; ++c )
{
SCIP_Real solval;
SCIP_Real frac;
var = fixcands[c];
/* ignore already fixed variables */
if( var == NULL )
continue;
if( SCIPvarGetUbLocal(var) - SCIPvarGetLbLocal(var) < 0.5 )
{
fixcands[c] = NULL;
continue;
}
/* get the LP solution value */
solval = SCIPvarGetLPSol(var);
frac = SCIPfrac(scip, solval);
/* ignore integer variables that are currently integral */
if( SCIPisFeasFracIntegral(scip, frac) )
continue;
if( frac < bestfrac )
{
bestcand = c;
bestsolval = solval;
bestfrac = frac;
bestfixval = SCIPfloor(scip, bestsolval + 0.5);
if( SCIPisZero(scip, bestfrac) )
{
/* we found an unfixed integer variable with integral LP solution value */
break;
}
}
}
}
assert(-1 <= bestcand && bestcand < nfixcands);
/* if there is no unfixed candidate left, we are done */
if( bestcand == -1 )
break;
var = fixcands[bestcand];
assert(var != NULL);
assert(SCIPvarIsIntegral(var));
assert(SCIPvarGetUbLocal(var) - SCIPvarGetLbLocal(var) > 0.5);
assert(SCIPisGE(scip, bestfixval, SCIPvarGetLbLocal(var)));
assert(SCIPisLE(scip, bestfixval, SCIPvarGetUbLocal(var)));
backtracked = FALSE;
do
{
/* if the variable is already fixed or if the solution value is outside the domain, numerical troubles may have
* occured or variable was fixed by propagation while backtracking => Abort diving!
*/
if( SCIPvarGetLbLocal(var) >= SCIPvarGetUbLocal(var) - 0.5 )
{
SCIPdebugMessage("Selected variable <%s> already fixed to [%g,%g], diving aborted \n",
SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var));
cutoff = TRUE;
break;
}
if( SCIPisFeasLT(scip, bestfixval, SCIPvarGetLbLocal(var)) || SCIPisFeasGT(scip, bestfixval, SCIPvarGetUbLocal(var)) )
{
SCIPdebugMessage("selected variable's <%s> solution value is outside the domain [%g,%g] (solval: %.9f), diving aborted\n",
SCIPvarGetName(var), SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), bestfixval);
assert(backtracked);
break;
}
/* apply fixing of best candidate */
SCIPdebugMessage(" dive %d/%d, LP iter %" SCIP_LONGINT_FORMAT "/%" SCIP_LONGINT_FORMAT ", %d unfixed: var <%s>, sol=%g, oldbounds=[%g,%g], fixed to %g\n",
divedepth, maxdivedepth, heurdata->nlpiterations, maxnlpiterations, SCIPgetNPseudoBranchCands(scip),
SCIPvarGetName(var), bestsolval, SCIPvarGetLbLocal(var), SCIPvarGetUbLocal(var), bestfixval);
SCIP_CALL( SCIPfixVarProbing(scip, var, bestfixval) );
/* apply domain propagation */
SCIP_CALL( SCIPpropagateProbing(scip, 0, &cutoff, &nnewdomreds) );
if( !cutoff )
{
/* if the best candidate was just fixed to its LP value and no domain reduction was found, the LP solution
* stays valid, and the LP does not need to be resolved
*/
if( nnewdomreds > 0 || !SCIPisEQ(scip, bestsolval, bestfixval) )
{
/* resolve the diving LP */
/* Errors in the LP solver should not kill the overall solving process, if the LP is just needed for a heuristic.
* Hence in optimized mode, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
#ifdef NDEBUG
SCIP_RETCODE retstat;
nlpiterations = SCIPgetNLPIterations(scip);
retstat = SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff);
if( retstat != SCIP_OKAY )
{
SCIPwarningMessage(scip, "Error while solving LP in Intdiving heuristic; LP solve terminated with code <%d>\n",retstat);
}
#else
nlpiterations = SCIPgetNLPIterations(scip);
SCIP_CALL( SCIPsolveProbingLP(scip, MAX((int)(maxnlpiterations - heurdata->nlpiterations), MINLPITER), &lperror, &cutoff) );
#endif
if( lperror )
break;
/* update iteration count */
nnewlpiterations = SCIPgetNLPIterations(scip) - nlpiterations;
heurdata->nlpiterations += nnewlpiterations;
/* get LP solution status */
lpsolstat = SCIPgetLPSolstat(scip);
assert(cutoff || (lpsolstat != SCIP_LPSOLSTAT_OBJLIMIT && lpsolstat != SCIP_LPSOLSTAT_INFEASIBLE &&
(lpsolstat != SCIP_LPSOLSTAT_OPTIMAL || SCIPisLT(scip, SCIPgetLPObjval(scip), SCIPgetCutoffbound(scip)))));
}
}
/* perform backtracking if a cutoff was detected */
if( cutoff && !backtracked && heurdata->backtrack )
{
SCIPdebugMessage(" *** cutoff detected at level %d - backtracking\n", SCIPgetProbingDepth(scip));
SCIP_CALL( SCIPbacktrackProbing(scip, SCIPgetProbingDepth(scip)-1) );
/* after backtracking there has to be at least one open node without exceeding the maximal tree depth */
assert(SCIPgetDepthLimit(scip) > SCIPgetDepth(scip));
SCIP_CALL( SCIPnewProbingNode(scip) );
bestfixval = SCIPvarIsBinary(var)
? 1.0 - bestfixval
: (SCIPisGT(scip, bestsolval, bestfixval) && SCIPisFeasLE(scip, bestfixval + 1, SCIPvarGetUbLocal(var)) ? bestfixval + 1 : bestfixval - 1);
backtracked = TRUE;
}
else
backtracked = FALSE;
}
while( backtracked );
if( !lperror && !cutoff && lpsolstat == SCIP_LPSOLSTAT_OPTIMAL )
{
SCIP_Bool success;
/* get new objective value */
objval = SCIPgetLPObjval(scip);
if( nnewlpiterations > 0 || !SCIPisEQ(scip, bestsolval, bestfixval) )
{
/* we must start again with the first candidate, since the LP solution changed */
nextcand = 0;
/* create solution from diving LP and try to round it */
SCIP_CALL( SCIPlinkLPSol(scip, heurdata->sol) );
SCIP_CALL( SCIProundSol(scip, heurdata->sol, &success) );
if( success )
{
SCIPdebugMessage("intdiving found roundable primal solution: obj=%g\n",
SCIPgetSolOrigObj(scip, heurdata->sol));
/* try to add solution to SCIP */
SCIP_CALL( SCIPtrySol(scip, heurdata->sol, FALSE, FALSE, FALSE, FALSE, &success) );
/* check, if solution was feasible and good enough */
if( success )
{
SCIPdebugMessage(" -> solution was feasible and good enough\n");
*result = SCIP_FOUNDSOL;
}
}
}
else
nextcand = bestcand+1; /* continue with the next candidate in the following loop */
}
SCIPdebugMessage(" -> lpsolstat=%d, objval=%g/%g\n", lpsolstat, objval, searchbound);
}
/* free temporary memory */
SCIPfreeBufferArray(scip, &fixcands);
/* end diving */
SCIP_CALL( SCIPendProbing(scip) );
if( *result == SCIP_FOUNDSOL )
heurdata->nsuccess++;
SCIPdebugMessage("intdiving heuristic finished\n");
return SCIP_OKAY;
}
/* 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;
}
/** reduced cost pricing method of variable pricer for feasible LPs */
static
SCIP_DECL_PRICERREDCOST(pricerRedcostBinpacking)
{ /*lint --e{715}*/
SCIP* subscip;
SCIP_PRICERDATA* pricerdata;
SCIP_CONS** conss;
SCIP_VAR** vars;
int* ids;
SCIP_Bool addvar;
SCIP_SOL** sols;
int nsols;
int s;
int nitems;
SCIP_Longint capacity;
SCIP_Real timelimit;
SCIP_Real memorylimit;
assert(scip != NULL);
assert(pricer != NULL);
(*result) = SCIP_DIDNOTRUN;
/* get the pricer data */
pricerdata = SCIPpricerGetData(pricer);
assert(pricerdata != NULL);
capacity = pricerdata->capacity;
conss = pricerdata->conss;
ids = pricerdata->ids;
nitems = pricerdata->nitems;
/* get the remaining time and memory limit */
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;
/* initialize SCIP */
SCIP_CALL( SCIPcreate(&subscip) );
SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );
/* create problem in sub SCIP */
SCIP_CALL( SCIPcreateProbBasic(subscip, "pricing") );
SCIP_CALL( SCIPsetObjsense(subscip, SCIP_OBJSENSE_MAXIMIZE) );
/* 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 time and memory limit */
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
SCIP_CALL( SCIPallocMemoryArray(subscip, &vars, nitems) );
/* initialization local pricing problem */
SCIP_CALL( initPricing(scip, pricerdata, subscip, vars) );
SCIPdebugMessage("solve pricer problem\n");
/* solve sub SCIP */
SCIP_CALL( SCIPsolve(subscip) );
sols = SCIPgetSols(subscip);
nsols = SCIPgetNSols(subscip);
addvar = FALSE;
/* loop over all solutions and create the corresponding column to master if the reduced cost are negative for master,
* that is the objective value i greater than 1.0
*/
for( s = 0; s < nsols; ++s )
{
SCIP_Bool feasible;
SCIP_SOL* sol;
/* the soultion should be sorted w.r.t. the objective function value */
assert(s == 0 || SCIPisFeasGE(subscip, SCIPgetSolOrigObj(subscip, sols[s-1]), SCIPgetSolOrigObj(subscip, sols[s])));
sol = sols[s];
assert(sol != NULL);
/* check if solution is feasible in original sub SCIP */
SCIP_CALL( SCIPcheckSolOrig(subscip, sol, &feasible, FALSE, FALSE ) );
if( !feasible )
{
SCIPwarningMessage(scip, "solution in pricing problem (capacity <%d>) is infeasible\n", capacity);
continue;
}
/* check if the solution has a value greater than 1.0 */
if( SCIPisFeasGT(subscip, SCIPgetSolOrigObj(subscip, sol), 1.0) )
{
SCIP_VAR* var;
SCIP_VARDATA* vardata;
int* consids;
char strtmp[SCIP_MAXSTRLEN];
char name[SCIP_MAXSTRLEN];
int nconss;
int o;
int v;
SCIPdebug( SCIP_CALL( SCIPprintSol(subscip, sol, NULL, FALSE) ) );
nconss = 0;
(void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "items");
SCIP_CALL( SCIPallocBufferArray(scip, &consids, nitems) );
/* check which variables are fixed -> which item belongs to this packing */
for( o = 0, v = 0; o < nitems; ++o )
{
if( !SCIPconsIsEnabled(conss[o]) )
continue;
assert(SCIPgetNFixedonesSetppc(scip, conss[o]) == 0);
if( SCIPgetSolVal(subscip, sol, vars[v]) > 0.5 )
{
(void) SCIPsnprintf(strtmp, SCIP_MAXSTRLEN, "_%d", ids[o]);
strcat(name, strtmp);
consids[nconss] = o;
nconss++;
}
else
assert( SCIPisFeasEQ(subscip, SCIPgetSolVal(subscip, sol, vars[v]), 0.0) );
v++;
}
SCIP_CALL( SCIPvardataCreateBinpacking(scip, &vardata, consids, nconss) );
/* create variable for a new column with objective function coefficient 0.0 */
SCIP_CALL( SCIPcreateVarBinpacking(scip, &var, name, 1.0, FALSE, TRUE, vardata) );
/* add the new variable to the pricer store */
SCIP_CALL( SCIPaddPricedVar(scip, var, 1.0) );
addvar = TRUE;
/* change the upper bound of the binary variable to lazy since the upper bound is already enforced due to
* the objective function the set covering constraint; The reason for doing is that, is to avoid the bound
* of x <= 1 in the LP relaxation since this bound constraint would produce a dual variable which might have
* a positive reduced cost
*/
SCIP_CALL( SCIPchgVarUbLazy(scip, var, 1.0) );
/* check which variable are fixed -> which orders belong to this packing */
for( v = 0; v < nconss; ++v )
{
assert(SCIPconsIsEnabled(conss[consids[v]]));
SCIP_CALL( SCIPaddCoefSetppc(scip, conss[consids[v]], var) );
}
SCIPdebug(SCIPprintVar(scip, var, NULL) );
SCIP_CALL( SCIPreleaseVar(scip, &var) );
SCIPfreeBufferArray(scip, &consids);
}
else
break;
}
/* free pricer MIP */
SCIPfreeMemoryArray(subscip, &vars);
if( addvar || SCIPgetStatus(subscip) == SCIP_STATUS_OPTIMAL )
(*result) = SCIP_SUCCESS;
/* free sub SCIP */
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecCrossover)
{ /*lint --e{715}*/
SCIP_HEURDATA* heurdata; /* primal heuristic data */
SCIP* subscip; /* the subproblem created by crossover */
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_SOL** sols;
SCIP_Real memorylimit; /* memory limit for the subproblem */
SCIP_Real timelimit; /* time limit for the subproblem */
SCIP_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real upperbound;
SCIP_Bool success;
SCIP_Longint nstallnodes; /* node limit for the subproblem */
int* selection; /* pool of solutions crossover uses */
int nvars; /* number of original problem's variables */
int nbinvars;
int nintvars;
int nusedsols;
int i;
SCIP_RETCODE retcode;
assert(heur != NULL);
assert(scip != NULL);
assert(result != NULL);
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert(heurdata != NULL);
nusedsols = heurdata->nusedsols;
*result = SCIP_DELAYED;
/* only call heuristic, if enough solutions are at hand */
if( SCIPgetNSols(scip) < nusedsols )
return SCIP_OKAY;
sols = SCIPgetSols(scip);
assert(sols != NULL);
/* if one good solution was found, heuristic should not be delayed any longer */
if( sols[nusedsols-1] != heurdata->prevlastsol )
{
heurdata->nextnodenumber = SCIPgetNNodes(scip);
if( sols[0] != heurdata->prevbestsol )
heurdata->nfailures = 0;
}
/* in nonrandomized mode: only recall heuristic, if at least one new good solution was found in the meantime */
else if( !heurdata->randomization )
return SCIP_OKAY;
/* if heuristic should be delayed, wait until certain number of nodes is reached */
if( SCIPgetNNodes(scip) < heurdata->nextnodenumber )
return SCIP_OKAY;
/* only call heuristic, if enough nodes were processed since last incumbent */
if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip,SCIPgetBestSol(scip)) < heurdata->nwaitingnodes
&& (SCIPgetDepth(scip) > 0 || !heurdata->dontwaitatroot) )
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* calculate the maximal number of branching nodes until heuristic is aborted */
nstallnodes = (SCIP_Longint)(heurdata->nodesquot * SCIPgetNNodes(scip));
/* reward Crossover if it succeeded often */
nstallnodes = (SCIP_Longint)
(nstallnodes * (1.0 + 2.0*(SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur)+1.0)));
/* count the setup costs for the sub-MIP as 100 nodes */
nstallnodes -= 100 * SCIPheurGetNCalls(heur);
nstallnodes += heurdata->nodesofs;
/* determine the node limit for the current process */
nstallnodes -= heurdata->usednodes;
nstallnodes = MIN(nstallnodes, heurdata->maxnodes);
/* check whether we have enough nodes left to call subproblem solving */
if( nstallnodes < heurdata->minnodes )
return SCIP_OKAY;
if( SCIPisStopped(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
assert(nvars > 0);
/* check whether discrete variables are available */
if( nbinvars == 0 && nintvars == 0 )
return SCIP_OKAY;
/* initializing the subproblem */
SCIP_CALL( SCIPcreate(&subscip) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
success = FALSE;
if( heurdata->uselprows )
{
char probname[SCIP_MAXSTRLEN];
/* copy all plugins */
SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );
/* get name of the original problem and add the string "_crossoversub" */
(void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_crossoversub", SCIPgetProbName(scip));
/* create the subproblem */
SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );
/* copy all variables */
SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
}
else
{
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "crossover", TRUE, FALSE, TRUE, &success) );
if( heurdata->copycuts )
{
/** copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
}
}
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
SCIP_CALL( SCIPallocBufferArray(scip, &selection, nusedsols) );
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) (size_t) SCIPhashmapGetImage(varmapfw, vars[i]);
/* free hash map */
SCIPhashmapFree(&varmapfw);
success = FALSE;
/* create a new problem, which fixes variables with same value in a certain set of solutions */
SCIP_CALL( setupSubproblem(scip, subscip, subvars, selection, heurdata, &success) );
heurdata->prevbestsol = SCIPgetBestSol(scip);
heurdata->prevlastsol = sols[heurdata->nusedsols-1];
/* if creation of sub-SCIP was aborted (e.g. due to number of fixings), free sub-SCIP and abort */
if( !success )
{
*result = SCIP_DIDNOTRUN;
/* this run will be counted as a failure since no new solution tuple could be generated or the neighborhood of the
* solution was not fruitful in the sense that it was too big
*/
updateFailureStatistic(scip, heurdata);
goto TERMINATE;
}
/* do not abort subproblem on CTRL-C */
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
/* disable output to console */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
/* check whether there is enough time and memory left */
SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
if( !SCIPisInfinity(scip, timelimit) )
timelimit -= SCIPgetSolvingTime(scip);
SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
/* substract the memory already used by the main SCIP and the estimated memory usage of external software */
if( !SCIPisInfinity(scip, memorylimit) )
{
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
}
/* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
goto TERMINATE;
/* set limits for the subproblem */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nstallnodes) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
/* forbid recursive call of heuristics and separators solving subMIPs */
SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
/* disable cutting plane separation */
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
/* disable expensive presolving */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );
/* use best estimate node selection */
if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
}
/* use inference branching */
if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
}
/* disable conflict analysis */
if( !SCIPisParamFixed(subscip, "conflict/useprop") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/useinflp") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/usesb") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/usepseudo") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
}
/* add an objective cutoff */
cutoff = SCIPinfinity(scip);
assert(!SCIPisInfinity(scip, SCIPgetUpperbound(scip)));
upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
{
cutoff = (1-heurdata->minimprove)*SCIPgetUpperbound(scip) + heurdata->minimprove*SCIPgetLowerbound(scip);
}
else
{
if( SCIPgetUpperbound ( scip ) >= 0 )
cutoff = ( 1 - heurdata->minimprove ) * SCIPgetUpperbound ( scip );
else
cutoff = ( 1 + heurdata->minimprove ) * SCIPgetUpperbound ( scip );
}
cutoff = MIN(upperbound, cutoff );
SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );
/* permute the subproblem to increase diversification */
if( heurdata->permute )
{
SCIP_CALL( SCIPpermuteProb(subscip, (unsigned int) SCIPheurGetNCalls(heur), TRUE, TRUE, TRUE, TRUE, TRUE) );
}
/* solve the subproblem */
SCIPdebugMessage("Solve Crossover subMIP\n");
retcode = SCIPsolve(subscip);
/* Errors in solving the subproblem should not kill the overall solving process.
* Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop. */
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage(scip, "Error while solving subproblem in Crossover heuristic; sub-SCIP terminated with code <%d>\n", retcode);
}
heurdata->usednodes += SCIPgetNNodes(subscip);
/* check, whether a solution was found */
if( SCIPgetNSols(subscip) > 0 )
{
SCIP_SOL** subsols;
int nsubsols;
int solindex; /* index of the solution created by crossover */
/* 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;
solindex = -1;
for( i = 0; i < nsubsols && !success; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &solindex, &success) );
}
if( success )
{
int tmp;
assert(solindex != -1);
*result = SCIP_FOUNDSOL;
/* insert all crossings of the new solution and (nusedsols-1) of its parents into the hashtable
* in order to avoid incest ;)
*/
for( i = 0; i < nusedsols; i++ )
{
SOLTUPLE* elem;
tmp = selection[i];
selection[i] = solindex;
SCIP_CALL( createSolTuple(scip, &elem, selection, nusedsols, heurdata) );
SCIP_CALL( SCIPhashtableInsert(heurdata->hashtable, elem) );
selection[i] = tmp;
}
/* if solution was among the best ones, crossover should not be called until another good solution was found */
if( !heurdata->randomization )
{
heurdata->prevbestsol = SCIPgetBestSol(scip);
heurdata->prevlastsol = SCIPgetSols(scip)[heurdata->nusedsols-1];
}
}
/* if solution is not better then incumbent or could not be added to problem => run is counted as a failure */
if( !success || solindex != SCIPsolGetIndex(SCIPgetBestSol(scip)) )
updateFailureStatistic(scip, heurdata);
}
else
{
/* if no new solution was found, run was a failure */
updateFailureStatistic(scip, heurdata);
}
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &selection);
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/** main procedure of the RENS heuristic, creates and solves a subMIP */
SCIP_RETCODE SCIPapplyGcgrens(
SCIP* scip, /**< original SCIP data structure */
SCIP_HEUR* heur, /**< heuristic data structure */
SCIP_RESULT* result, /**< result data structure */
SCIP_Real minfixingrate, /**< minimum percentage of integer variables that have to be fixed */
SCIP_Real minimprove, /**< factor by which RENS should at least improve the incumbent */
SCIP_Longint maxnodes, /**< maximum number of nodes for the subproblem */
SCIP_Longint nstallnodes, /**< number of stalling nodes for the subproblem */
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* subscip; /* the subproblem created by RENS */
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_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real timelimit;
SCIP_Real memorylimit;
int nvars;
int i;
SCIP_Bool success;
SCIP_RETCODE retcode;
assert(scip != NULL);
assert(heur != NULL);
assert(result != NULL);
assert(maxnodes >= 0);
assert(nstallnodes >= 0);
assert(0.0 <= minfixingrate && minfixingrate <= 1.0);
assert(0.0 <= minimprove && minimprove <= 1.0);
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) );
if( uselprows )
{
char probname[SCIP_MAXSTRLEN];
/* copy all plugins */
SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );
/* get name of the original problem and add the string "_gcgrenssub" */
(void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_gcgrenssub", SCIPgetProbName(scip));
/* create the subproblem */
SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );
/* copy all variables */
SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
}
else
{
SCIP_Bool valid;
SCIP_HEURDATA* heurdata;
valid = FALSE;
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "gcgrens", TRUE, FALSE, TRUE, &valid) ); /** @todo check for thread safeness */
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert( heurdata != NULL );
if( heurdata->copycuts )
{
/** copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
}
SCIPdebugMessage("Copying the SCIP instance was %s complete.\n", valid ? "" : "not ");
}
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
/* free hash map */
SCIPhashmapFree(&varmapfw);
/* create a new problem, which fixes variables with same value in bestsol and LP relaxation */
SCIP_CALL( createSubproblem(scip, subscip, subvars, minfixingrate, binarybounds, uselprows, &success) );
SCIPdebugMessage("RENS subproblem: %d vars, %d cons, success=%u\n", SCIPgetNVars(subscip), SCIPgetNConss(subscip), success);
/* do not abort subproblem on CTRL-C */
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
/* disable output to console */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
/* check whether there is enough time and memory left */
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) );
if( !SCIPisInfinity(scip, memorylimit) )
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
if( timelimit <= 0.0 || memorylimit <= 0.0 )
goto TERMINATE;
/* set limits for the subproblem */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/stallnodes", nstallnodes) );
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", maxnodes) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
/* forbid recursive call of heuristics and separators solving sub-SCIPs */
SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
/* disable cutting plane separation */
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
/* disable expensive presolving */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );
/* use best estimate node selection */
if( SCIPfindNodesel(scip, "estimate") != NULL )
{
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
}
/* use inference branching */
if( SCIPfindBranchrule(scip, "inference") != NULL )
{
SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
}
/* disable conflict analysis */
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
#ifdef SCIP_DEBUG
/* for debugging RENS, enable MIP output */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 5) );
SCIP_CALL( SCIPsetIntParam(subscip, "display/freq", 100000000) );
#endif
/* if the subproblem could not be created, free memory and return */
if( !success )
{
*result = SCIP_DIDNOTRUN;
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/* if there is already a solution, add an objective cutoff */
if( SCIPgetNSols(scip) > 0 )
{
SCIP_Real upperbound;
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( SCIPsetObjlimit(subscip, cutoff) );
}
/* presolve the subproblem */
retcode = SCIPpresolve(subscip);
/* Errors in solving the subproblem should not kill the overall solving process
* Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage(scip, "Error while presolving subproblem in GCG RENS heuristic; sub-SCIP terminated with code <%d>\n",retcode);
}
SCIPdebugMessage("GCG RENS presolved subproblem: %d vars, %d cons, success=%u\n", SCIPgetNVars(subscip), SCIPgetNConss(subscip), success);
/* after presolving, we should have at least reached a certain fixing rate over ALL variables (including continuous)
* to ensure that not only the MIP but also the LP relaxation is easy enough
*/
if( ( nvars - SCIPgetNVars(subscip) ) / (SCIP_Real)nvars >= minfixingrate / 2.0 )
{
SCIP_SOL** subsols;
int nsubsols;
/* solve the subproblem */
SCIPdebugMessage("solving subproblem: nstallnodes=%"SCIP_LONGINT_FORMAT", maxnodes=%"SCIP_LONGINT_FORMAT"\n", nstallnodes, maxnodes);
retcode = SCIPsolve(subscip);
/* Errors in solving the subproblem should not kill the overall solving process
* Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage(scip, "Error while solving subproblem in GCG RENS 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; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
}
if( success )
*result = SCIP_FOUNDSOL;
}
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/** writes problem to file */
SCIP_RETCODE SCIPwriteCcg(
SCIP* scip, /**< SCIP data structure */
FILE* file, /**< output file, or NULL if standard output should be used */
const char* name, /**< problem name */
SCIP_Bool transformed, /**< TRUE iff problem is the transformed problem */
SCIP_VAR** vars, /**< array with active variables ordered binary, integer, implicit, continuous */
int nvars, /**< number of active variables in the problem */
SCIP_CONS** conss, /**< array with constraints of the problem */
int nconss, /**< number of constraints in the problem */
SCIP_RESULT* result /**< pointer to store the result of the file writing call */
)
{ /*lint --e{715}*/
int c;
int v;
int i;
SCIP_CONSHDLR* conshdlr;
const char* conshdlrname;
SCIP_CONS* cons;
SCIP_VAR** consvars;
SCIP_Real* consvals;
int nconsvars;
SparseGraph G;
assert( scip != NULL );
assert( nvars >= 0 );
/* initialize graph */
SCIP_CALL( initGraph(scip, &G, (unsigned int) nvars, 10) );
/* check all constraints */
for( c = 0; c < nconss; ++c)
{
cons = conss[c];
assert( cons != NULL);
/* in case the transformed is written only constraint are posted which are enabled in the current node */
assert(!transformed || SCIPconsIsEnabled(cons));
conshdlr = SCIPconsGetHdlr(cons);
assert( conshdlr != NULL );
conshdlrname = SCIPconshdlrGetName(conshdlr);
assert( transformed == SCIPconsIsTransformed(cons) );
if( strcmp(conshdlrname, "linear") == 0 )
{
consvars = SCIPgetVarsLinear(scip, cons);
nconsvars = SCIPgetNVarsLinear(scip, cons);
assert( consvars != NULL || nconsvars == 0 );
if( nconsvars > 0 )
{
SCIP_CALL( handleLinearCons(scip, SCIPgetVarsLinear(scip, cons), SCIPgetValsLinear(scip, cons),
SCIPgetNVarsLinear(scip, cons), transformed, &G) );
}
}
else if( strcmp(conshdlrname, "setppc") == 0 )
{
consvars = SCIPgetVarsSetppc(scip, cons);
nconsvars = SCIPgetNVarsSetppc(scip, cons);
assert( consvars != NULL || nconsvars == 0 );
if( nconsvars > 0 )
{
SCIP_CALL( handleLinearCons(scip, consvars, NULL, nconsvars, transformed, &G) );
}
}
else if( strcmp(conshdlrname, "logicor") == 0 )
{
consvars = SCIPgetVarsLogicor(scip, cons);
nconsvars = SCIPgetNVarsLogicor(scip, cons);
assert( consvars != NULL || nconsvars == 0 );
if( nconsvars > 0 )
{
SCIP_CALL( handleLinearCons(scip, SCIPgetVarsLogicor(scip, cons), NULL, SCIPgetNVarsLogicor(scip, cons), transformed, &G) );
}
}
else if( strcmp(conshdlrname, "knapsack") == 0 )
{
SCIP_Longint* w;
consvars = SCIPgetVarsKnapsack(scip, cons);
nconsvars = SCIPgetNVarsKnapsack(scip, cons);
assert( consvars != NULL || nconsvars == 0 );
/* copy Longint array to SCIP_Real array */
w = SCIPgetWeightsKnapsack(scip, cons);
SCIP_CALL( SCIPallocBufferArray(scip, &consvals, nconsvars) );
for( v = 0; v < nconsvars; ++v )
consvals[v] = (SCIP_Real)w[v];
if( nconsvars > 0 )
{
SCIP_CALL( handleLinearCons(scip, consvars, consvals, nconsvars, transformed, &G) );
}
SCIPfreeBufferArray(scip, &consvals);
}
else if( strcmp(conshdlrname, "varbound") == 0 )
{
SCIP_CALL( SCIPallocBufferArray(scip, &consvars, 2) );
SCIP_CALL( SCIPallocBufferArray(scip, &consvals, 2) );
consvars[0] = SCIPgetVarVarbound(scip, cons);
consvars[1] = SCIPgetVbdvarVarbound(scip, cons);
consvals[0] = 1.0;
consvals[1] = SCIPgetVbdcoefVarbound(scip, cons);
SCIP_CALL( handleLinearCons(scip, consvars, consvals, 2, transformed, &G) );
SCIPfreeBufferArray(scip, &consvars);
SCIPfreeBufferArray(scip, &consvals);
}
else
{
SCIPwarningMessage(scip, "constraint handler <%s> cannot print requested format\n", conshdlrname );
SCIPinfoMessage(scip, file, "\\ ");
SCIP_CALL( SCIPprintCons(scip, cons, file) );
SCIPinfoMessage(scip, file, ";\n");
}
}
/* output graph */
SCIPinfoMessage(scip, file, "c graph generated from %s\n", name);
SCIPinfoMessage(scip, file, "p edge %d %d\n", nvars, G.m);
for( i = 0; i < nvars; ++i )
{
unsigned int k;
int a;
k = 0;
a = G.A[i][k];
while( a >= 0 )
{
/* only output edges from lower to higher number */
if( i < a )
{
/* note: node numbers start with 1 in the DIMACS format */
SCIPinfoMessage(scip, file, "e %d %d %f\n", i+1, a+1, G.W[i][k]);
}
a = G.A[i][++k];
assert( k <= G.size[i] );
}
assert( k == G.deg[i] );
}
freeGraph(scip, &G);
*result = SCIP_SUCCESS;
return SCIP_OKAY;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecLocalbranching)
{ /*lint --e{715}*/
SCIP_Longint maxnnodes; /* maximum number of subnodes */
SCIP_Longint nsubnodes; /* nodelimit for subscip */
SCIP_HEURDATA* heurdata;
SCIP* subscip; /* the subproblem created by localbranching */
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_SOL* bestsol; /* best solution so far */
SCIP_EVENTHDLR* eventhdlr; /* event handler for LP events */
SCIP_Real timelimit; /* timelimit for subscip (equals remaining time of scip) */
SCIP_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real upperbound;
SCIP_Real memorylimit;
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_VAR** vars;
int nvars;
int i;
SCIP_Bool success;
SCIP_RETCODE retcode;
assert(heur != NULL);
assert(scip != NULL);
assert(result != NULL);
*result = SCIP_DIDNOTRUN;
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert( heurdata != NULL );
/* there should be enough binary variables that a local branching constraint makes sense */
if( SCIPgetNBinVars(scip) < 2*heurdata->neighborhoodsize )
return SCIP_OKAY;
*result = SCIP_DELAYED;
/* only call heuristic, if an IP solution is at hand */
if( SCIPgetNSols(scip) <= 0 )
return SCIP_OKAY;
bestsol = SCIPgetBestSol(scip);
assert(bestsol != NULL);
/* only call heuristic, if the best solution comes from transformed problem */
if( SCIPsolIsOriginal(bestsol) )
return SCIP_OKAY;
/* only call heuristic, if enough nodes were processed since last incumbent */
if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip, bestsol) < heurdata->nwaitingnodes)
return SCIP_OKAY;
/* only call heuristic, if the best solution does not come from trivial heuristic */
if( SCIPsolGetHeur(bestsol) != NULL && strcmp(SCIPheurGetName(SCIPsolGetHeur(bestsol)), "trivial") == 0 )
return SCIP_OKAY;
/* reset neighborhood and minnodes, if new solution was found */
if( heurdata->lastsol != bestsol )
{
heurdata->curneighborhoodsize = heurdata->neighborhoodsize;
heurdata->curminnodes = heurdata->minnodes;
heurdata->emptyneighborhoodsize = 0;
heurdata->callstatus = EXECUTE;
heurdata->lastsol = bestsol;
}
/* if no new solution was found and local branching also seems to fail, just keep on waiting */
if( heurdata->callstatus == WAITFORNEWSOL )
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* calculate the maximal number of branching nodes until heuristic is aborted */
maxnnodes = (SCIP_Longint)(heurdata->nodesquot * SCIPgetNNodes(scip));
/* reward local branching if it succeeded often */
maxnnodes = (SCIP_Longint)(maxnnodes * (1.0 + 2.0*(SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur)+1.0)));
maxnnodes -= 100 * SCIPheurGetNCalls(heur); /* count the setup costs for the sub-MIP as 100 nodes */
maxnnodes += heurdata->nodesofs;
/* determine the node limit for the current process */
nsubnodes = maxnnodes - heurdata->usednodes;
nsubnodes = MIN(nsubnodes, heurdata->maxnodes);
/* check whether we have enough nodes left to call sub problem solving */
if( nsubnodes < heurdata->curminnodes )
return SCIP_OKAY;
if( SCIPisStopped(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
SCIPdebugMessage("running localbranching heuristic ...\n");
/* get the data of the variables and the best solution */
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* initializing the subproblem */
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
SCIP_CALL( SCIPcreate(&subscip) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
success = FALSE;
eventhdlr = NULL;
if( heurdata->uselprows )
{
char probname[SCIP_MAXSTRLEN];
/* copy all plugins */
SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );
/* get name of the original problem and add the string "_localbranchsub" */
(void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_localbranchsub", SCIPgetProbName(scip));
/* create the subproblem */
SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );
/* copy all variables */
SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
}
else
{
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "localbranchsub", TRUE, FALSE, TRUE, &success) );
if( heurdata->copycuts )
{
/* copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
}
/* create event handler for LP events */
SCIP_CALL( SCIPincludeEventhdlrBasic(subscip, &eventhdlr, EVENTHDLR_NAME, EVENTHDLR_DESC, eventExecLocalbranching, NULL) );
if( eventhdlr == NULL )
{
SCIPerrorMessage("event handler for "HEUR_NAME" heuristic not found.\n");
return SCIP_PLUGINNOTFOUND;
}
}
SCIPdebugMessage("Copying the plugins was %ssuccessful.\n", success ? "" : "not ");
for (i = 0; i < nvars; ++i)
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
/* free hash map */
SCIPhashmapFree(&varmapfw);
/* if the subproblem could not be created, free memory and return */
if( !success )
{
*result = SCIP_DIDNOTRUN;
goto TERMINATE;
}
/* 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
/* check whether there is enough time and memory left */
SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
if( !SCIPisInfinity(scip, timelimit) )
timelimit -= SCIPgetSolvingTime(scip);
SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
/* substract the memory already used by the main SCIP and the estimated memory usage of external software */
if( !SCIPisInfinity(scip, memorylimit) )
{
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
}
/* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
goto TERMINATE;
/* set limits for the subproblem */
heurdata->nodelimit = nsubnodes;
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nsubnodes) );
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/stallnodes", MAX(10, nsubnodes/10)) );
SCIP_CALL( SCIPsetIntParam(subscip, "limits/bestsol", 3) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
/* forbid recursive call of heuristics and separators solving subMIPs */
SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
/* disable cutting plane separation */
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
/* disable expensive presolving */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );
/* use best estimate node selection */
if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
}
/* use inference branching */
if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
}
/* disable conflict analysis */
if( !SCIPisParamFixed(subscip, "conflict/useprop") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/useinflp") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/usesb") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/usepseudo") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
}
/* employ a limit on the number of enforcement rounds in the quadratic constraint 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", 500) );
}
/* copy the original problem and add the local branching constraint */
if( heurdata->uselprows )
{
SCIP_CALL( createSubproblem(scip, subscip, subvars) );
}
SCIP_CALL( addLocalBranchingConstraint(scip, subscip, subvars, heurdata) );
/* add an objective cutoff */
cutoff = SCIPinfinity(scip);
assert( !SCIPisInfinity(scip,SCIPgetUpperbound(scip)) );
upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
if( !SCIPisInfinity(scip,-1.0*SCIPgetLowerbound(scip)) )
{
cutoff = (1-heurdata->minimprove)*SCIPgetUpperbound(scip) + heurdata->minimprove*SCIPgetLowerbound(scip);
}
else
{
if( SCIPgetUpperbound ( scip ) >= 0 )
cutoff = ( 1 - heurdata->minimprove ) * SCIPgetUpperbound ( scip );
else
cutoff = ( 1 + heurdata->minimprove ) * SCIPgetUpperbound ( scip );
}
cutoff = MIN(upperbound, cutoff );
SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );
/* catch LP events of sub-SCIP */
if( !heurdata->uselprows )
{
assert(eventhdlr != NULL);
SCIP_CALL( SCIPtransformProb(subscip) );
SCIP_CALL( SCIPcatchEvent(subscip, SCIP_EVENTTYPE_LPSOLVED, eventhdlr, (SCIP_EVENTDATA*) heurdata, NULL) );
}
/* solve the subproblem */
SCIPdebugMessage("solving local branching subproblem with neighborhoodsize %d and maxnodes %"SCIP_LONGINT_FORMAT"\n",
heurdata->curneighborhoodsize, nsubnodes);
retcode = SCIPsolve(subscip);
/* drop LP events of sub-SCIP */
if( !heurdata->uselprows )
{
assert(eventhdlr != NULL);
SCIP_CALL( SCIPdropEvent(subscip, SCIP_EVENTTYPE_LPSOLVED, 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 local branching heuristic; sub-SCIP terminated with code <%d>\n",retcode);
}
/* print solving statistics of subproblem if we are in SCIP's debug mode */
SCIPdebug( SCIP_CALL( SCIPprintStatistics(subscip, NULL) ) );
heurdata->usednodes += SCIPgetNNodes(subscip);
SCIPdebugMessage("local branching used %"SCIP_LONGINT_FORMAT"/%"SCIP_LONGINT_FORMAT" nodes\n",
SCIPgetNNodes(subscip), nsubnodes);
/* check, whether a solution was found */
if( SCIPgetNSols(subscip) > 0 )
{
SCIP_SOL** subsols;
int nsubsols;
/* check, whether a solution was found;
* due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
*/
nsubsols = SCIPgetNSols(subscip);
subsols = SCIPgetSols(subscip);
success = FALSE;
for( i = 0; i < nsubsols && !success; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
}
if( success )
{
SCIPdebugMessage("-> accepted solution of value %g\n", SCIPgetSolOrigObj(subscip, subsols[i]));
*result = SCIP_FOUNDSOL;
}
}
/* check the status of the sub-MIP */
switch( SCIPgetStatus(subscip) )
{
case SCIP_STATUS_OPTIMAL:
case SCIP_STATUS_BESTSOLLIMIT:
heurdata->callstatus = WAITFORNEWSOL; /* new solution will immediately be installed at next call */
SCIPdebugMessage(" -> found new solution\n");
break;
case SCIP_STATUS_NODELIMIT:
case SCIP_STATUS_STALLNODELIMIT:
case SCIP_STATUS_TOTALNODELIMIT:
heurdata->callstatus = EXECUTE;
heurdata->curneighborhoodsize = (heurdata->emptyneighborhoodsize + heurdata->curneighborhoodsize)/2;
heurdata->curminnodes *= 2;
SCIPdebugMessage(" -> node limit reached: reduced neighborhood to %d, increased minnodes to %d\n",
heurdata->curneighborhoodsize, heurdata->curminnodes);
if( heurdata->curneighborhoodsize <= heurdata->emptyneighborhoodsize )
{
heurdata->callstatus = WAITFORNEWSOL;
SCIPdebugMessage(" -> new neighborhood was already proven to be empty: wait for new solution\n");
}
break;
case SCIP_STATUS_INFEASIBLE:
case SCIP_STATUS_INFORUNBD:
heurdata->emptyneighborhoodsize = heurdata->curneighborhoodsize;
heurdata->curneighborhoodsize += heurdata->curneighborhoodsize/2;
heurdata->curneighborhoodsize = MAX(heurdata->curneighborhoodsize, heurdata->emptyneighborhoodsize + 2);
heurdata->callstatus = EXECUTE;
SCIPdebugMessage(" -> neighborhood is empty: increased neighborhood to %d\n", heurdata->curneighborhoodsize);
break;
case SCIP_STATUS_UNKNOWN:
case SCIP_STATUS_USERINTERRUPT:
case SCIP_STATUS_TIMELIMIT:
case SCIP_STATUS_MEMLIMIT:
case SCIP_STATUS_GAPLIMIT:
case SCIP_STATUS_SOLLIMIT:
case SCIP_STATUS_UNBOUNDED:
default:
heurdata->callstatus = WAITFORNEWSOL;
SCIPdebugMessage(" -> unexpected sub-MIP status <%d>: waiting for new solution\n", SCIPgetStatus(subscip));
break;
}
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
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;
}
/** reads the given solution file */
static
SCIP_RETCODE readSol(
SCIP* scip, /**< SCIP data structure */
const char* filename /**< name of the input file */
)
{
SCIP_FILE* file;
SCIP_Bool error;
SCIP_Bool unknownvariablemessage;
int lineno;
int nfixed;
assert(scip != NULL);
assert(filename != NULL);
/* open input file */
file = SCIPfopen(filename, "r");
if( file == NULL )
{
SCIPerrorMessage("cannot open file <%s> for reading\n", filename);
SCIPprintSysError(filename);
return SCIP_NOFILE;
}
/* read the file */
error = FALSE;
unknownvariablemessage = FALSE;
lineno = 0;
nfixed = 0;
while( !SCIPfeof(file) && !error )
{
char buffer[SCIP_MAXSTRLEN];
char varname[SCIP_MAXSTRLEN];
char valuestring[SCIP_MAXSTRLEN];
char objstring[SCIP_MAXSTRLEN];
SCIP_VAR* var;
SCIP_Real value;
SCIP_Bool infeasible;
SCIP_Bool fixed;
int nread;
/* get next line */
if( SCIPfgets(buffer, (int) sizeof(buffer), file) == NULL )
break;
lineno++;
/* the lines "solution status: ..." and "objective value: ..." may preceed the solution information */
if( strncasecmp(buffer, "solution status:", 16) == 0 || strncasecmp(buffer, "objective value:", 16) == 0 )
continue;
/* parse the line */
nread = sscanf(buffer, "%s %s %s\n", varname, valuestring, objstring);
if( nread < 2 )
{
SCIPerrorMessage("invalid input line %d in solution file <%s>: <%s>\n", lineno, filename, buffer);
error = TRUE;
break;
}
/* find the variable */
var = SCIPfindVar(scip, varname);
if( var == NULL )
{
if( !unknownvariablemessage )
{
SCIPwarningMessage(scip, "unknown variable <%s> in line %d of solution file <%s>\n", varname, lineno, filename);
SCIPwarningMessage(scip, " (further unknown variables are ignored)\n");
unknownvariablemessage = TRUE;
}
continue;
}
/* cast the value */
if( strncasecmp(valuestring, "inv", 3) == 0 )
continue;
else if( strncasecmp(valuestring, "+inf", 4) == 0 || strncasecmp(valuestring, "inf", 3) == 0 )
value = SCIPinfinity(scip);
else if( strncasecmp(valuestring, "-inf", 4) == 0 )
value = -SCIPinfinity(scip);
else
{
nread = sscanf(valuestring, "%lf", &value);
if( nread != 1 )
{
SCIPerrorMessage("invalid solution value <%s> for variable <%s> in line %d of solution file <%s>\n",
valuestring, varname, lineno, filename);
error = TRUE;
break;
}
}
/* fix the variable */
SCIP_CALL( SCIPfixVar(scip, var, value, &infeasible, &fixed) );
if( infeasible )
{
SCIPerrorMessage("infeasible solution value of <%s>[%.15g,%.15g] to %.15g in line %d of solution file <%s>\n",
varname, SCIPvarGetLbGlobal(var), SCIPvarGetUbGlobal(var), value, lineno, filename);
error = TRUE;
break;
}
if( fixed )
nfixed++;
}
/* close input file */
SCIPfclose(file);
/* display result */
SCIPverbMessage(scip, SCIP_VERBLEVEL_NORMAL, NULL, "fixed %d variables from solution file <%s>\n", nfixed, filename);
if( error )
return SCIP_READERROR;
else
return SCIP_OKAY;
}
/** problem reading method of reader */
static
SCIP_DECL_READERREAD(readerReadBpa)
{ /*lint --e{715}*/
SCIP_FILE* file;
SCIP_Longint* weights;
int* ids;
SCIP_Bool error;
char name[SCIP_MAXSTRLEN];
char format[16];
char buffer[SCIP_MAXSTRLEN];
int capacity;
int nitems;
int bestsolvalue;
int nread;
int weight;
int nweights;
int lineno;
*result = SCIP_DIDNOTRUN;
/* open file */
file = SCIPfopen(filename, "r");
if( file == NULL )
{
SCIPerrorMessage("cannot open file <%s> for reading\n", filename);
SCIPprintSysError(filename);
return SCIP_NOFILE;
}
lineno = 0;
/* read problem name */
if( !SCIPfeof(file) )
{
/* get next line */
if( SCIPfgets(buffer, sizeof(buffer), file) == NULL )
return SCIP_READERROR;
lineno++;
/* parse dimension line */
sprintf(format, "%%%ds\n", SCIP_MAXSTRLEN);
nread = sscanf(buffer, format, name);
if( nread == 0 )
{
SCIPwarningMessage(scip, "invalid input line %d in file <%s>: <%s>\n", lineno, filename, buffer);
return SCIP_READERROR;
}
SCIPdebugMessage("problem name <%s>\n", name);
}
/* read problem dimension */
if( !SCIPfeof(file) )
{
/* get next line */
if( SCIPfgets(buffer, sizeof(buffer), file) == NULL )
return SCIP_READERROR;
lineno++;
/* parse dimension line */
nread = sscanf(buffer, "%d %d %d\n", &capacity, &nitems, &bestsolvalue);
if( nread < 2 )
{
SCIPwarningMessage(scip, "invalid input line %d in file <%s>: <%s>\n", lineno, filename, buffer);
return SCIP_READERROR;
}
SCIPdebugMessage("capacity = <%d>, number of items = <%d>, best known solution = <%d>\n", capacity, nitems, bestsolvalue);
}
/* allocate buffer memory for storing the weights and ids temporary */
SCIP_CALL( SCIPallocBufferArray(scip, &weights, nitems) );
SCIP_CALL( SCIPallocBufferArray(scip, &ids, nitems) );
/* pasre weights */
nweights = 0;
error = FALSE;
while( !SCIPfeof(file) && !error )
{
/* get next line */
if( SCIPfgets(buffer, sizeof(buffer), file) == NULL )
break;
lineno++;
/* parse the line */
nread = sscanf(buffer, "%d\n", &weight);
if( nread == 0 )
{
SCIPwarningMessage(scip, "invalid input line %d in file <%s>: <%s>\n", lineno, filename, buffer);
error = TRUE;
break;
}
SCIPdebugMessage("found weight %d <%d>\n", nweights, weight);
weights[nweights] = weight;
ids[nweights] = nweights;
nweights++;
if( nweights == nitems )
break;
}
if( nweights < nitems )
{
SCIPwarningMessage(scip, "set nitems from <%d> to <%d> since the file <%s> only contains <%d> weights\n", nitems, weights, filename, weights);
nitems = nweights;
}
if( !error )
{
/* create a new problem in SCIP */
SCIP_CALL( SCIPprobdataCreate(scip, name, ids, weights, nitems, (SCIP_Longint)capacity) );
}
(void)SCIPfclose(file);
SCIPfreeBufferArray(scip, &ids);
SCIPfreeBufferArray(scip, &weights);
if( error )
return SCIP_READERROR;
*result = SCIP_SUCCESS;
return SCIP_OKAY;
}
/** reads the next line from the input file into the line buffer; skips comments;
* returns whether a line could be read
*/
static
SCIP_Bool getNextLine(
SCIP* scip, /**< SCIP data structure */
LPINPUT* lpinput /**< LP reading data */
)
{
int i;
assert(lpinput != NULL);
/* if we previously detected a comment we have to parse the remaining line away if there is something left */
if( !lpinput->endline && lpinput->comment )
{
SCIPdebugMessage("Throwing rest of comment away.\n");
do
{
lpinput->linebuf[LP_MAX_LINELEN-2] = '\0';
(void)SCIPfgets(lpinput->linebuf, (int) sizeof(lpinput->linebuf), lpinput->file);
}
while( lpinput->linebuf[LP_MAX_LINELEN-2] != '\0' );
lpinput->comment = FALSE;
lpinput->endline = TRUE;
}
/* read next line */
lpinput->linepos = 0;
lpinput->linebuf[LP_MAX_LINELEN-2] = '\0';
if( SCIPfgets(lpinput->linebuf, (int) sizeof(lpinput->linebuf), lpinput->file) == NULL )
{
/* clear the line, this is really necessary here! */
BMSclearMemoryArray(lpinput->linebuf, LP_MAX_LINELEN);
return FALSE;
}
lpinput->linenumber++;
/* if line is too long for our buffer correct the buffer and correct position in file */
if( lpinput->linebuf[LP_MAX_LINELEN-2] != '\0' )
{
char* last;
/* buffer is full; erase last token since it might be incomplete */
lpinput->endline = FALSE;
last = strrchr(lpinput->linebuf, ' ');
if( last == NULL )
{
SCIPwarningMessage(scip, "we read %d characters from the file; this might indicate a corrupted input file!",
LP_MAX_LINELEN - 2);
lpinput->linebuf[LP_MAX_LINELEN-2] = '\0';
SCIPdebugMessage("the buffer might be corrupted\n");
}
else
{
SCIPfseek(lpinput->file, -(long) strlen(last) - 1, SEEK_CUR);
SCIPdebugMessage("correct buffer, reread the last %ld characters\n", (long) strlen(last) + 1);
*last = '\0';
}
}
else
{
/* found end of line */
lpinput->endline = TRUE;
}
lpinput->linebuf[LP_MAX_LINELEN-1] = '\0'; /* we want to use lookahead of one char -> we need two \0 at the end */
lpinput->comment = FALSE;
/* skip characters after comment symbol */
for( i = 0; commentchars[i] != '\0'; ++i )
{
char* commentstart;
commentstart = strchr(lpinput->linebuf, commentchars[i]);
if( commentstart != NULL )
{
*commentstart = '\0';
*(commentstart+1) = '\0'; /* we want to use lookahead of one char -> we need two \0 at the end */
lpinput->comment = TRUE;
break;
}
}
return TRUE;
}
/** execution method of primal heuristic */
static
SCIP_DECL_HEUREXEC(heurExecMutation)
{ /*lint --e{715}*/
SCIP_Longint maxnnodes;
SCIP_Longint nsubnodes; /* node limit for the subproblem */
SCIP_HEURDATA* heurdata; /* heuristic's data */
SCIP* subscip; /* the subproblem created by mutation */
SCIP_VAR** vars; /* original problem's variables */
SCIP_VAR** subvars; /* subproblem's variables */
SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
SCIP_Real cutoff; /* objective cutoff for the subproblem */
SCIP_Real maxnnodesr;
SCIP_Real memorylimit;
SCIP_Real timelimit; /* timelimit for the subproblem */
SCIP_Real upperbound;
int nvars; /* number of original problem's variables */
int i;
SCIP_Bool success;
SCIP_RETCODE retcode;
assert( heur != NULL );
assert( scip != NULL );
assert( result != NULL );
/* get heuristic's data */
heurdata = SCIPheurGetData(heur);
assert( heurdata != NULL );
*result = SCIP_DELAYED;
/* only call heuristic, if feasible solution is available */
if( SCIPgetNSols(scip) <= 0 )
return SCIP_OKAY;
/* only call heuristic, if the best solution comes from transformed problem */
assert( SCIPgetBestSol(scip) != NULL );
if( SCIPsolIsOriginal(SCIPgetBestSol(scip)) )
return SCIP_OKAY;
/* only call heuristic, if enough nodes were processed since last incumbent */
if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip,SCIPgetBestSol(scip)) < heurdata->nwaitingnodes)
return SCIP_OKAY;
*result = SCIP_DIDNOTRUN;
/* only call heuristic, if discrete variables are present */
if( SCIPgetNBinVars(scip) == 0 && SCIPgetNIntVars(scip) == 0 )
return SCIP_OKAY;
/* calculate the maximal number of branching nodes until heuristic is aborted */
maxnnodesr = heurdata->nodesquot * SCIPgetNNodes(scip);
/* reward mutation if it succeeded often, count the setup costs for the sub-MIP as 100 nodes */
maxnnodesr *= 1.0 + 2.0 * (SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur) + 1.0);
maxnnodes = (SCIP_Longint) maxnnodesr - 100 * SCIPheurGetNCalls(heur);
maxnnodes += heurdata->nodesofs;
/* determine the node limit for the current process */
nsubnodes = maxnnodes - heurdata->usednodes;
nsubnodes = MIN(nsubnodes, heurdata->maxnodes);
/* check whether we have enough nodes left to call subproblem solving */
if( nsubnodes < heurdata->minnodes )
return SCIP_OKAY;
if( SCIPisStopped(scip) )
return SCIP_OKAY;
*result = SCIP_DIDNOTFIND;
SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, NULL, NULL, NULL, NULL) );
/* initializing the subproblem */
SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
SCIP_CALL( SCIPcreate(&subscip) );
/* create the variable mapping hash map */
SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), SCIPcalcHashtableSize(5 * nvars)) );
if( heurdata->uselprows )
{
char probname[SCIP_MAXSTRLEN];
/* copy all plugins */
SCIP_CALL( SCIPincludeDefaultPlugins(subscip) );
/* get name of the original problem and add the string "_mutationsub" */
(void) SCIPsnprintf(probname, SCIP_MAXSTRLEN, "%s_mutationsub", SCIPgetProbName(scip));
/* create the subproblem */
SCIP_CALL( SCIPcreateProb(subscip, probname, NULL, NULL, NULL, NULL, NULL, NULL, NULL) );
/* copy all variables */
SCIP_CALL( SCIPcopyVars(scip, subscip, varmapfw, NULL, TRUE) );
}
else
{
SCIP_Bool valid;
valid = FALSE;
SCIP_CALL( SCIPcopy(scip, subscip, varmapfw, NULL, "rens", TRUE, FALSE, TRUE, &valid) );
if( heurdata->copycuts )
{
/* copies all active cuts from cutpool of sourcescip to linear constraints in targetscip */
SCIP_CALL( SCIPcopyCuts(scip, subscip, varmapfw, NULL, TRUE, NULL) );
}
SCIPdebugMessage("Copying the SCIP instance was %s complete.\n", valid ? "" : "not ");
}
for( i = 0; i < nvars; i++ )
subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
/* free hash map */
SCIPhashmapFree(&varmapfw);
/* create a new problem, which fixes variables with same value in bestsol and LP relaxation */
SCIP_CALL( createSubproblem(scip, subscip, subvars, heurdata->minfixingrate, &heurdata->randseed, heurdata->uselprows) );
/* do not abort subproblem on CTRL-C */
SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
/* disable output to console */
SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
/* check whether there is enough time and memory left */
SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
if( !SCIPisInfinity(scip, timelimit) )
timelimit -= SCIPgetSolvingTime(scip);
SCIP_CALL( SCIPgetRealParam(scip, "limits/memory", &memorylimit) );
/* substract the memory already used by the main SCIP and the estimated memory usage of external software */
if( !SCIPisInfinity(scip, memorylimit) )
{
memorylimit -= SCIPgetMemUsed(scip)/1048576.0;
memorylimit -= SCIPgetMemExternEstim(scip)/1048576.0;
}
/* abort if no time is left or not enough memory to create a copy of SCIP, including external memory usage */
if( timelimit <= 0.0 || memorylimit <= 2.0*SCIPgetMemExternEstim(scip)/1048576.0 )
goto TERMINATE;
/* set limits for the subproblem */
SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nsubnodes) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/time", timelimit) );
SCIP_CALL( SCIPsetRealParam(subscip, "limits/memory", memorylimit) );
/* forbid recursive call of heuristics and separators solving subMIPs */
SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
/* disable cutting plane separation */
SCIP_CALL( SCIPsetSeparating(subscip, SCIP_PARAMSETTING_OFF, TRUE) );
/* disable expensive presolving */
SCIP_CALL( SCIPsetPresolving(subscip, SCIP_PARAMSETTING_FAST, TRUE) );
/* use best estimate node selection */
if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
}
/* use inference branching */
if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
}
/* disable conflict analysis */
if( !SCIPisParamFixed(subscip, "conflict/useprop") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useprop", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/useinflp") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useinflp", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/useboundlp", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/usesb") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usesb", FALSE) );
}
if( !SCIPisParamFixed(subscip, "conflict/usepseudo") )
{
SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/usepseudo", FALSE) );
}
/* employ a limit on the number of enforcement rounds in the quadratic constraint handlers; this fixes the issue that
* sometimes the quadratic constraint handler needs hundreds or thousands of enforcement rounds to determine the
* feasibility status of a single node without fractional branching candidates by separation (namely for uflquad
* instances); however, the solution status of the sub-SCIP might get corrupted by this; hence no decutions shall be
* made for the original SCIP
*/
if( SCIPfindConshdlr(subscip, "quadratic") != NULL && !SCIPisParamFixed(subscip, "constraints/quadratic/enfolplimit") )
{
SCIP_CALL( SCIPsetIntParam(subscip, "constraints/quadratic/enfolplimit", 10) );
}
/* add an objective cutoff */
cutoff = SCIPinfinity(scip);
assert( !SCIPisInfinity(scip, SCIPgetUpperbound(scip)) );
upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
if( !SCIPisInfinity(scip, -1.0 * SCIPgetLowerbound(scip)) )
{
cutoff = (1-heurdata->minimprove) * SCIPgetUpperbound(scip) + heurdata->minimprove * SCIPgetLowerbound(scip);
}
else
{
if( SCIPgetUpperbound ( scip ) >= 0 )
cutoff = ( 1 - heurdata->minimprove ) * SCIPgetUpperbound ( scip );
else
cutoff = ( 1 + heurdata->minimprove ) * SCIPgetUpperbound ( scip );
}
cutoff = MIN(upperbound, cutoff );
SCIP_CALL( SCIPsetObjlimit(subscip, cutoff) );
/* solve the subproblem */
SCIPdebugMessage("Solve Mutation subMIP\n");
retcode = SCIPsolve(subscip);
/* Errors in solving the subproblem should not kill the overall solving process
* Hence, the return code is caught and a warning is printed, only in debug mode, SCIP will stop.
*/
if( retcode != SCIP_OKAY )
{
#ifndef NDEBUG
SCIP_CALL( retcode );
#endif
SCIPwarningMessage(scip, "Error while solving subproblem in Mutation heuristic; sub-SCIP terminated with code <%d>\n",retcode);
}
heurdata->usednodes += SCIPgetNNodes(subscip);
/* check, whether a solution was found */
if( SCIPgetNSols(subscip) > 0 )
{
SCIP_SOL** subsols;
int nsubsols;
/* check, whether a solution was found;
* due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
*/
nsubsols = SCIPgetNSols(subscip);
subsols = SCIPgetSols(subscip);
success = FALSE;
for( i = 0; i < nsubsols && !success; ++i )
{
SCIP_CALL( createNewSol(scip, subscip, subvars, heur, subsols[i], &success) );
}
if( success )
*result = SCIP_FOUNDSOL;
}
TERMINATE:
/* free subproblem */
SCIPfreeBufferArray(scip, &subvars);
SCIP_CALL( SCIPfree(&subscip) );
return SCIP_OKAY;
}
/** read objective sense, offset, and scale */
static
SCIP_RETCODE getObjective(
SCIP* scip, /**< SCIP data structure */
CIPINPUT* cipinput, /**< CIP parsing data */
SCIP_Real* objscale, /**< buffer where to multiply with objective scale */
SCIP_Real* objoffset /**< buffer where to add with objective offset */
)
{
char* buf;
char* name;
assert(objscale != NULL);
assert(objoffset != NULL);
buf = cipinput->strbuf;
if( strncmp(buf, "VARIABLES", 8) == 0 )
cipinput->section = CIP_VARS;
else if( strncmp(buf, "FIXED", 5) == 0 )
cipinput->section = CIP_FIXEDVARS;
else 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_OBJECTIVE )
return SCIP_OKAY;
SCIPdebugMessage("parse objective information\n");
/* remove white space */
while ( isspace((unsigned char)* buf) )
++buf;
if( strncasecmp(buf, "Sense", 5) == 0 )
{
SCIP_OBJSENSE objsense;
name = strchr(buf, ':');
if( name == NULL )
{
SCIPwarningMessage(scip, "did not find objective sense (line: %d):\n%s\n", cipinput->linenumber, cipinput->strbuf);
return SCIP_OKAY; /* no error - might work with default */
}
/* skip ':' */
++name;
/* remove white space in front of the name */
while( isspace((unsigned char)* name) )
++name;
if( strncasecmp(name, "minimize", 3) == 0 )
objsense = SCIP_OBJSENSE_MINIMIZE;
else if( strncasecmp(name, "maximize", 3) == 0 )
objsense = SCIP_OBJSENSE_MAXIMIZE;
else
{
SCIPwarningMessage(scip, "unknown objective sense '%s' (line: %d):\n%s\n", name, cipinput->linenumber, cipinput->strbuf);
return SCIP_OKAY; /* no error - might work with default */
}
/* set problem name */
SCIP_CALL( SCIPsetObjsense(scip, objsense) );
SCIPdebugMessage("objective sense <%s>\n", objsense == SCIP_OBJSENSE_MINIMIZE ? "minimize" : "maximize");
}
else if( strncasecmp(buf, "Offset", 6) == 0 )
{
SCIP_Real off = 0;
char* endptr;
name = strchr(buf, ':');
if( name == NULL )
{
SCIPwarningMessage(scip, "did not find offset (line: %d)\n", cipinput->linenumber);
return SCIP_OKAY;
}
/* skip ':' */
++name;
/* remove white space in front of the name */
while(isspace((unsigned char)*name))
++name;
if ( SCIPstrToRealValue(name, &off, &endptr) )
{
*objoffset += off;
SCIPdebugMessage("offset <%g> (total: %g)\n", off, *objoffset);
}
else
{
SCIPwarningMessage(scip, "could not parse offset (line: %d)\n%s\n", cipinput->linenumber, cipinput->strbuf);
return SCIP_OKAY;
}
}
else if( strncasecmp(buf, "Scale", 5) == 0 )
{
SCIP_Real scale = 1.0;
char* endptr;
name = strchr(buf, ':');
if( name == NULL )
{
SCIPwarningMessage(scip, "did not find scale (line: %d)\n", cipinput->linenumber);
return SCIP_OKAY;
}
/* skip ':' */
++name;
/* remove white space in front of the name */
while(isspace((unsigned char)*name))
++name;
if ( SCIPstrToRealValue(name, &scale, &endptr) )
{
*objscale *= scale;
SCIPdebugMessage("objscale <%g> (total: %g)\n", scale, *objscale);
}
else
{
SCIPwarningMessage(scip, "could not parse objective scale (line: %d)\n%s\n", cipinput->linenumber, cipinput->strbuf);
return SCIP_OKAY;
}
}
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;
}
/** reads an objective or constraint with name and coefficients */
static
SCIP_RETCODE readCoefficients(
SCIP* scip, /**< SCIP data structure */
LPINPUT* lpinput, /**< LP reading data */
SCIP_Bool isobjective, /**< indicates whether we are currently reading the coefficients of the objective */
char* name, /**< pointer to store the name of the line; must be at least of size
* LP_MAX_LINELEN */
SCIP_VAR*** vars, /**< pointer to store the array with variables (must be freed by caller) */
SCIP_Real** coefs, /**< pointer to store the array with coefficients (must be freed by caller) */
int* ncoefs, /**< pointer to store the number of coefficients */
SCIP_Bool* newsection /**< pointer to store whether a new section was encountered */
)
{
SCIP_Bool havesign;
SCIP_Bool havevalue;
SCIP_Real coef;
int coefsign;
int coefssize;
assert(lpinput != NULL);
assert(name != NULL);
assert(vars != NULL);
assert(coefs != NULL);
assert(ncoefs != NULL);
assert(newsection != NULL);
*vars = NULL;
*coefs = NULL;
*name = '\0';
*ncoefs = 0;
*newsection = FALSE;
/* read the first token, which may be the name of the line */
if( getNextToken(scip, lpinput) )
{
/* check if we reached a new section */
if( isNewSection(scip, lpinput) )
{
*newsection = TRUE;
return SCIP_OKAY;
}
/* remember the token in the token buffer */
swapTokenBuffer(lpinput);
/* get the next token and check, whether it is a colon */
if( getNextToken(scip, lpinput) )
{
if( strcmp(lpinput->token, ":") == 0 )
{
/* the second token was a colon: the first token is the line name */
(void)SCIPmemccpy(name, lpinput->tokenbuf, '\0', LP_MAX_LINELEN);
name[LP_MAX_LINELEN - 1] = '\0';
SCIPdebugMessage("(line %d) read constraint name: '%s'\n", lpinput->linenumber, name);
}
else
{
/* the second token was no colon: push the tokens back onto the token stack and parse them as coefficients */
pushToken(lpinput);
pushBufferToken(lpinput);
}
}
else
{
/* there was only one token left: push it back onto the token stack and parse it as coefficient */
pushBufferToken(lpinput);
}
}
/* initialize buffers for storing the coefficients */
coefssize = LP_INIT_COEFSSIZE;
SCIP_CALL( SCIPallocMemoryArray(scip, vars, coefssize) );
SCIP_CALL( SCIPallocMemoryArray(scip, coefs, coefssize) );
/* read the coefficients */
coefsign = +1;
coef = 1.0;
havesign = FALSE;
havevalue = FALSE;
*ncoefs = 0;
while( getNextToken(scip, lpinput) )
{
SCIP_VAR* var;
/* check if we read a sign */
if( isSign(lpinput, &coefsign) )
{
SCIPdebugMessage("(line %d) read coefficient sign: %+d\n", lpinput->linenumber, coefsign);
havesign = TRUE;
continue;
}
/* check if we read a value */
if( isValue(scip, lpinput, &coef) )
{
SCIPdebugMessage("(line %d) read coefficient value: %g with sign %+d\n", lpinput->linenumber, coef, coefsign);
if( havevalue )
{
syntaxError(scip, lpinput, "two consecutive values.");
return SCIP_OKAY;
}
havevalue = TRUE;
continue;
}
/* check if we reached an equation sense */
if( isSense(lpinput, NULL) )
{
if( isobjective )
{
syntaxError(scip, lpinput, "no sense allowed in objective");
return SCIP_OKAY;
}
/* put the sense back onto the token stack */
pushToken(lpinput);
break;
}
/* check if we reached a new section, that will be only allowed when having no current sign and value and if we
* are not in the quadratic part
*/
if( (isobjective || (!havevalue && !havesign)) && isNewSection(scip, lpinput) )
{
if( havesign && !havevalue )
{
SCIPwarningMessage(scip, "skipped single sign %c without value or variable in objective\n", coefsign == 1 ? '+' : '-');
}
else if( isobjective && havevalue && !SCIPisZero(scip, coef) )
{
SCIPwarningMessage(scip, "constant term %+g in objective is skipped\n", coef * coefsign);
}
*newsection = TRUE;
return SCIP_OKAY;
}
/* check if we start a quadratic part */
if( *lpinput->token == '[' )
{
syntaxError(scip, lpinput, "diff reader does not support quadratic objective function.");
return SCIP_READERROR;
}
/* all but the first coefficient need a sign */
if( *ncoefs > 0 && !havesign )
{
syntaxError(scip, lpinput, "expected sign ('+' or '-') or sense ('<' or '>').");
return SCIP_OKAY;
}
/* check if the last variable should be squared */
if( *lpinput->token == '^' )
{
syntaxError(scip, lpinput, "diff reader does not support quadratic objective function.");
return SCIP_READERROR;
}
else
{
/* the token is a variable name: get the corresponding variable */
SCIP_CALL( getVariable(scip, lpinput->token, &var) );
}
/* insert the linear coefficient */
SCIPdebugMessage("(line %d) read linear coefficient: %+g<%s>\n", lpinput->linenumber, coefsign * coef, SCIPvarGetName(var));
if( !SCIPisZero(scip, coef) )
{
/* resize the vars and coefs array if needed */
if( *ncoefs >= coefssize )
{
coefssize *= 2;
coefssize = MAX(coefssize, (*ncoefs)+1);
SCIP_CALL( SCIPreallocMemoryArray(scip, vars, coefssize) );
SCIP_CALL( SCIPreallocMemoryArray(scip, coefs, coefssize) );
}
assert(*ncoefs < coefssize);
/* add coefficient */
(*vars)[*ncoefs] = var;
(*coefs)[*ncoefs] = coefsign * coef;
(*ncoefs)++;
}
/* reset the flags and coefficient value for the next coefficient */
coefsign = +1;
coef = 1.0;
havesign = FALSE;
havevalue = FALSE;
}
return SCIP_OKAY;
}
