Scippy

SCIP

Solving Constraint Integer Programs

heur_ascendprune.c
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1 /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
2 /* */
3 /* This file is part of the program and library */
4 /* SCIP --- Solving Constraint Integer Programs */
5 /* */
6 /* Copyright (C) 2002-2021 Konrad-Zuse-Zentrum */
7 /* fuer Informationstechnik Berlin */
8 /* */
9 /* SCIP is distributed under the terms of the ZIB Academic License. */
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15 
16 /**@file heur_ascendprune.c
17  * @brief reduction-based primal heuristic for Steiner problems
18  * @author Daniel Rehfeldt
19  *
20  * This file implements a reduction and dual-cost based heuristic for Steiner problems. See
21  * "SCIP-Jack - A solver for STP and variants with parallelization extensions" (2016) by
22  * Gamrath, Koch, Maher, Rehfeldt and Shinano
23  *
24  * A list of all interface methods can be found in heur_ascendprune.h
25  *
26  */
27 
28 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
29 
30 #include <assert.h>
31 #include <string.h>
32 #include <stdio.h>
33 #include "scip/scip.h"
34 #include "scip/scipdefplugins.h"
35 #include "scip/cons_linear.h"
36 #include "heur_ascendprune.h"
37 #include "heur_local.h"
38 #include "heur_prune.h"
39 #include "grph.h"
40 #include "heur_tm.h"
41 #include "cons_stp.h"
42 #include "scip/pub_misc.h"
43 #include "probdata_stp.h"
44 
45 #define HEUR_NAME "ascendprune"
46 #define HEUR_DESC "Dual-cost reduction heuristic for Steiner problems"
47 #define HEUR_DISPCHAR 'A'
48 #define HEUR_PRIORITY 2
49 #define HEUR_FREQ -1
50 #define HEUR_FREQOFS 0
51 #define HEUR_MAXDEPTH -1
52 #define HEUR_TIMING (SCIP_HEURTIMING_DURINGLPLOOP | SCIP_HEURTIMING_AFTERLPLOOP | SCIP_HEURTIMING_AFTERNODE)
53 #define HEUR_USESSUBSCIP FALSE /**< does the heuristic use a secondary SCIP instance? */
54 
55 #define DEFAULT_MAXFREQPRUNE FALSE /**< executions of the heuristic at maximum frequency? */
56 #define ASCENPRUNE_MINLPIMPROVE 0.05 /**< minimum percentual improvement of dual bound (wrt to gap) mandatory to execute heuristic */
57 
58 #ifdef WITH_UG
59 int getUgRank(void);
60 #endif
61 
62 /*
63  * Data structures
64  */
65 
66 /** primal heuristic data */
67 struct SCIP_HeurData
68 {
69  SCIP_Real lastdualbound; /**< dual bound after the previous run */
70  int bestsolindex; /**< best solution during the previous run */
71  int nfailures; /**< number of failures since last successful call */
72  SCIP_Bool maxfreq; /**< should the heuristic be called at maximum frequency? */
73 };
74 
75 
76 /*
77  * Local methods
78  */
79 
80 /* put your local methods here, and declare them static */
81 
82 
83 /*
84  * Callback methods of primal heuristic
85  */
86 
87 
88 /** copy method for primal heuristic plugins (called when SCIP copies plugins) */
89 static
90 SCIP_DECL_HEURCOPY(heurCopyAscendPrune)
91 { /*lint --e{715}*/
92  assert(scip != NULL);
93  assert(heur != NULL);
94  assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
95 
96  /* call inclusion method of primal heuristic */
98 
99  return SCIP_OKAY;
100 }
101 
102 /** destructor of primal heuristic to free user data (called when SCIP is exiting) */
103 static
104 SCIP_DECL_HEURFREE(heurFreeAscendPrune)
105 { /*lint --e{715}*/
106  SCIP_HEURDATA* heurdata;
107 
108  assert(heur != NULL);
109  assert(scip != NULL);
110 
111  /* get heuristic data */
112  heurdata = SCIPheurGetData(heur);
113  assert(heurdata != NULL);
114 
115  /* free heuristic data */
116  SCIPfreeMemory(scip, &heurdata);
117  SCIPheurSetData(heur, NULL);
118 
119  return SCIP_OKAY;
120 }
121 
122 
123 /** initialization method of primal heuristic (called after problem was transformed) */
124 
125 static
126 SCIP_DECL_HEURINIT(heurInitAscendPrune)
127 { /*lint --e{715}*/
128  SCIP_HEURDATA* heurdata;
129 
130  assert(heur != NULL);
131  assert(scip != NULL);
132 
133  /* get heuristic's data */
134  heurdata = SCIPheurGetData(heur);
135 
136  assert(heurdata != NULL);
137 
138  /* initialize data */
139  heurdata->nfailures = 0;
140  heurdata->bestsolindex = -1;
141  heurdata->lastdualbound = 0.0;
142 
143  return SCIP_OKAY;
144 }
145 
146 /** execution method of primal heuristic */
147 static
148 SCIP_DECL_HEUREXEC(heurExecAscendPrune)
149 { /*lint --e{715}*/
150  SCIP_HEURDATA* heurdata;
151  SCIP_PROBDATA* probdata;
152  SCIP_VAR** vars;
153  SCIP_SOL* bestsol; /* best known solution */
154  GRAPH* graph;
155  SCIP_Real dualbound;
156  SCIP_Real gap;
157  SCIP_Real* redcosts;
158  SCIP_Bool success;
159  int e;
160  int nnodes;
161  int nedges;
162  int* edgearrint;
163  int* nodearrint;
164  STP_Bool* nodearrchar;
165 
166  assert(heur != NULL);
167  assert(scip != NULL);
168  assert(result != NULL);
169  assert(strcmp(SCIPheurGetName(heur), HEUR_NAME) == 0);
170 
171  /* get heuristic data */
172  heurdata = SCIPheurGetData(heur);
173  assert(heurdata != NULL);
174 
175  /* get problem data */
176  probdata = SCIPgetProbData(scip);
177  assert(probdata != NULL);
178 
179  /* get graph */
180  graph = SCIPprobdataGetGraph(probdata);
181  assert(graph != NULL);
182 
183  vars = SCIPprobdataGetVars(scip);
184  assert(vars != NULL);
185 
186  *result = SCIP_DIDNOTRUN;
187 
188  /* todo: delete this file and move to slack-prune */
189 
190  nedges = graph->edges;
191  nnodes = graph->knots;
192  success = FALSE;
193 
194  /* get best current solution */
195  bestsol = SCIPgetBestSol(scip);
196 
197  /* no solution available? */
198  if( bestsol == NULL )
199  return SCIP_OKAY;
200 
201  /* get dual bound */
202  dualbound = SCIPgetDualbound(scip);
203 
204  /* no new best solution available? */
205  if( heurdata->bestsolindex == SCIPsolGetIndex(SCIPgetBestSol(scip)) && !(heurdata->maxfreq) )
206  {
207  /* current optimality gap */
208  gap = SCIPgetSolOrigObj(scip, bestsol) - dualbound;
209 
210  if( SCIPisLT(scip, dualbound - heurdata->lastdualbound, gap * ASCENPRUNE_MINLPIMPROVE ) )
211  return SCIP_OKAY;
212  }
213 
214  heurdata->lastdualbound = dualbound;
215 
216  /* allocate memory for ascent and prune */
217  SCIP_CALL( SCIPallocBufferArray(scip, &redcosts, nedges) );
218  SCIP_CALL( SCIPallocBufferArray(scip, &edgearrint, nedges) );
219  SCIP_CALL( SCIPallocBufferArray(scip, &nodearrint, nnodes ) );
220  SCIP_CALL( SCIPallocBufferArray(scip, &nodearrchar, nnodes) );
221 
222  for( e = 0; e < nedges; e++ )
223  {
224  assert(SCIPvarIsBinary(vars[e]));
225 
226  /* variable is already fixed, we must not trust the reduced cost */
227  if( SCIPvarGetLbLocal(vars[e]) + 0.5 > SCIPvarGetUbLocal(vars[e]) )
228  {
229  if( SCIPvarGetLbLocal(vars[e]) > 0.5 )
230  redcosts[e] = 0.0;
231  else
232  {
233  assert(SCIPvarGetUbLocal(vars[e]) < 0.5);
234  redcosts[e] = FARAWAY;
235  }
236  }
237  else
238  {
239  if( SCIPisFeasZero(scip, SCIPgetSolVal(scip, NULL, vars[e])) )
240  {
241  assert(!SCIPisDualfeasNegative(scip, SCIPgetVarRedcost(scip, vars[e])));
242  redcosts[e] = SCIPgetVarRedcost(scip, vars[e]);
243  }
244  else
245  {
246  assert(!SCIPisDualfeasPositive(scip, SCIPgetVarRedcost(scip, vars[e])));
247  assert(SCIPisFeasEQ(scip, SCIPgetSolVal(scip, NULL, vars[e]), 1.0) || SCIPisDualfeasZero(scip, SCIPgetVarRedcost(scip, vars[e])));
248  redcosts[e] = 0.0;
249  }
250  }
251 
252  if( SCIPisLT(scip, redcosts[e], 0.0) )
253  redcosts[e] = 0.0;
254 
255  assert(SCIPisGE(scip, redcosts[e], 0.0));
256  assert(!SCIPisEQ(scip, redcosts[e], SCIP_INVALID));
257  }
258 
259  /* perform ascent and prune */
260  SCIP_CALL( SCIPStpHeurAscendPruneRun(scip, heur, graph, redcosts, edgearrint, nodearrint, graph->source, nodearrchar, &success, TRUE) );
261 
262  if( success )
263  {
264  heurdata->nfailures = 0;
265  *result = SCIP_FOUNDSOL;
266  }
267  else
268  {
269  heurdata->nfailures++;
270  }
271 
272  heurdata->bestsolindex = SCIPsolGetIndex(SCIPgetBestSol(scip));
273 
274  /* free memory */
275  SCIPfreeBufferArray(scip, &nodearrchar);
276  SCIPfreeBufferArray(scip, &nodearrint);
277  SCIPfreeBufferArray(scip, &edgearrint);
278  SCIPfreeBufferArray(scip, &redcosts);
279 
280  return SCIP_OKAY;
281 }
282 
283 
284 /*
285  * primal heuristic specific interface methods
286  */
287 
288 
289 /** ascent and prune */
291  SCIP* scip, /**< SCIP data structure */
292  SCIP_HEUR* heur, /**< heuristic data structure or NULL */
293  const GRAPH* g, /**< the graph */
294  const SCIP_Real* redcosts, /**< the reduced costs */
295  int* edgearrint, /**< int edges array to store solution */
296  int* nodearrint, /**< int vertices array for internal computations */
297  int root, /**< the root (used for dual ascent) */
298  STP_Bool* nodearrchar, /**< STP_Bool vertices array for internal computations */
299  SCIP_Bool* solfound, /**< has a solution been found? */
300  SCIP_Bool addsol /**< should the solution be added to SCIP by this method? */
301  )
302 {
303  GRAPH* newgraph;
304  SCIP_Real* nval;
305  int* const mark = g->mark;
306  int* const newedges = edgearrint;
307  int* const nodechild = nodearrint;
308  int* edgeancestor;
309  const int nnodes = g->knots;
310  const int nedges = g->edges;
311  const int probtype = g->stp_type;
312  int nnewnodes = 0;
313  int nnewedges = 0;
314  const SCIP_Bool pcmw = (probtype == STP_PCSPG || probtype == STP_MWCSP || probtype == STP_RPCSPG || probtype == STP_RMWCSP);
315  SCIP_Bool success;
316 
317  assert(g != NULL);
318  assert(scip != NULL);
319  assert(redcosts != NULL);
320  assert(edgearrint != NULL);
321  assert(nodearrint != NULL);
322  assert(nodearrchar != NULL);
323 
324  if( root < 0 )
325  root = g->source;
326 
327  assert(Is_term(g->term[root]));
328  assert(graph_valid(g));
329 
330  if( addsol )
331  {
332  const int nvars = SCIPprobdataGetNVars(scip);
333  SCIP_CALL( SCIPallocBufferArray(scip, &nval, nvars) );
334  }
335  else
336  {
337  nval = NULL;
338  }
339 
340  /* DFS to identify 0-redcost subgraph */
341  {
342  int* const queue = nodearrint;
343  STP_Bool* const scanned = nodearrchar;
344  int qsize;
345 
346  /*
347  * construct new graph corresponding to zero cost paths from the root to all terminals
348  */
349 
350  BMSclearMemoryArray(mark, nnodes);
351  BMSclearMemoryArray(scanned, nnodes);
352 
353  qsize = 0;
354  mark[root] = TRUE;
355  queue[qsize++] = root;
356  nnewnodes++;
357 
358  /* DFS */
359  while( qsize )
360  {
361  const int k = queue[--qsize];
362  scanned[k] = TRUE;
363 
364  /* traverse outgoing arcs */
365  for( int a = g->outbeg[k]; a != EAT_LAST; a = g->oeat[a] )
366  {
367  const int head = g->head[a];
368 
369  if( SCIPisZero(scip, redcosts[a]) )
370  {
371  if( pcmw && k == root && Is_term(g->term[head]) )
372  continue;
373 
374  /* vertex not labeled yet? */
375  if( !mark[head] )
376  {
377  mark[head] = TRUE;
378  nnewnodes++;
379  queue[qsize++] = head;
380  }
381 
382  if( (!scanned[head] || !SCIPisZero(scip, redcosts[flipedge(a)])) && k != root )
383  {
384  assert(g->tail[a] != root);
385  assert(g->head[a] != root);
386 
387  newedges[nnewedges++] = a;
388  }
389  }
390  }
391  }
392 
393 #ifndef NDEBUG
394  for( int k = 0; k < nnewedges && pcmw; k++ )
395  {
396  const int e = newedges[k];
397  assert(!(g->tail[e] == root && Is_pterm(g->term[g->head[e]])));
398  assert(!(g->head[e] == root && Is_pterm(g->term[g->tail[e]])));
399  }
400 #endif
401 
402  for( int a = g->outbeg[root]; a != EAT_LAST; a = g->oeat[a] )
403  {
404  const int head = g->head[a];
405  if( mark[head] )
406  newedges[nnewedges++] = a;
407  }
408  }
409 
410  SCIP_CALL( SCIPallocBufferArray(scip, &edgeancestor, 2 * nnewedges) );
411 
412  /* initialize new graph */
413  SCIP_CALL( graph_init(scip, &newgraph, nnewnodes, 2 * nnewedges, 1) );
414 
415  if( probtype == STP_RSMT || probtype == STP_OARSMT || probtype == STP_GSTP )
416  newgraph->stp_type = STP_SPG;
417  else
418  newgraph->stp_type = probtype;
419 
420  if( pcmw )
421  SCIP_CALL( graph_pc_init(scip, newgraph, nnewnodes, nnewnodes) );
422 
423  for( int k = 0; k < nnodes; k++ )
424  {
425  if( mark[k] )
426  {
427  if( pcmw )
428  {
429  if( (!Is_term(g->term[k])) )
430  newgraph->prize[newgraph->knots] = g->prize[k];
431  else
432  newgraph->prize[newgraph->knots] = 0.0;
433  }
434 
435  nodechild[k] = newgraph->knots;
436  graph_knot_add(newgraph, g->term[k]);
437  }
438  }
439 
440  if( pcmw )
441  {
442  newgraph->norgmodelknots = nnewnodes;
443  newgraph->extended = TRUE;
444  }
445 
446  assert(nnewnodes == newgraph->knots);
447 
448  /* set root of new graph */
449  newgraph->source = nodechild[root];
450  assert(newgraph->source >= 0);
451 
452  if( g->stp_type == STP_RPCSPG || g->stp_type == STP_RMWCSP )
453  newgraph->prize[newgraph->source] = FARAWAY;
454 
455  /* add edges to new graph */
456  for( int a = 0; a < nnewedges; a++ )
457  {
458  int i;
459  const int e = newedges[a];
460  const int tail = nodechild[g->tail[e]];
461  const int head = nodechild[g->head[e]];
462 
463  assert(tail >= 0);
464  assert(head >= 0);
465 
466  for( i = newgraph->outbeg[tail]; i != EAT_LAST; i = newgraph->oeat[i] )
467  if( newgraph->head[i] == head )
468  break;
469 
470  if( i == EAT_LAST )
471  {
472  edgeancestor[newgraph->edges] = e;
473  edgeancestor[newgraph->edges + 1] = flipedge(e);
474 
475  if( pcmw )
476  graph_pc_updateTerm2edge(newgraph, g, tail, head, g->tail[e], g->head[e]);
477 
478  graph_edge_add(scip, newgraph, tail, head, g->cost[e], g->cost[flipedge(e)]);
479  }
480  }
481 
482  nnewedges = newgraph->edges;
483  newgraph->norgmodeledges = nnewedges;
484 
485  assert(!pcmw || -1 == newgraph->term2edge[newgraph->source]);
486 
487  /* initialize ancestors of new graph edges */
488  SCIP_CALL( graph_init_history(scip, newgraph) );
489 
490  /* initialize shortest path algorithm */
491  SCIP_CALL( graph_path_init(scip, newgraph) );
492 
493  SCIP_CALL( level0(scip, newgraph) );
494 
495 #ifdef DEBUG_ASCENDPRUNE
496  for( int k = 0; k < nnodes && !pcmw; k++ )
497  {
498  if( Is_term(g->term[k]) )
499  {
500  const int i = nodechild[k];
501  if( i < 0 )
502  {
503  printf("k %d root %d \n", k, root);
504  printf("FAIL in AP \n\n\n");
505  return SCIP_ERROR;
506  }
507 
508  if( newgraph->grad[i] == 0 && newgraph->knots > 1 )
509  {
510  printf("FAIL GRAD \n\n\n");
511  return SCIP_ERROR;
512 
513  }
514  }
515  }
516 #endif
517  assert(graph_valid(newgraph));
518 
519  /* get solution on new graph by PRUNE heuristic */
520  SCIP_CALL( SCIPStpHeurPruneRun(scip, NULL, newgraph, newedges, &success, FALSE, TRUE) );
521 
522 #ifdef DEBUG_ASCENDPRUNE
523  for( int k = 0; k < newgraph->knots; ++k )
524  {
525  if( Is_term(newgraph->term[k]) && newgraph->grad[k] == 0 && k != newgraph->source )
526  {
527  printf("after i %d r %d \n", k, root);
528  return SCIP_ERROR;
529  }
530  }
531 
532  if( !graph_sol_valid(scip, newgraph, newedges) )
533  {
534  printf("not valid %d \n", 0);
535  return SCIP_ERROR;
536  }
537 #endif
538  if( !success )
539  {
540  SCIPdebugMessage("failed to build tree in ascend-prune (by prune) \n");
541  goto TERMINATE;
542  }
543 
544  assert(success && graph_sol_valid(scip, newgraph, newedges));
545 
546  SCIPdebugMessage("obj after prune %f \n", graph_sol_getObj(newgraph->cost, newedges, 0.0, newgraph->edges));
547 
548  SCIP_CALL( SCIPStpHeurLocalRun(scip, newgraph, newgraph->cost, newedges) );
549 
550  SCIPdebugMessage("obj after local %f \n", graph_sol_getObj(newgraph->cost, newedges, 0.0, newgraph->edges));
551 
552  assert(graph_sol_valid(scip, newgraph, newedges));
553  graph_path_exit(scip, newgraph);
554 
555 
556  /*
557  * prune solution (in the original graph)
558  */
559 
560  BMSclearMemoryArray(nodearrchar, nnodes);
561 
562  for( int e = 0; e < nnewedges; e++ )
563  if( newedges[e] == CONNECT )
564  {
565  const int eorg = edgeancestor[e];
566  nodearrchar[g->tail[eorg]] = TRUE;
567  nodearrchar[g->head[eorg]] = TRUE;
568  }
569 
570  for( int e = 0; e < nedges; e++ )
571  newedges[e] = UNKNOWN;
572 
573  if( pcmw )
574  SCIP_CALL( SCIPStpHeurTMPrunePc(scip, g, g->cost, newedges, nodearrchar) );
575  else
576  SCIP_CALL( SCIPStpHeurTMPrune(scip, g, g->cost, 0, newedges, nodearrchar) );
577 
578  assert(graph_sol_valid(scip, g, newedges));
579 
580  if( addsol )
581  {
582  assert(nval != NULL);
583  for( int e = 0; e < nedges; e++ )
584  {
585  if( newedges[e] == CONNECT )
586  nval[e] = 1.0;
587  else
588  nval[e] = 0.0;
589  }
590  }
591 
592  success = graph_sol_valid(scip, g, newedges);
593 
594  if( success && addsol )
595  {
596  /* add solution */
597  SCIP_SOL* sol = NULL;
598  SCIP_CALL( SCIPprobdataAddNewSol(scip, nval, sol, heur, &success) );
599  SCIPdebugMessage("Ascend-and-prune added solution \n");
600  }
601 
602  *solfound = success;
603 
604  TERMINATE:
605 
606  for( int k = 0; k < nnodes; k++ )
607  mark[k] = (g->grad[k] > 0);
608 
609  /* free memory */
610  graph_free(scip, &newgraph, TRUE);
611  SCIPfreeBufferArray(scip, &edgeancestor);
612  SCIPfreeBufferArrayNull(scip, &nval);
613 
614  return SCIP_OKAY;
615 }
616 
617 
618 /** creates the prune primal heuristic and includes it in SCIP */
620  SCIP* scip /**< SCIP data structure */
621  )
622 {
623  SCIP_HEURDATA* heurdata;
624  SCIP_HEUR* heur;
625 
626  /* create prune primal heuristic data */
627  SCIP_CALL( SCIPallocMemory(scip, &heurdata) );
628 
629  /* include primal heuristic */
630  SCIP_CALL( SCIPincludeHeurBasic(scip, &heur,
632  HEUR_MAXDEPTH, HEUR_TIMING, HEUR_USESSUBSCIP, heurExecAscendPrune, heurdata) );
633 
634  assert(heur != NULL);
635 
636  /* set non fundamental callbacks via setter functions */
637  SCIP_CALL( SCIPsetHeurCopy(scip, heur, heurCopyAscendPrune) );
638  SCIP_CALL( SCIPsetHeurFree(scip, heur, heurFreeAscendPrune) );
639  SCIP_CALL( SCIPsetHeurInit(scip, heur, heurInitAscendPrune) );
640 
641  /* add ascend and prune primal heuristic parameters */
642  SCIP_CALL( SCIPaddBoolParam(scip, "heuristics/"HEUR_NAME"/maxfreq",
643  "should the heuristic be executed at maximum frequeny?",
644  &heurdata->maxfreq, FALSE, DEFAULT_MAXFREQPRUNE, NULL, NULL) );
645 
646  return SCIP_OKAY;
647 }
SCIP_RETCODE graph_path_init(SCIP *, GRAPH *)
Definition: grphpath.c:444
SCIP_Bool SCIPisEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_RETCODE SCIPStpHeurPruneRun(SCIP *scip, SCIP_VAR **vars, GRAPH *g, int *soledge, SCIP_Bool *success, const SCIP_Bool withinitialsol, const SCIP_Bool reducegraph)
Definition: heur_prune.c:597
SCIP_RETCODE graph_pc_init(SCIP *, GRAPH *, int, int)
Definition: grphbase.c:766
const char * SCIPheurGetName(SCIP_HEUR *heur)
Definition: heur.c:1429
int *RESTRICT head
Definition: grph.h:96
Definition: grph.h:57
int source
Definition: grph.h:67
SCIP_Bool SCIPisGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
#define STP_GSTP
Definition: grph.h:49
SCIP_HEURDATA * SCIPheurGetData(SCIP_HEUR *heur)
Definition: heur.c:1340
Constraint handler for Steiner problems.
SCIP_Real SCIPgetVarRedcost(SCIP *scip, SCIP_VAR *var)
Definition: scip_var.c:1861
SCIP_Bool graph_valid(const GRAPH *)
Definition: grphbase.c:4328
SCIP_VAR ** SCIPprobdataGetVars(SCIP *scip)
SCIP_RETCODE graph_init_history(SCIP *, GRAPH *)
Definition: grphbase.c:3573
SCIP_Real SCIPgetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var)
Definition: scip_sol.c:1353
int norgmodeledges
Definition: grph.h:88
#define EAT_LAST
Definition: grph.h:31
SCIP_EXPORT SCIP_Bool SCIPvarIsBinary(SCIP_VAR *var)
Definition: var.c:17197
#define HEUR_TIMING
reduction and dual-cost based primal heuristic for Steiner problems
#define FALSE
Definition: def.h:73
#define HEUR_DESC
#define STP_RMWCSP
Definition: grph.h:50
void graph_free(SCIP *, GRAPH **, SCIP_Bool)
Definition: grphbase.c:3678
Problem data for stp problem.
#define TRUE
Definition: def.h:72
enum SCIP_Retcode SCIP_RETCODE
Definition: type_retcode.h:54
void graph_path_exit(SCIP *, GRAPH *)
Definition: grphpath.c:466
SCIP_PROBDATA * SCIPgetProbData(SCIP *scip)
Definition: scip_prob.c:962
int SCIPprobdataGetNVars(SCIP *scip)
struct SCIP_HeurData SCIP_HEURDATA
Definition: type_heur.h:67
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:48
#define STP_PCSPG
Definition: grph.h:40
#define SCIPdebugMessage
Definition: pub_message.h:87
#define SCIPfreeBufferArray(scip, ptr)
Definition: scip_mem.h:123
SCIP_RETCODE SCIPsetHeurInit(SCIP *scip, SCIP_HEUR *heur, SCIP_DECL_HEURINIT((*heurinit)))
Definition: scip_heur.c:185
void graph_pc_updateTerm2edge(GRAPH *, const GRAPH *, int, int, int, int)
Definition: grphbase.c:928
GRAPH * SCIPprobdataGetGraph(SCIP_PROBDATA *probdata)
SCIP_RETCODE SCIPStpHeurAscendPruneRun(SCIP *scip, SCIP_HEUR *heur, const GRAPH *g, const SCIP_Real *redcosts, int *edgearrint, int *nodearrint, int root, STP_Bool *nodearrchar, SCIP_Bool *solfound, SCIP_Bool addsol)
SCIP_Bool SCIPisDualfeasNegative(SCIP *scip, SCIP_Real val)
int *RESTRICT mark
Definition: grph.h:70
SCIP_Bool SCIPisDualfeasZero(SCIP *scip, SCIP_Real val)
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:108
int *RESTRICT oeat
Definition: grph.h:103
#define CONNECT
Definition: grph.h:154
SCIP_Bool extended
Definition: grph.h:128
int stp_type
Definition: grph.h:127
#define HEUR_DISPCHAR
SCIP_RETCODE level0(SCIP *, GRAPH *)
Definition: reduce.c:153
#define Is_pterm(a)
Definition: grph.h:169
unsigned char STP_Bool
Definition: grph.h:52
SCIP_Bool SCIPisFeasEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
SCIP_RETCODE SCIPprobdataAddNewSol(SCIP *scip, SCIP_Real *nval, SCIP_SOL *sol, SCIP_HEUR *heur, SCIP_Bool *success)
#define SCIPfreeBufferArrayNull(scip, ptr)
Definition: scip_mem.h:124
SCIP_Real * prize
Definition: grph.h:82
int *RESTRICT grad
Definition: grph.h:73
SCIP_Bool SCIPisZero(SCIP *scip, SCIP_Real val)
SCIP_Bool graph_sol_valid(SCIP *, const GRAPH *, const int *)
Definition: grphbase.c:3070
void SCIPheurSetData(SCIP_HEUR *heur, SCIP_HEURDATA *heurdata)
Definition: heur.c:1350
#define NULL
Definition: lpi_spx1.cpp:155
#define ASCENPRUNE_MINLPIMPROVE
int knots
Definition: grph.h:62
#define SCIP_CALL(x)
Definition: def.h:370
int * term2edge
Definition: grph.h:80
Improvement heuristic for Steiner problems.
reduction-based primal heuristic for Steiner problems
#define FARAWAY
Definition: grph.h:156
SCIP_Bool SCIPisFeasZero(SCIP *scip, SCIP_Real val)
#define HEUR_PRIORITY
#define STP_SPG
Definition: grph.h:38
#define SCIPallocBufferArray(scip, ptr, num)
Definition: scip_mem.h:111
public data structures and miscellaneous methods
#define HEUR_NAME
#define SCIP_Bool
Definition: def.h:70
static SCIP_DECL_HEUREXEC(heurExecAscendPrune)
#define STP_MWCSP
Definition: grph.h:47
int *RESTRICT tail
Definition: grph.h:95
#define HEUR_MAXDEPTH
SCIP_Bool SCIPisDualfeasPositive(SCIP *scip, SCIP_Real val)
static SCIP_DECL_HEURINIT(heurInitAscendPrune)
SCIP_RETCODE SCIPStpIncludeHeurAscendPrune(SCIP *scip)
SCIP_EXPORT int SCIPsolGetIndex(SCIP_SOL *sol)
Definition: sol.c:2635
int *RESTRICT term
Definition: grph.h:68
SCIP_Real graph_sol_getObj(const SCIP_Real *, const int *, SCIP_Real, int)
Definition: grphbase.c:3200
static SCIP_DECL_HEURFREE(heurFreeAscendPrune)
Constraint handler for linear constraints in their most general form, .
SCIP_EXPORT SCIP_Real SCIPvarGetLbLocal(SCIP_VAR *var)
Definition: var.c:17723
includes various files containing graph methods used for Steiner tree problems
#define SCIPfreeMemory(scip, ptr)
Definition: scip_mem.h:67
SCIP_EXPORT SCIP_Real SCIPvarGetUbLocal(SCIP_VAR *var)
Definition: var.c:17733
#define HEUR_FREQ
#define Is_term(a)
Definition: grph.h:168
struct SCIP_ProbData SCIP_PROBDATA
Definition: type_prob.h:44
static SCIP_DECL_HEURCOPY(heurCopyAscendPrune)
SCIP_Real * cost
Definition: grph.h:94
SCIP_RETCODE SCIPsetHeurCopy(SCIP *scip, SCIP_HEUR *heur, SCIP_DECL_HEURCOPY((*heurcopy)))
Definition: scip_heur.c:153
SCIP_VAR * a
Definition: circlepacking.c:57
#define SCIP_Real
Definition: def.h:163
SCIP_Bool SCIPisLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
int *RESTRICT outbeg
Definition: grph.h:76
SCIP_RETCODE SCIPStpHeurTMPrunePc(SCIP *scip, const GRAPH *g, const SCIP_Real *cost, int *result, STP_Bool *connected)
Definition: heur_tm.c:167
#define SCIP_INVALID
Definition: def.h:183
SCIP_RETCODE SCIPStpHeurLocalRun(SCIP *scip, GRAPH *graph, const SCIP_Real *cost, int *best_result)
Definition: heur_local.c:208
shortest paths based primal heuristics for Steiner problems
int edges
Definition: grph.h:92
#define flipedge(edge)
Definition: grph.h:150
void graph_knot_add(GRAPH *, int)
Definition: grphbase.c:2200
SCIP_RETCODE SCIPsetHeurFree(SCIP *scip, SCIP_HEUR *heur, SCIP_DECL_HEURFREE((*heurfree)))
Definition: scip_heur.c:169
#define DEFAULT_MAXFREQPRUNE
#define SCIPallocMemory(scip, ptr)
Definition: scip_mem.h:51
#define HEUR_USESSUBSCIP
#define UNKNOWN
Definition: sepa_mcf.c:4095
#define STP_RSMT
Definition: grph.h:45
#define nnodes
Definition: gastrans.c:65
#define STP_OARSMT
Definition: grph.h:46
#define BMSclearMemoryArray(ptr, num)
Definition: memory.h:122
SCIP_Real SCIPgetDualbound(SCIP *scip)
#define HEUR_FREQOFS
SCIP_RETCODE SCIPStpHeurTMPrune(SCIP *scip, const GRAPH *g, const SCIP_Real *cost, int layer, int *result, STP_Bool *connected)
Definition: heur_tm.c:555
void graph_edge_add(SCIP *, GRAPH *, int, int, double, double)
default SCIP plugins
#define STP_RPCSPG
Definition: grph.h:41
SCIP_SOL * SCIPgetBestSol(SCIP *scip)
Definition: scip_sol.c:2305
SCIP callable library.
SCIP_RETCODE graph_init(SCIP *, GRAPH **, int, int, int)
Definition: grphbase.c:3495
int norgmodelknots
Definition: grph.h:60
SCIP_Real SCIPgetSolOrigObj(SCIP *scip, SCIP_SOL *sol)
Definition: scip_sol.c:1436