Scippy

SCIP

Solving Constraint Integer Programs

heur_mutation.c
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4 /* SCIP --- Solving Constraint Integer Programs */
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24 
25 /**@file heur_mutation.c
26  * @ingroup DEFPLUGINS_HEUR
27  * @brief LNS heuristic that tries to randomly mutate the incumbent solution
28  * @author Timo Berthold
29  */
30 
31 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
32 
33 #include "blockmemshell/memory.h"
34 #include "scip/heuristics.h"
35 #include "scip/heur_mutation.h"
36 #include "scip/pub_heur.h"
37 #include "scip/pub_message.h"
38 #include "scip/pub_misc.h"
39 #include "scip/pub_sol.h"
40 #include "scip/pub_var.h"
41 #include "scip/scip_branch.h"
42 #include "scip/scip_cons.h"
43 #include "scip/scip_copy.h"
44 #include "scip/scip_general.h"
45 #include "scip/scip_heur.h"
46 #include "scip/scip_mem.h"
47 #include "scip/scip_message.h"
48 #include "scip/scip_nodesel.h"
49 #include "scip/scip_numerics.h"
50 #include "scip/scip_param.h"
51 #include "scip/scip_prob.h"
52 #include "scip/scip_randnumgen.h"
53 #include "scip/scip_sol.h"
54 #include "scip/scip_solve.h"
55 #include "scip/scip_solvingstats.h"
56 #include <string.h>
57 
58 #define HEUR_NAME "mutation"
59 #define HEUR_DESC "mutation heuristic randomly fixing variables"
60 #define HEUR_DISPCHAR SCIP_HEURDISPCHAR_LNS
61 #define HEUR_PRIORITY -1103010
62 #define HEUR_FREQ -1
63 #define HEUR_FREQOFS 8
64 #define HEUR_MAXDEPTH -1
65 #define HEUR_TIMING SCIP_HEURTIMING_AFTERNODE
66 #define HEUR_USESSUBSCIP TRUE /**< does the heuristic use a secondary SCIP instance? */
67 
68 #define DEFAULT_NODESOFS 500 /**< number of nodes added to the contingent of the total nodes */
69 #define DEFAULT_MAXNODES 5000 /**< maximum number of nodes to regard in the subproblem */
70 #define DEFAULT_MINIMPROVE 0.01 /**< factor by which Mutation should at least improve the incumbent */
71 #define DEFAULT_MINNODES 500 /**< minimum number of nodes to regard in the subproblem */
72 #define DEFAULT_MINFIXINGRATE 0.8 /**< minimum percentage of integer variables that have to be fixed */
73 #define DEFAULT_NODESQUOT 0.1 /**< subproblem nodes in relation to nodes of the original problem */
74 #define DEFAULT_NWAITINGNODES 200 /**< number of nodes without incumbent change that heuristic should wait */
75 #define DEFAULT_USELPROWS FALSE /**< should subproblem be created out of the rows in the LP rows,
76  * otherwise, the copy constructors of the constraints handlers are used */
77 #define DEFAULT_COPYCUTS TRUE /**< if DEFAULT_USELPROWS is FALSE, then should all active cuts from the
78  * cutpool of the original scip be copied to constraints of the subscip */
79 #define DEFAULT_BESTSOLLIMIT -1 /**< limit on number of improving incumbent solutions in sub-CIP */
80 #define DEFAULT_USEUCT FALSE /**< should uct node selection be used at the beginning of the search? */
81 #define DEFAULT_RANDSEED 19 /**< initial random seed */
82 /*
83  * Data structures
84  */
85 
86 /** primal heuristic data */
87 struct SCIP_HeurData
88 {
89  int nodesofs; /**< number of nodes added to the contingent of the total nodes */
90  int maxnodes; /**< maximum number of nodes to regard in the subproblem */
91  int minnodes; /**< minimum number of nodes to regard in the subproblem */
92  SCIP_Real minfixingrate; /**< minimum percentage of integer variables that have to be fixed */
93  int nwaitingnodes; /**< number of nodes without incumbent change that heuristic should wait */
94  SCIP_Real minimprove; /**< factor by which Mutation should at least improve the incumbent */
95  SCIP_Longint usednodes; /**< nodes already used by Mutation in earlier calls */
96  SCIP_Real nodesquot; /**< subproblem nodes in relation to nodes of the original problem */
97  SCIP_RANDNUMGEN* randnumgen; /**< random number generator */
98  SCIP_Bool uselprows; /**< should subproblem be created out of the rows in the LP rows? */
99  SCIP_Bool copycuts; /**< if uselprows == FALSE, should all active cuts from cutpool be copied
100  * to constraints in subproblem?
101  */
102  int bestsollimit; /**< limit on number of improving incumbent solutions in sub-CIP */
103  SCIP_Bool useuct; /**< should uct node selection be used at the beginning of the search? */
104 };
105 
106 
107 /*
108  * Local methods
109  */
110 
111 /** determine variables and values which should be fixed in the mutation subproblem */
112 static
114  SCIP* scip, /**< original SCIP data structure */
115  SCIP_VAR** fixedvars, /**< array to store the variables that should be fixed in the subproblem */
116  SCIP_Real* fixedvals, /**< array to store the fixing values to fix variables in the subproblem */
117  int* nfixedvars, /**< pointer to store the number of variables that should be fixed */
118  SCIP_Real minfixingrate, /**< percentage of integer variables that have to be fixed */
119  SCIP_RANDNUMGEN* randnumgen, /**< random number generator */
120  SCIP_Bool* success /**< used to store whether the creation of the subproblem worked */
121  )
122 {
123  SCIP_VAR** vars; /* original scip variables */
124  SCIP_SOL* sol; /* pool of solutions */
125 
126  int nvars;
127  int nbinvars;
128  int nintvars;
129  int ndiscretevars;
130  int i;
131 
132  assert(fixedvars != NULL);
133  assert(fixedvals != NULL);
134 
135  /* get required data of the original problem */
136  SCIP_CALL( SCIPgetVarsData(scip, &vars, &nvars, &nbinvars, &nintvars, NULL, NULL) );
137  sol = SCIPgetBestSol(scip);
138  assert(sol != NULL);
139 
140  /* compute the number of variables that should be fixed in the subproblem */
141  *nfixedvars = (int)(minfixingrate * (nbinvars + nintvars));
142 
143  /* avoid the two corner cases that no or all discrete variables should be fixed */
144  if( *nfixedvars == 0 || *nfixedvars == nbinvars + nintvars )
145  {
146  *success = FALSE;
147  return SCIP_OKAY;
148  }
149  assert(*nfixedvars < nbinvars + nintvars);
150 
151  ndiscretevars = nbinvars + nintvars;
152  /* copy the binary and integer variables into fixedvars */
153  BMScopyMemoryArray(fixedvars, vars, ndiscretevars);
154 
155  /* shuffle the array randomly */
156  SCIPrandomPermuteArray(randnumgen, (void **)fixedvars, 0, nbinvars + nintvars);
157 
158  *success = TRUE;
159  /* store the fixing values for the subset of variables that should be fixed */
160  for( i = 0; i < *nfixedvars; ++i )
161  {
162  /* fix all randomly marked variables */
163  SCIP_Real solval;
164  SCIP_Real lb;
165  SCIP_Real ub;
166 
167  solval = SCIPgetSolVal(scip, sol, fixedvars[i]);
168  lb = SCIPvarGetLbGlobal(fixedvars[i]);
169  ub = SCIPvarGetUbGlobal(fixedvars[i]);
170  assert(SCIPisLE(scip, lb, ub));
171 
172  /* due to dual reductions, it may happen that the solution value is not in
173  the variable's domain anymore */
174  if( SCIPisLT(scip, solval, lb) )
175  solval = lb;
176  else if( SCIPisGT(scip, solval, ub) )
177  solval = ub;
178 
179  /* we cannot fix to infinite solution values, better break in this case */
180  if( SCIPisInfinity(scip, REALABS(solval)) )
181  {
182  *success = FALSE;
183  break;
184  }
185 
186  /* store the possibly adjusted solution value as fixing value */
187  fixedvals[i] = solval;
188  }
189 
190  return SCIP_OKAY;
191 }
192 
193 /** setup and solve mutation sub-SCIP */
194 static
196  SCIP* scip, /**< SCIP data structure */
197  SCIP* subscip, /**< sub-SCIP data structure */
198  SCIP_HEUR* heur, /**< mutation heuristic */
199  SCIP_VAR** fixedvars, /**< array to store the variables that should be fixed in the subproblem */
200  SCIP_Real* fixedvals, /**< array to store the fixing values to fix variables in the subproblem */
201  int nfixedvars, /**< the number of variables that should be fixed */
202  SCIP_Longint nsubnodes, /**< node limit for the subproblem */
203  SCIP_RESULT* result /**< pointer to store the result */
204  )
205 {
206  SCIP_VAR** subvars; /* subproblem's variables */
207  SCIP_VAR** vars; /* original problem's variables */
208  SCIP_HASHMAP* varmapfw; /* mapping of SCIP variables to sub-SCIP variables */
209  SCIP_HEURDATA* heurdata;
210  SCIP_Real cutoff; /* objective cutoff for the subproblem */
211  SCIP_Real upperbound;
212  int nvars; /* number of original problem's variables */
213  int i;
214  SCIP_Bool success;
215 
216  assert(scip != NULL);
217  assert(subscip != NULL);
218  assert(heur != NULL);
219  assert(fixedvars != NULL);
220  assert(fixedvals != NULL);
221 
222  heurdata = SCIPheurGetData(heur);
223  assert(heurdata != NULL);
224 
225  vars = SCIPgetVars(scip);
226  nvars = SCIPgetNVars(scip);
227 
228  SCIP_CALL( SCIPallocBufferArray(scip, &subvars, nvars) );
229 
230  /* create the variable mapping hash map */
231  SCIP_CALL( SCIPhashmapCreate(&varmapfw, SCIPblkmem(subscip), nvars) );
232 
233  /* create a problem copy as sub SCIP */
234  SCIP_CALL( SCIPcopyLargeNeighborhoodSearch(scip, subscip, varmapfw, "mutation", fixedvars, fixedvals, nfixedvars,
235  heurdata->uselprows, heurdata->copycuts, &success, NULL) );
236 
237  for( i = 0; i < nvars; i++ )
238  subvars[i] = (SCIP_VAR*) SCIPhashmapGetImage(varmapfw, vars[i]);
239 
240  /* free hash map */
241  SCIPhashmapFree(&varmapfw);
242 
243  /* do not abort subproblem on CTRL-C */
244  SCIP_CALL( SCIPsetBoolParam(subscip, "misc/catchctrlc", FALSE) );
245 
246 #ifdef SCIP_DEBUG
247  /* for debugging, enable full output */
248  SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 5) );
249  SCIP_CALL( SCIPsetIntParam(subscip, "display/freq", 100000000) );
250 #else
251  /* disable statistic timing inside sub SCIP and output to console */
252  SCIP_CALL( SCIPsetIntParam(subscip, "display/verblevel", 0) );
253  SCIP_CALL( SCIPsetBoolParam(subscip, "timing/statistictiming", FALSE) );
254 #endif
255 
256  /* set limits for the subproblem */
257  SCIP_CALL( SCIPcopyLimits(scip, subscip) );
258  SCIP_CALL( SCIPsetLongintParam(subscip, "limits/nodes", nsubnodes) );
259  SCIP_CALL( SCIPsetIntParam(subscip, "limits/bestsol", heurdata->bestsollimit) );
260 
261  /* forbid recursive call of heuristics and separators solving subMIPs */
262  SCIP_CALL( SCIPsetSubscipsOff(subscip, TRUE) );
263 
264  /* disable cutting plane separation */
266 
267  /* disable expensive presolving */
269 
270  /* use best estimate node selection */
271  if( SCIPfindNodesel(subscip, "estimate") != NULL && !SCIPisParamFixed(subscip, "nodeselection/estimate/stdpriority") )
272  {
273  SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/estimate/stdpriority", INT_MAX/4) );
274  }
275 
276  /* activate uct node selection at the top of the tree */
277  if( heurdata->useuct && SCIPfindNodesel(subscip, "uct") != NULL && !SCIPisParamFixed(subscip, "nodeselection/uct/stdpriority") )
278  {
279  SCIP_CALL( SCIPsetIntParam(subscip, "nodeselection/uct/stdpriority", INT_MAX/2) );
280  }
281 
282  /* use inference branching */
283  if( SCIPfindBranchrule(subscip, "inference") != NULL && !SCIPisParamFixed(subscip, "branching/inference/priority") )
284  {
285  SCIP_CALL( SCIPsetIntParam(subscip, "branching/inference/priority", INT_MAX/4) );
286  }
287 
288  /* enable conflict analysis, disable analysis of boundexceeding LPs, and restrict conflict pool */
289  if( !SCIPisParamFixed(subscip, "conflict/enable") )
290  {
291  SCIP_CALL( SCIPsetBoolParam(subscip, "conflict/enable", TRUE) );
292  }
293  if( !SCIPisParamFixed(subscip, "conflict/useboundlp") )
294  {
295  SCIP_CALL( SCIPsetCharParam(subscip, "conflict/useboundlp", 'o') );
296  }
297  if( !SCIPisParamFixed(subscip, "conflict/maxstoresize") )
298  {
299  SCIP_CALL( SCIPsetIntParam(subscip, "conflict/maxstoresize", 100) );
300  }
301 
302  /* speed up sub-SCIP by not checking dual LP feasibility */
303  SCIP_CALL( SCIPsetBoolParam(subscip, "lp/checkdualfeas", FALSE) );
304 
305  /* add an objective cutoff */
306  assert( !SCIPisInfinity(scip, SCIPgetUpperbound(scip)) );
307 
308  upperbound = SCIPgetUpperbound(scip) - SCIPsumepsilon(scip);
309  if( !SCIPisInfinity(scip, -1.0 * SCIPgetLowerbound(scip)) )
310  {
311  cutoff = (1 - heurdata->minimprove) * SCIPgetUpperbound(scip)
312  + heurdata->minimprove * SCIPgetLowerbound(scip);
313  }
314  else
315  {
316  if( SCIPgetUpperbound(scip) >= 0 )
317  cutoff = (1 - heurdata->minimprove) * SCIPgetUpperbound(scip);
318  else
319  cutoff = (1 + heurdata->minimprove) * SCIPgetUpperbound(scip);
320  }
321  cutoff = MIN(upperbound, cutoff);
322  SCIP_CALL(SCIPsetObjlimit(subscip, cutoff));
323 
324  /* solve the subproblem
325  *
326  * Errors in solving the subproblem should not kill the overall solving process
327  * Hence, the return code is caught but only in debug mode, SCIP will stop.
328  */
329  SCIPdebugMsg(scip, "Solve Mutation subMIP\n");
330  SCIP_CALL_ABORT( SCIPsolve(subscip) );
331 
332  /* transfer variable statistics from sub-SCIP */
333  SCIP_CALL( SCIPmergeVariableStatistics(subscip, scip, subvars, vars, nvars) );
334 
335  /* print solving statistics of subproblem if we are in SCIP's debug mode */
337 
338  heurdata->usednodes += SCIPgetNNodes(subscip);
339 
340  /* check, whether a solution was found;
341  * due to numerics, it might happen that not all solutions are feasible -> try all solutions until one was accepted
342  */
343  SCIP_CALL( SCIPtranslateSubSols(scip, subscip, heur, subvars, &success, NULL) );
344  if( success )
345  *result = SCIP_FOUNDSOL;
346 
347  /* free subproblem */
348  SCIPfreeBufferArray(scip, &subvars);
349 
350  return SCIP_OKAY;
351 }
352 
353 
354 /*
355  * Callback methods of primal heuristic
356  */
357 
358 /** copy method for primal heuristic plugins (called when SCIP copies plugins) */
359 static
360 SCIP_DECL_HEURCOPY(heurCopyMutation)
361 { /*lint --e{715}*/
362  assert(scip != NULL);
363  assert(heur != NULL);
364  assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
365 
366  /* call inclusion method of primal heuristic */
368 
369  return SCIP_OKAY;
370 }
371 
372 /** destructor of primal heuristic to free user data (called when SCIP is exiting) */
373 static
374 SCIP_DECL_HEURFREE(heurFreeMutation)
375 { /*lint --e{715}*/
376  SCIP_HEURDATA* heurdata;
377 
378  assert(heur != NULL);
379  assert(scip != NULL);
380 
381  /* get heuristic data */
382  heurdata = SCIPheurGetData(heur);
383  assert(heurdata != NULL);
384 
385  /* free heuristic data */
386  SCIPfreeBlockMemory(scip, &heurdata);
387  SCIPheurSetData(heur, NULL);
388 
389  return SCIP_OKAY;
390 }
391 
392 /** initialization method of primal heuristic (called after problem was transformed) */
393 static
394 SCIP_DECL_HEURINIT(heurInitMutation)
395 { /*lint --e{715}*/
396  SCIP_HEURDATA* heurdata;
397 
398  assert(heur != NULL);
399  assert(scip != NULL);
400 
401  /* get heuristic's data */
402  heurdata = SCIPheurGetData(heur);
403  assert(heurdata != NULL);
404 
405  /* initialize data */
406  heurdata->usednodes = 0;
407 
408  /* create random number generator */
409  SCIP_CALL( SCIPcreateRandom(scip, &heurdata->randnumgen,
411 
412  return SCIP_OKAY;
413 }
414 
415 /** deinitialization method of primal heuristic */
416 static
417 SCIP_DECL_HEUREXIT(heurExitMutation)
418 { /*lint --e{715}*/
419  SCIP_HEURDATA* heurdata;
420 
421  assert(heur != NULL);
422  assert(scip != NULL);
423 
424  /* get heuristic data */
425  heurdata = SCIPheurGetData(heur);
426  assert(heurdata != NULL);
427 
428  /* free random number generator */
429  SCIPfreeRandom(scip, &heurdata->randnumgen);
430 
431  return SCIP_OKAY;
432 }
433 
434 /** execution method of primal heuristic */
435 static
436 SCIP_DECL_HEUREXEC(heurExecMutation)
437 { /*lint --e{715}*/
438  SCIP_Longint maxnnodes;
439  SCIP_Longint nsubnodes; /* node limit for the subproblem */
440 
441  SCIP_HEURDATA* heurdata; /* heuristic's data */
442  SCIP* subscip; /* the subproblem created by mutation */
443  SCIP_VAR** fixedvars; /* array to store variables that should be fixed in the subproblem */
444  SCIP_Real* fixedvals; /* array to store fixing values for the variables */
445 
446  SCIP_Real maxnnodesr;
447 
448  int nfixedvars;
449  int nbinvars;
450  int nintvars;
451 
452  SCIP_Bool success;
453 
454  SCIP_RETCODE retcode;
455 
456  assert( heur != NULL );
457  assert( scip != NULL );
458  assert( result != NULL );
459 
460  /* get heuristic's data */
461  heurdata = SCIPheurGetData(heur);
462  assert(heurdata != NULL);
463 
464  *result = SCIP_DELAYED;
465 
466  /* only call heuristic, if feasible solution is available */
467  if( SCIPgetNSols(scip) <= 0 )
468  return SCIP_OKAY;
469 
470  /* only call heuristic, if the best solution comes from transformed problem */
471  assert(SCIPgetBestSol(scip) != NULL);
472  if( SCIPsolIsOriginal(SCIPgetBestSol(scip)) )
473  return SCIP_OKAY;
474 
475  /* only call heuristic, if enough nodes were processed since last incumbent */
476  if( SCIPgetNNodes(scip) - SCIPgetSolNodenum(scip,SCIPgetBestSol(scip)) < heurdata->nwaitingnodes)
477  return SCIP_OKAY;
478 
479  *result = SCIP_DIDNOTRUN;
480 
481  SCIP_CALL( SCIPgetVarsData(scip, NULL, NULL, &nbinvars, &nintvars, NULL, NULL) );
482 
483  /* only call heuristic, if discrete variables are present */
484  if( nbinvars + nintvars == 0 )
485  return SCIP_OKAY;
486 
487  /* calculate the maximal number of branching nodes until heuristic is aborted */
488  maxnnodesr = heurdata->nodesquot * SCIPgetNNodes(scip);
489 
490  /* reward mutation if it succeeded often, count the setup costs for the sub-MIP as 100 nodes */
491  maxnnodesr *= 1.0 + 2.0 * (SCIPheurGetNBestSolsFound(heur)+1.0)/(SCIPheurGetNCalls(heur) + 1.0);
492  maxnnodes = (SCIP_Longint) maxnnodesr - 100 * SCIPheurGetNCalls(heur);
493  maxnnodes += heurdata->nodesofs;
494 
495  /* determine the node limit for the current process */
496  nsubnodes = maxnnodes - heurdata->usednodes;
497  nsubnodes = MIN(nsubnodes, heurdata->maxnodes);
498 
499  /* check whether we have enough nodes left to call subproblem solving */
500  if( nsubnodes < heurdata->minnodes )
501  return SCIP_OKAY;
502 
503  if( SCIPisStopped(scip) )
504  return SCIP_OKAY;
505 
506  /* check whether there is enough time and memory left */
507  SCIP_CALL( SCIPcheckCopyLimits(scip, &success) );
508 
509  if( !success )
510  return SCIP_OKAY;
511 
512  SCIP_CALL( SCIPallocBufferArray(scip, &fixedvars, nbinvars + nintvars) );
513  SCIP_CALL( SCIPallocBufferArray(scip, &fixedvals, nbinvars + nintvars) );
514 
515  /* determine variables that should be fixed in the mutation subproblem */
516  SCIP_CALL( determineVariableFixings(scip, fixedvars, fixedvals, &nfixedvars, heurdata->minfixingrate, heurdata->randnumgen, &success) );
517 
518  /* terminate if it is not possible to create the subproblem */
519  if( !success )
520  {
521  SCIPdebugMsg(scip, "Could not create the subproblem -> skip call\n");
522  goto TERMINATE;
523  }
524 
525  *result = SCIP_DIDNOTFIND;
526 
527  /* initializing the subproblem */
528  SCIP_CALL( SCIPcreate(&subscip) );
529 
530  /* setup and solve the subproblem and catch the return code */
531  retcode = setupAndSolveSubscipMutation(scip, subscip, heur, fixedvars, fixedvals, nfixedvars, nsubnodes, result);
532 
533  /* free the subscip in any case */
534  SCIP_CALL( SCIPfree(&subscip) );
535  SCIP_CALL( retcode );
536 
537  /* free storage for subproblem fixings */
538  TERMINATE:
539  SCIPfreeBufferArray(scip, &fixedvals);
540  SCIPfreeBufferArray(scip, &fixedvars);
541 
542  return SCIP_OKAY;
543 }
544 
545 /*
546  * primal heuristic specific interface methods
547  */
548 
549 /** creates the mutation primal heuristic and includes it in SCIP */
551  SCIP* scip /**< SCIP data structure */
552  )
553 {
554  SCIP_HEURDATA* heurdata;
555  SCIP_HEUR* heur;
556 
557  /* create Mutation primal heuristic data */
558  SCIP_CALL( SCIPallocBlockMemory(scip, &heurdata) );
559 
560  /* include primal heuristic */
561  SCIP_CALL( SCIPincludeHeurBasic(scip, &heur,
563  HEUR_MAXDEPTH, HEUR_TIMING, HEUR_USESSUBSCIP, heurExecMutation, heurdata) );
564 
565  assert(heur != NULL);
566 
567  /* set non-NULL pointers to callback methods */
568  SCIP_CALL( SCIPsetHeurCopy(scip, heur, heurCopyMutation) );
569  SCIP_CALL( SCIPsetHeurFree(scip, heur, heurFreeMutation) );
570  SCIP_CALL( SCIPsetHeurInit(scip, heur, heurInitMutation) );
571  SCIP_CALL( SCIPsetHeurExit(scip, heur, heurExitMutation) );
572 
573  /* add mutation primal heuristic parameters */
574  SCIP_CALL( SCIPaddIntParam(scip, "heuristics/" HEUR_NAME "/nodesofs",
575  "number of nodes added to the contingent of the total nodes",
576  &heurdata->nodesofs, FALSE, DEFAULT_NODESOFS, 0, INT_MAX, NULL, NULL) );
577 
578  SCIP_CALL( SCIPaddIntParam(scip, "heuristics/" HEUR_NAME "/maxnodes",
579  "maximum number of nodes to regard in the subproblem",
580  &heurdata->maxnodes, TRUE, DEFAULT_MAXNODES, 0, INT_MAX, NULL, NULL) );
581 
582  SCIP_CALL( SCIPaddIntParam(scip, "heuristics/" HEUR_NAME "/minnodes",
583  "minimum number of nodes required to start the subproblem",
584  &heurdata->minnodes, TRUE, DEFAULT_MINNODES, 0, INT_MAX, NULL, NULL) );
585 
586  SCIP_CALL( SCIPaddIntParam(scip, "heuristics/" HEUR_NAME "/nwaitingnodes",
587  "number of nodes without incumbent change that heuristic should wait",
588  &heurdata->nwaitingnodes, TRUE, DEFAULT_NWAITINGNODES, 0, INT_MAX, NULL, NULL) );
589 
590  SCIP_CALL( SCIPaddRealParam(scip, "heuristics/" HEUR_NAME "/nodesquot",
591  "contingent of sub problem nodes in relation to the number of nodes of the original problem",
592  &heurdata->nodesquot, FALSE, DEFAULT_NODESQUOT, 0.0, 1.0, NULL, NULL) );
593 
594  SCIP_CALL( SCIPaddRealParam(scip, "heuristics/" HEUR_NAME "/minfixingrate",
595  "percentage of integer variables that have to be fixed",
596  &heurdata->minfixingrate, FALSE, DEFAULT_MINFIXINGRATE, SCIPsumepsilon(scip), 1.0-SCIPsumepsilon(scip), NULL, NULL) );
597 
598  SCIP_CALL( SCIPaddRealParam(scip, "heuristics/" HEUR_NAME "/minimprove",
599  "factor by which " HEUR_NAME " should at least improve the incumbent",
600  &heurdata->minimprove, TRUE, DEFAULT_MINIMPROVE, 0.0, 1.0, NULL, NULL) );
601 
602  SCIP_CALL( SCIPaddBoolParam(scip, "heuristics/" HEUR_NAME "/uselprows",
603  "should subproblem be created out of the rows in the LP rows?",
604  &heurdata->uselprows, TRUE, DEFAULT_USELPROWS, NULL, NULL) );
605 
606  SCIP_CALL( SCIPaddBoolParam(scip, "heuristics/" HEUR_NAME "/copycuts",
607  "if uselprows == FALSE, should all active cuts from cutpool be copied to constraints in subproblem?",
608  &heurdata->copycuts, TRUE, DEFAULT_COPYCUTS, NULL, NULL) );
609 
610  SCIP_CALL( SCIPaddIntParam(scip, "heuristics/" HEUR_NAME "/bestsollimit",
611  "limit on number of improving incumbent solutions in sub-CIP",
612  &heurdata->bestsollimit, FALSE, DEFAULT_BESTSOLLIMIT, -1, INT_MAX, NULL, NULL) );
613 
614  SCIP_CALL( SCIPaddBoolParam(scip, "heuristics/" HEUR_NAME "/useuct",
615  "should uct node selection be used at the beginning of the search?",
616  &heurdata->useuct, TRUE, DEFAULT_USEUCT, NULL, NULL) );
617 
618  return SCIP_OKAY;
619 }
enum SCIP_Result SCIP_RESULT
Definition: type_result.h:61
SCIP_Bool SCIPsolIsOriginal(SCIP_SOL *sol)
Definition: sol.c:2721
#define DEFAULT_COPYCUTS
Definition: heur_mutation.c:78
void SCIPfreeRandom(SCIP *scip, SCIP_RANDNUMGEN **randnumgen)
static SCIP_DECL_HEURCOPY(heurCopyMutation)
static SCIP_DECL_HEUREXIT(heurExitMutation)
SCIP_RETCODE SCIPincludeHeurMutation(SCIP *scip)
SCIP_RETCODE SCIPsetSeparating(SCIP *scip, SCIP_PARAMSETTING paramsetting, SCIP_Bool quiet)
Definition: scip_param.c:979
#define NULL
Definition: def.h:267
static SCIP_DECL_HEURFREE(heurFreeMutation)
public methods for SCIP parameter handling
public methods for node selector plugins
public methods for memory management
#define DEFAULT_NWAITINGNODES
Definition: heur_mutation.c:74
SCIP_Real SCIPvarGetLbGlobal(SCIP_VAR *var)
Definition: var.c:18079
SCIP_Longint SCIPheurGetNBestSolsFound(SCIP_HEUR *heur)
Definition: heur.c:1599
SCIP_RETCODE SCIPsetHeurExit(SCIP *scip, SCIP_HEUR *heur, SCIP_DECL_HEUREXIT((*heurexit)))
Definition: scip_heur.c:210
public solving methods
#define DEFAULT_MINNODES
Definition: heur_mutation.c:71
#define DEFAULT_RANDSEED
Definition: heur_mutation.c:83
SCIP_RETCODE SCIPgetVarsData(SCIP *scip, SCIP_VAR ***vars, int *nvars, int *nbinvars, int *nintvars, int *nimplvars, int *ncontvars)
Definition: scip_prob.c:1866
#define FALSE
Definition: def.h:94
#define HEUR_DISPCHAR
Definition: heur_mutation.c:60
SCIP_RETCODE SCIPhashmapCreate(SCIP_HASHMAP **hashmap, BMS_BLKMEM *blkmem, int mapsize)
Definition: misc.c:3074
SCIP_RETCODE SCIPcopyLimits(SCIP *sourcescip, SCIP *targetscip)
Definition: scip_copy.c:3296
#define TRUE
Definition: def.h:93
void SCIPrandomPermuteArray(SCIP_RANDNUMGEN *randnumgen, void **array, int begin, int end)
Definition: misc.c:10179
#define SCIPdebug(x)
Definition: pub_message.h:93
enum SCIP_Retcode SCIP_RETCODE
Definition: type_retcode.h:63
methods commonly used by primal heuristics
#define DEFAULT_MINFIXINGRATE
Definition: heur_mutation.c:72
SCIP_RETCODE SCIPsetPresolving(SCIP *scip, SCIP_PARAMSETTING paramsetting, SCIP_Bool quiet)
Definition: scip_param.c:953
SCIP_BRANCHRULE * SCIPfindBranchrule(SCIP *scip, const char *name)
Definition: scip_branch.c:297
static SCIP_RETCODE setupAndSolveSubscipMutation(SCIP *scip, SCIP *subscip, SCIP_HEUR *heur, SCIP_VAR **fixedvars, SCIP_Real *fixedvals, int nfixedvars, SCIP_Longint nsubnodes, SCIP_RESULT *result)
struct SCIP_HeurData SCIP_HEURDATA
Definition: type_heur.h:77
public methods for problem variables
#define SCIPfreeBlockMemory(scip, ptr)
Definition: scip_mem.h:108
SCIP_RETCODE SCIPincludeHeurBasic(SCIP *scip, SCIP_HEUR **heur, const char *name, const char *desc, char dispchar, int priority, int freq, int freqofs, int maxdepth, SCIP_HEURTIMING timingmask, SCIP_Bool usessubscip, SCIP_DECL_HEUREXEC((*heurexec)), SCIP_HEURDATA *heurdata)
Definition: scip_heur.c:117
SCIP_RETCODE SCIPtranslateSubSols(SCIP *scip, SCIP *subscip, SCIP_HEUR *heur, SCIP_VAR **subvars, SCIP_Bool *success, int *solindex)
Definition: scip_copy.c:1448
#define HEUR_NAME
Definition: heur_mutation.c:58
void * SCIPhashmapGetImage(SCIP_HASHMAP *hashmap, void *origin)
Definition: misc.c:3261
#define SCIPfreeBufferArray(scip, ptr)
Definition: scip_mem.h:136
SCIP_RETCODE SCIPcreate(SCIP **scip)
Definition: scip_general.c:307
void SCIPheurSetData(SCIP_HEUR *heur, SCIP_HEURDATA *heurdata)
Definition: heur.c:1374
#define SCIPallocBlockMemory(scip, ptr)
Definition: scip_mem.h:89
#define SCIPdebugMsg
Definition: scip_message.h:78
SCIP_RETCODE SCIPaddIntParam(SCIP *scip, const char *name, const char *desc, int *valueptr, SCIP_Bool isadvanced, int defaultvalue, int minvalue, int maxvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:83
SCIP_RETCODE SCIPprintStatistics(SCIP *scip, FILE *file)
public methods for numerical tolerances
public methods for querying solving statistics
SCIP_Real SCIPvarGetUbGlobal(SCIP_VAR *var)
Definition: var.c:18089
static SCIP_DECL_HEUREXEC(heurExecMutation)
SCIP_RETCODE SCIPsolve(SCIP *scip)
Definition: scip_solve.c:2498
const char * SCIPheurGetName(SCIP_HEUR *heur)
Definition: heur.c:1453
SCIP_Bool SCIPisParamFixed(SCIP *scip, const char *name)
Definition: scip_param.c:219
SCIP_RETCODE SCIPsetHeurFree(SCIP *scip, SCIP_HEUR *heur, SCIP_DECL_HEURFREE((*heurfree)))
Definition: scip_heur.c:178
SCIP_Bool SCIPisLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_RETCODE SCIPsetBoolParam(SCIP *scip, const char *name, SCIP_Bool value)
Definition: scip_param.c:429
#define DEFAULT_NODESQUOT
Definition: heur_mutation.c:73
BMS_BLKMEM * SCIPblkmem(SCIP *scip)
Definition: scip_mem.c:57
void SCIPhashmapFree(SCIP_HASHMAP **hashmap)
Definition: misc.c:3108
SCIP_RETCODE SCIPmergeVariableStatistics(SCIP *sourcescip, SCIP *targetscip, SCIP_VAR **sourcevars, SCIP_VAR **targetvars, int nvars)
Definition: scip_copy.c:1265
LNS heuristic that tries to randomly mutate the incumbent solution.
#define REALABS(x)
Definition: def.h:197
public methods for problem copies
public methods for primal CIP solutions
#define DEFAULT_MAXNODES
Definition: heur_mutation.c:69
#define SCIP_CALL(x)
Definition: def.h:380
SCIP_Real SCIPgetLowerbound(SCIP *scip)
SCIP_Longint SCIPheurGetNCalls(SCIP_HEUR *heur)
Definition: heur.c:1579
#define DEFAULT_MINIMPROVE
Definition: heur_mutation.c:70
public methods for primal heuristic plugins and divesets
public methods for constraint handler plugins and constraints
#define HEUR_MAXDEPTH
Definition: heur_mutation.c:64
SCIP_RETCODE SCIPcreateRandom(SCIP *scip, SCIP_RANDNUMGEN **randnumgen, unsigned int initialseed, SCIP_Bool useglobalseed)
#define SCIPallocBufferArray(scip, ptr, num)
Definition: scip_mem.h:124
public data structures and miscellaneous methods
#define SCIP_Bool
Definition: def.h:91
#define HEUR_USESSUBSCIP
Definition: heur_mutation.c:66
#define HEUR_PRIORITY
Definition: heur_mutation.c:61
SCIP_RETCODE SCIPsetObjlimit(SCIP *scip, SCIP_Real objlimit)
Definition: scip_prob.c:1422
#define MIN(x, y)
Definition: def.h:243
SCIP_RETCODE SCIPsetIntParam(SCIP *scip, const char *name, int value)
Definition: scip_param.c:487
int SCIPgetNSols(SCIP *scip)
Definition: scip_sol.c:2070
#define BMScopyMemoryArray(ptr, source, num)
Definition: memory.h:134
SCIP_Bool SCIPisInfinity(SCIP *scip, SCIP_Real val)
#define DEFAULT_USELPROWS
Definition: heur_mutation.c:75
SCIP_RETCODE SCIPsetCharParam(SCIP *scip, const char *name, char value)
Definition: scip_param.c:661
int SCIPgetNVars(SCIP *scip)
Definition: scip_prob.c:1992
#define HEUR_FREQOFS
Definition: heur_mutation.c:63
public methods for branching rule plugins and branching
general public methods
SCIP_SOL * SCIPgetBestSol(SCIP *scip)
Definition: scip_sol.c:2169
SCIP_Bool SCIPisGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
public methods for solutions
public methods for random numbers
public methods for message output
SCIP_RETCODE SCIPsetHeurInit(SCIP *scip, SCIP_HEUR *heur, SCIP_DECL_HEURINIT((*heurinit)))
Definition: scip_heur.c:194
#define HEUR_DESC
Definition: heur_mutation.c:59
SCIP_NODESEL * SCIPfindNodesel(SCIP *scip, const char *name)
Definition: scip_nodesel.c:234
SCIP_RETCODE SCIPcopyLargeNeighborhoodSearch(SCIP *sourcescip, SCIP *subscip, SCIP_HASHMAP *varmap, const char *suffix, SCIP_VAR **fixedvars, SCIP_Real *fixedvals, int nfixedvars, SCIP_Bool uselprows, SCIP_Bool copycuts, SCIP_Bool *success, SCIP_Bool *valid)
Definition: heuristics.c:951
SCIP_VAR ** SCIPgetVars(SCIP *scip)
Definition: scip_prob.c:1947
#define HEUR_TIMING
Definition: heur_mutation.c:65
#define SCIP_Real
Definition: def.h:173
SCIP_Bool SCIPisStopped(SCIP *scip)
Definition: scip_general.c:724
public methods for message handling
#define HEUR_FREQ
Definition: heur_mutation.c:62
static SCIP_DECL_HEURINIT(heurInitMutation)
#define SCIP_Longint
Definition: def.h:158
SCIP_RETCODE SCIPcheckCopyLimits(SCIP *sourcescip, SCIP_Bool *success)
Definition: scip_copy.c:3253
SCIP_Bool SCIPisLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
#define DEFAULT_BESTSOLLIMIT
Definition: heur_mutation.c:81
SCIP_RETCODE SCIPsetHeurCopy(SCIP *scip, SCIP_HEUR *heur, SCIP_DECL_HEURCOPY((*heurcopy)))
Definition: scip_heur.c:162
SCIP_Real SCIPsumepsilon(SCIP *scip)
SCIP_Real SCIPgetUpperbound(SCIP *scip)
public methods for primal heuristics
#define DEFAULT_USEUCT
Definition: heur_mutation.c:82
#define SCIP_CALL_ABORT(x)
Definition: def.h:359
SCIP_HEURDATA * SCIPheurGetData(SCIP_HEUR *heur)
Definition: heur.c:1364
SCIP_Longint SCIPgetNNodes(SCIP *scip)
public methods for global and local (sub)problems
SCIP_Real SCIPgetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var)
Definition: scip_sol.c:1217
SCIP_RETCODE SCIPaddRealParam(SCIP *scip, const char *name, const char *desc, SCIP_Real *valueptr, SCIP_Bool isadvanced, SCIP_Real defaultvalue, SCIP_Real minvalue, SCIP_Real maxvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:139
SCIP_RETCODE SCIPsetSubscipsOff(SCIP *scip, SCIP_Bool quiet)
Definition: scip_param.c:904
SCIP_RETCODE SCIPsetLongintParam(SCIP *scip, const char *name, SCIP_Longint value)
Definition: scip_param.c:545
SCIP_RETCODE SCIPaddBoolParam(SCIP *scip, const char *name, const char *desc, SCIP_Bool *valueptr, SCIP_Bool isadvanced, SCIP_Bool defaultvalue, SCIP_DECL_PARAMCHGD((*paramchgd)), SCIP_PARAMDATA *paramdata)
Definition: scip_param.c:57
#define DEFAULT_NODESOFS
Definition: heur_mutation.c:68
SCIP_RETCODE SCIPfree(SCIP **scip)
Definition: scip_general.c:339
SCIP_Longint SCIPgetSolNodenum(SCIP *scip, SCIP_SOL *sol)
Definition: scip_sol.c:1513
memory allocation routines
static SCIP_RETCODE determineVariableFixings(SCIP *scip, SCIP_VAR **fixedvars, SCIP_Real *fixedvals, int *nfixedvars, SCIP_Real minfixingrate, SCIP_RANDNUMGEN *randnumgen, SCIP_Bool *success)