Scippy

SCIP

Solving Constraint Integer Programs

sepa_convexproj.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) 2002-2020 Konrad-Zuse-Zentrum */
7 /* fuer Informationstechnik Berlin */
8 /* */
9 /* SCIP is distributed under the terms of the ZIB Academic License. */
10 /* */
11 /* You should have received a copy of the ZIB Academic License */
12 /* along with SCIP; see the file COPYING. If not visit scipopt.org. */
13 /* */
14 /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
15 
16 /**@file sepa_convexproj.c
17  * @ingroup DEFPLUGINS_SEPA
18  * @brief convexproj separator
19  * @author Felipe Serrano
20  *
21  * @todo should separator only be run when SCIPallColsInLP is true?
22  * @todo check if it makes sense to implement the copy callback
23  * @todo add SCIPisStopped(scip) to the condition of time consuming loops
24  */
25 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
26 
27 #include <assert.h>
28 #include <string.h>
29 
30 #include "blockmemshell/memory.h"
31 #include "nlpi/exprinterpret.h"
32 #include "nlpi/nlpi.h"
33 #include "nlpi/pub_expr.h"
34 #include "scip/pub_message.h"
35 #include "scip/pub_misc.h"
36 #include "scip/pub_nlp.h"
37 #include "scip/pub_sepa.h"
38 #include "scip/pub_var.h"
39 #include "scip/scip_cut.h"
40 #include "scip/scip_general.h"
41 #include "scip/scip_lp.h"
42 #include "scip/scip_mem.h"
43 #include "scip/scip_message.h"
44 #include "scip/scip_nlp.h"
45 #include "scip/scip_nonlinear.h"
46 #include "scip/scip_numerics.h"
47 #include "scip/scip_param.h"
48 #include "scip/scip_prob.h"
49 #include "scip/scip_sepa.h"
50 #include "scip/scip_sol.h"
51 #include "scip/scip_solvingstats.h"
52 #include "scip/scip_timing.h"
53 #include "scip/scip_tree.h"
54 #include "scip/sepa_convexproj.h"
55 #include <string.h>
56 
57 
58 #define SEPA_NAME "convexproj"
59 #define SEPA_DESC "separate at projection of point onto convex region"
60 #define SEPA_PRIORITY 0
61 #define SEPA_FREQ -1
62 #define SEPA_MAXBOUNDDIST 1.0
63 #define SEPA_USESSUBSCIP FALSE /**< does the separator use a secondary SCIP instance? */
64 #define SEPA_DELAY TRUE /**< should separation method be delayed, if other separators found cuts? */
65 
66 #define DEFAULT_MAXDEPTH -1 /* maximum depth at which the separator is applied; -1 means no limit */
67 #define DEFAULT_NLPTIMELIMIT 0.0 /**< default time limit of NLP solver; 0.0 for no limit */
68 #define DEFAULT_NLPITERLIM 250 /**< default NLP iteration limit */
69 
70 #define VIOLATIONFAC 100 /* points regarded violated if max violation > VIOLATIONFAC*SCIPfeastol */
71 
72 #define NLPVERBOSITY 0 /**< NLP solver verbosity */
73 
74 /*
75  * Data structures
76  */
77 
78 /** side that makes an nlrow convex */
80 {
81  LHS = 0, /**< left hand side */
82  RHS = 1 /**< right hand side */
83 };
84 typedef enum ConvexSide CONVEXSIDE;
85 
86 /** separator data
87  * it keeps the nlpi which represents the projection problem (see sepa_convexproj.h); it also keeps the convex nlrows
88  * and the side which actually makes them convex; when separating, we use the nlpi to compute the projection and then
89  * the convex nlrows to compute the actual gradient cuts */
90 struct SCIP_SepaData
91 {
92  SCIP_NLPI* nlpi; /**< nlpi used to create the nlpi problem */
93  SCIP_NLPIPROBLEM* nlpiprob; /**< nlpi problem representing the convex NLP relaxation */
94  SCIP_VAR** nlpivars; /**< array containing all variables of the nlpi */
95  SCIP_HASHMAP* var2nlpiidx; /**< mapping between variables and nlpi indices */
96  int nlpinvars; /**< total number of nlpi variables */
97 
98  SCIP_Bool skipsepa; /**< should separator be skipped? */
99 
100  SCIP_NLROW** nlrows; /**< convex nlrows */
101  CONVEXSIDE* convexsides; /**< which sides make the nlrows convex */
102  SCIP_Real* constraintviolation;/**< array storing the violation of constraint by current solution; 0.0 if it is not violated */
103  int nnlrows; /**< total number of nlrows */
104  int nlrowssize; /**< memory allocated for nlrows, convexsides and nlrowsidx */
105 
106  SCIP_EXPRINT* exprinterpreter; /**< expression interpreter to compute gradients */
107 
108  /* parameter */
109  SCIP_Real nlptimelimit; /**< time limit of NLP solver; 0.0 for no limit */
110  int nlpiterlimit; /**< iteration limit of NLP solver; 0 for no limit */
111  int maxdepth; /**< maximal depth at which the separator is applied */
112 
113  int ncuts; /**< number of cuts generated */
114 };
115 
116 
117 /*
118  * Local methods
119  */
120 
121 /** clears the sepadata data */
122 static
124  SCIP* scip, /**< SCIP data structure */
125  SCIP_SEPADATA* sepadata /**< separator data */
126  )
127 {
128  assert(sepadata != NULL);
129 
130  /* nlrowssize gets allocated first and then its decided whether to create the nlpiprob */
131  if( sepadata->nlrowssize > 0 )
132  {
133  SCIPfreeBlockMemoryArray(scip, &sepadata->constraintviolation, sepadata->nlrowssize);
134  SCIPfreeBlockMemoryArray(scip, &sepadata->convexsides, sepadata->nlrowssize);
135  SCIPfreeBlockMemoryArray(scip, &sepadata->nlrows, sepadata->nlrowssize);
136  sepadata->nlrowssize = 0;
137  }
138 
139  if( sepadata->nlpiprob != NULL )
140  {
141  assert(sepadata->nlpi != NULL);
142 
143  SCIPfreeBlockMemoryArray(scip, &sepadata->nlpivars, sepadata->nlpinvars);
144 
145  SCIPhashmapFree(&sepadata->var2nlpiidx);
146  SCIP_CALL( SCIPnlpiFreeProblem(sepadata->nlpi, &sepadata->nlpiprob) );
147  SCIP_CALL( SCIPexprintFree(&sepadata->exprinterpreter) );
148 
149  sepadata->nlpinvars = 0;
150  sepadata->nnlrows = 0;
151  }
152  assert(sepadata->nlpinvars == 0);
153  assert(sepadata->nnlrows == 0);
154  assert(sepadata->nlrowssize == 0);
155 
156  sepadata->skipsepa = FALSE;
157 
158  return SCIP_OKAY;
159 }
160 
161 /** computes gradient of exprtree at projection */
162 static
164  SCIP* scip, /**< SCIP data structure */
165  SCIP_EXPRINT* exprint, /**< expressions interpreter */
166  SCIP_SOL* projection, /**< point where we compute gradient */
167  SCIP_EXPRTREE* exprtree, /**< exprtree for which we compute the gradient */
168  SCIP_Real* grad /**< buffer to store the gradient */
169  )
170 {
171  SCIP_Real* x;
172  SCIP_Real val;
173  int nvars;
174  int i;
175 
176  assert(scip != NULL);
177  assert(exprint != NULL);
178  assert(projection != NULL);
179  assert(exprtree != NULL);
180  assert(grad != NULL);
181 
182  nvars = SCIPexprtreeGetNVars(exprtree);
183  assert(nvars > 0);
184 
185  SCIP_CALL( SCIPallocBufferArray(scip, &x, nvars) );
186 
187  /* compile expression exprtree, if not done before */
188  if( SCIPexprtreeGetInterpreterData(exprtree) == NULL )
189  {
190  SCIP_CALL( SCIPexprintCompile(exprint, exprtree) );
191  }
192 
193  for( i = 0; i < nvars; ++i )
194  {
195  x[i] = SCIPgetSolVal(scip, projection, SCIPexprtreeGetVars(exprtree)[i]);
196  }
197 
198  SCIP_CALL( SCIPexprintGrad(exprint, exprtree, x, TRUE, &val, grad) );
199 
200  /*SCIPdebug( for( i = 0; i < nvars; ++i ) printf("%e [%s]\n", grad[i], SCIPvarGetName(SCIPexprtreeGetVars(exprtree)[i])) );*/
201 
202  SCIPfreeBufferArray(scip, &x);
203 
204  return SCIP_OKAY;
205 }
206 
207 /** computes gradient cut (linearization) of nlrow at projection */
208 static
210  SCIP* scip, /**< SCIP data structure */
211  SCIP_SEPA* sepa, /**< the cut separator itself */
212  SCIP_EXPRINT* exprint, /**< expression interpreter */
213  SCIP_SOL* projection, /**< point where we compute gradient cut */
214  SCIP_NLROW* nlrow, /**< constraint for which we generate gradient cut */
215  CONVEXSIDE convexside, /**< which side makes the nlrow convex */
216  SCIP_Real activity, /**< activity of constraint at projection */
217  SCIP_ROW** row /**< storage for cut */
218  )
219 {
220  char rowname[SCIP_MAXSTRLEN];
221  SCIP_SEPADATA* sepadata;
222  SCIP_Real gradx0; /* <grad f(x_0), x_0> */
223  int i;
224 
225  assert(scip != NULL);
226  assert(sepa != NULL);
227  assert(exprint != NULL);
228  assert(nlrow != NULL);
229  assert(row != NULL);
230 
231  sepadata = SCIPsepaGetData(sepa);
232 
233  assert(sepadata != NULL);
234 
235  gradx0 = 0.0;
236 
237  /* an nlrow has a linear part, quadratic part and expression tree; ideally one would just build the gradient but we
238  * do not know if the different parts share variables or not, so we can't just build the gradient; for this reason
239  * we create the row right away and compute the gradients of each part independently and add them to the row; the
240  * row takes care to add coeffs corresponding to the same variable when they appear in different parts of the nlrow
241  * NOTE: a gradient cut is globally valid whenever the constraint from which it is deduced is globally valid; since
242  * we build the convex relaxation using only globally valid constraints, the cuts are globally valid
243  */
244  (void) SCIPsnprintf(rowname, SCIP_MAXSTRLEN, "proj_cut_%s_%u", SCIPnlrowGetName(nlrow), ++(sepadata->ncuts));
245  SCIP_CALL( SCIPcreateEmptyRowSepa(scip, row, sepa, rowname, -SCIPinfinity(scip), SCIPinfinity(scip), TRUE, FALSE ,
246  TRUE) );
247 
248  SCIP_CALL( SCIPcacheRowExtensions(scip, *row) );
249 
250  /* linear part */
251  for( i = 0; i < SCIPnlrowGetNLinearVars(nlrow); i++ )
252  {
253  gradx0 += SCIPgetSolVal(scip, projection, SCIPnlrowGetLinearVars(nlrow)[i]) * SCIPnlrowGetLinearCoefs(nlrow)[i];
254  SCIP_CALL( SCIPaddVarToRow(scip, *row, SCIPnlrowGetLinearVars(nlrow)[i], SCIPnlrowGetLinearCoefs(nlrow)[i]) );
255  }
256 
257  /* quadratic part */
258  for( i = 0; i < SCIPnlrowGetNQuadElems(nlrow); i++ )
259  {
260  SCIP_VAR* var1;
261  SCIP_VAR* var2;
262  SCIP_Real grad1;
263  SCIP_Real grad2;
264 
265  var1 = SCIPnlrowGetQuadVars(nlrow)[SCIPnlrowGetQuadElems(nlrow)[i].idx1];
266  var2 = SCIPnlrowGetQuadVars(nlrow)[SCIPnlrowGetQuadElems(nlrow)[i].idx2];
267  grad1 = SCIPnlrowGetQuadElems(nlrow)[i].coef * SCIPgetSolVal(scip, projection, var2);
268  grad2 = SCIPnlrowGetQuadElems(nlrow)[i].coef * SCIPgetSolVal(scip, projection, var1);
269 
270  SCIP_CALL( SCIPaddVarToRow(scip, *row, var1, grad1) );
271  SCIP_CALL( SCIPaddVarToRow(scip, *row, var2, grad2) );
272 
273  gradx0 += grad1 * SCIPgetSolVal(scip, projection, var1) + grad2 * SCIPgetSolVal(scip, projection, var2);
274  }
275 
276  /* expression tree part */
277  {
278  SCIP_Real* grad;
279  SCIP_EXPRTREE* tree;
280 
281  tree = SCIPnlrowGetExprtree(nlrow);
282 
283  if( tree != NULL && SCIPexprtreeGetNVars(tree) > 0 )
284  {
285  SCIP_CALL( SCIPallocBufferArray(scip, &grad, SCIPexprtreeGetNVars(tree)) );
286 
287  SCIP_CALL( computeGradient(scip, sepadata->exprinterpreter, projection, tree, grad) );
288 
289  for( i = 0; i < SCIPexprtreeGetNVars(tree); i++ )
290  {
291  gradx0 += grad[i] * SCIPgetSolVal(scip, projection, SCIPexprtreeGetVars(tree)[i]);
292  SCIP_CALL( SCIPaddVarToRow(scip, *row, SCIPexprtreeGetVars(tree)[i], grad[i]) );
293  }
294 
295  SCIPfreeBufferArray(scip, &grad);
296  }
297  }
298 
299  SCIP_CALL( SCIPflushRowExtensions(scip, *row) );
300 
301  SCIPdebugPrintf("gradient: ");
302  SCIPdebug( SCIP_CALL( SCIPprintRow(scip, *row, NULL) ) );
303  SCIPdebugPrintf("gradient dot x_0: %g\n", gradx0);
304 
305  /* gradient cut is f(x_0) - <grad f(x_0), x_0> + <grad f(x_0), x> <= rhs or >= lhs */
306  if( convexside == RHS )
307  {
308  assert(!SCIPisInfinity(scip, SCIPnlrowGetRhs(nlrow)));
309  SCIP_CALL( SCIPchgRowRhs(scip, *row, SCIPnlrowGetRhs(nlrow) - activity + gradx0) );
310  }
311  else
312  {
313  assert(convexside == LHS);
314  assert(!SCIPisInfinity(scip, -SCIPnlrowGetLhs(nlrow)));
315  SCIP_CALL( SCIPchgRowLhs(scip, *row, SCIPnlrowGetLhs(nlrow) - activity + gradx0) );
316  }
317 
318  SCIPdebugPrintf("gradient cut: ");
319  SCIPdebug( SCIP_CALL( SCIPprintRow(scip, *row, NULL) ) );
320 
321  return SCIP_OKAY;
322 }
323 
324 /** set quadratic part of objective function: \f$ \sum_i x_i^2 \f$; the objective function is \f$ ||x - x_0||^2 \f$,
325  * where \f$ x_0 \f$ is the point to separate; the only part that changes is the term \f$ -2 \langle x_0, x \rangle \f$
326  * which is linear and is set every time we want to separate a point, see separateCuts
327  */
328 static
330  SCIP* scip, /**< SCIP data structure */
331  SCIP_SEPADATA* sepadata /**< the cut separator data */
332  )
333 {
334  SCIP_QUADELEM* quadelems;
335  int i;
336 
337  assert(scip != NULL);
338  assert(sepadata != NULL);
339  assert(sepadata->nlpi != NULL);
340  assert(sepadata->nlpiprob != NULL);
341  assert(sepadata->var2nlpiidx != NULL);
342  assert(sepadata->nlpinvars > 0);
343 
344  SCIP_CALL( SCIPallocBufferArray(scip, &quadelems, sepadata->nlpinvars) );
345  for( i = 0; i < sepadata->nlpinvars; i++ )
346  {
347  SCIP_VAR* var;
348 
349  var = sepadata->nlpivars[i];
350  assert(SCIPhashmapExists(sepadata->var2nlpiidx, (void*)var) );
351 
352  quadelems[i].idx1 = SCIPhashmapGetImageInt(sepadata->var2nlpiidx, (void*)var);
353  quadelems[i].idx2 = quadelems[i].idx1;
354  quadelems[i].coef = 1.0;
355  }
356 
357  /* set quadratic part of objective function */
358  SCIP_CALL( SCIPnlpiSetObjective(sepadata->nlpi, sepadata->nlpiprob,
359  0, NULL, NULL, sepadata->nlpinvars, quadelems, NULL, NULL, 0.0) );
360 
361  /* free memory */
362  SCIPfreeBufferArray(scip, &quadelems);
363 
364  return SCIP_OKAY;
365 }
366 
367 /** projects sol onto convex relaxation (stored in sepadata) and tries to generate gradient cuts at the projection
368  * it generates cuts only for the constraints that were violated by the LP solution and are now active or still
369  * violated (in case we don't solve to optimality).
370  * @todo: store a feasible solution if one is found to use as warmstart
371  */
372 static
374  SCIP* scip, /**< SCIP data structure */
375  SCIP_SEPA* sepa, /**< the cut separator itself */
376  SCIP_SOL* sol, /**< solution that should be separated */
377  SCIP_RESULT* result /**< pointer to store the result of the separation call */
378  )
379 {
380  SCIP_SEPADATA* sepadata;
381  SCIP_SOL* projection;
382  SCIP_Real* linvals;
383  SCIP_Real* nlpisol;
384  SCIP_Real timelimit;
385  int nlpinvars;
386  int i;
387  int iterlimit;
388  int* lininds;
389  SCIP_Bool nlpunstable;
390 
391  nlpunstable = FALSE;
392 
393  assert(sepa != NULL);
394 
395  sepadata = SCIPsepaGetData(sepa);
396 
397  assert(result != NULL);
398  assert(sepadata != NULL);
399  assert(sepadata->nnlrows > 0);
400  assert(sepadata->nlpi != NULL);
401  assert(sepadata->nlpinvars > 0);
402  assert(sepadata->nlrows != NULL);
403  assert(sepadata->nlpiprob != NULL);
404  assert(sepadata->var2nlpiidx != NULL);
405  assert(sepadata->convexsides != NULL);
406  assert(sepadata->constraintviolation != NULL);
407 
408  nlpinvars = sepadata->nlpinvars;
409  /* set linear part of objective function: \norm(x - x^0)^2 = \norm(x)^2 - \sum 2 * x_i * x^0_i + const
410  * we ignore the constant; x0 is `sol`
411  */
412  SCIP_CALL( SCIPallocBufferArray(scip, &linvals, nlpinvars) );
413  SCIP_CALL( SCIPallocBufferArray(scip, &lininds, nlpinvars) );
414  for( i = 0; i < nlpinvars; i++ )
415  {
416  SCIP_VAR* var;
417 
418  var = sepadata->nlpivars[i];
419  assert(SCIPhashmapExists(sepadata->var2nlpiidx, (void*)var) );
420 
421  lininds[i] = SCIPhashmapGetImageInt(sepadata->var2nlpiidx, (void*)var);
422  linvals[i] = - 2.0 * SCIPgetSolVal(scip, sol, var);
423 
424  /* if coefficient is too large, don't separate */
425  if( SCIPisHugeValue(scip, REALABS(linvals[i])) )
426  {
427  SCIPdebugMsg(scip, "Don't separate points too close to infinity\n");
428  goto CLEANUP;
429  }
430  }
431 
432  /* set linear part of objective function */
433  SCIP_CALL( SCIPnlpiChgLinearCoefs(sepadata->nlpi, sepadata->nlpiprob, -1, nlpinvars, lininds, linvals) );
434 
435  /* set parameters in nlpi; time and iterations limit, tolerance, verbosity; for time limit, get time limit of scip;
436  * if scip doesn't have much time left, don't run separator. otherwise, timelimit is the minimum between whats left
437  * for scip and the timelimit setting
438  */
439  SCIP_CALL( SCIPgetRealParam(scip, "limits/time", &timelimit) );
440  if( !SCIPisInfinity(scip, timelimit) )
441  {
442  timelimit -= SCIPgetSolvingTime(scip);
443  if( timelimit <= 1.0 )
444  {
445  SCIPdebugMsg(scip, "skip NLP solve; no time left\n");
446  goto CLEANUP;
447  }
448  }
449  if( sepadata->nlptimelimit > 0.0 )
450  timelimit = MIN(sepadata->nlptimelimit, timelimit);
451  SCIP_CALL( SCIPnlpiSetRealPar(sepadata->nlpi, sepadata->nlpiprob, SCIP_NLPPAR_TILIM, timelimit) );
452 
453  iterlimit = sepadata->nlpiterlimit > 0 ? sepadata->nlpiterlimit : INT_MAX;
454  SCIP_CALL( SCIPnlpiSetIntPar(sepadata->nlpi, sepadata->nlpiprob, SCIP_NLPPAR_ITLIM, iterlimit) );
455  SCIP_CALL( SCIPnlpiSetRealPar(sepadata->nlpi, sepadata->nlpiprob, SCIP_NLPPAR_FEASTOL, SCIPfeastol(scip) / 10.0) ); /* use tighter tolerances for the NLP solver */
456  SCIP_CALL( SCIPnlpiSetRealPar(sepadata->nlpi, sepadata->nlpiprob, SCIP_NLPPAR_RELOBJTOL, MAX(SCIPfeastol(scip), SCIPdualfeastol(scip))) ); /*lint !e666*/
457  SCIP_CALL( SCIPnlpiSetIntPar(sepadata->nlpi, sepadata->nlpiprob, SCIP_NLPPAR_VERBLEVEL, NLPVERBOSITY) );
458 
459  /* compute the projection onto the convex NLP relaxation */
460  SCIP_CALL( SCIPnlpiSolve(sepadata->nlpi, sepadata->nlpiprob) );
461  SCIPdebugMsg(scip, "NLP solstat = %d\n", SCIPnlpiGetSolstat(sepadata->nlpi, sepadata->nlpiprob));
462 
463  /* if solution is feasible, add cuts */
464  switch( SCIPnlpiGetSolstat(sepadata->nlpi, sepadata->nlpiprob) )
465  {
468  /* @todo: if solution is optimal, we might as well add the cut <x - P(x_0), x_0 - P(x_0)> <= 0
469  * even though this cut is implied by all the gradient cuts of the rows active at the projection,
470  * we do not add them all (only the gradient cuts of constraints that violated the LP solution */
472  /* generate cuts for violated constraints (at sol) that are active or still violated at the projection, since
473  * a suboptimal solution or numerical issues could give a solution of the projection problem where constraints
474  * are not active; if the solution of the projection problem is in the interior of the region, we do nothing
475  */
476 
477  /* get solution: build SCIP_SOL out of nlpi sol */
478  SCIP_CALL( SCIPnlpiGetSolution(sepadata->nlpi, sepadata->nlpiprob, &nlpisol, NULL, NULL, NULL, NULL) );
479  assert(nlpisol != NULL);
480 
481  SCIP_CALL( SCIPcreateSol(scip, &projection, NULL) );
482  for( i = 0; i < nlpinvars; i++ )
483  {
484  SCIP_VAR* var;
485 
486  var = sepadata->nlpivars[i];
487  assert(SCIPhashmapExists(sepadata->var2nlpiidx, (void*)var) );
488 
489  SCIP_CALL( SCIPsetSolVal(scip, projection, var,
490  nlpisol[SCIPhashmapGetImageInt(sepadata->var2nlpiidx, (void *)var)]) );
491  }
492  SCIPdebug( SCIPprintSol(scip, projection, NULL, TRUE) );
493 
494  /* check for active or violated constraints */
495  for( i = 0; i < sepadata->nnlrows; ++i )
496  {
497  SCIP_NLROW* nlrow;
498  CONVEXSIDE convexside;
499  SCIP_Real activity;
500 
501  /* ignore constraints that are not violated by `sol` */
502  if( SCIPisFeasZero(scip, sepadata->constraintviolation[i]) )
503  continue;
504 
505  convexside = sepadata->convexsides[i];
506  nlrow = sepadata->nlrows[i];
507  assert(nlrow != NULL);
508 
509  /* check for currently active constraints at projected point */
510  SCIP_CALL( SCIPgetNlRowSolActivity(scip, nlrow, projection, &activity) );
511 
512  SCIPdebugMsg(scip, "NlRow activity at nlpi solution: %g <= %g <= %g\n", SCIPnlrowGetLhs(nlrow), activity,
513  SCIPnlrowGetRhs(nlrow) );
514 
515  /* if nlrow is active or violates the projection, build gradient cut at projection */
516  if( (convexside == RHS && SCIPisFeasGE(scip, activity, SCIPnlrowGetRhs(nlrow)))
517  || (convexside == LHS && SCIPisFeasLE(scip, activity, SCIPnlrowGetLhs(nlrow))) )
518  {
519  SCIP_ROW* row;
520 
521  SCIP_CALL( generateCut(scip, sepa, sepadata->exprinterpreter, projection, nlrow, convexside, activity,
522  &row) );
523 
524  SCIPdebugMsg(scip, "active or violated nlrow: (sols vio: %e)\n", sepadata->constraintviolation[i]);
525  SCIPdebug( SCIP_CALL( SCIPprintNlRow(scip, nlrow, NULL) ) );
526  SCIPdebugMsg(scip, "cut with efficacy %g generated\n", SCIPgetCutEfficacy(scip, sol, row));
527  SCIPdebug( SCIPprintRow(scip, row, NULL) );
528 
529  /* add cut if it is efficacious for the point we want to separate (sol) */
530  if( SCIPisCutEfficacious(scip, sol, row) )
531  {
532  SCIP_Bool infeasible;
533 
534  SCIP_CALL( SCIPaddRow(scip, row, FALSE, &infeasible) );
535 
536  if( infeasible )
537  {
538  *result = SCIP_CUTOFF;
539  SCIP_CALL( SCIPreleaseRow(scip, &row) );
540  break;
541  }
542  else
543  {
544  *result = SCIP_SEPARATED;
545  }
546  }
547 
548  /* release the row */
549  SCIP_CALL( SCIPreleaseRow(scip, &row) );
550  }
551  }
552 
553 #ifdef SCIP_DEBUG
554  {
555  SCIP_Real distance;
556 
557  /* compute distance between LP sol and its projection (only makes sense when it is optimal) */
558  distance = 0.0;
559  for( i = 0; i < SCIPgetNNLPVars(scip); ++i )
560  {
561  SCIP_VAR* var;
562 
563  var = SCIPgetNLPVars(scip)[i];
564  assert(var != NULL);
565 
566  /* assert NLP solution is within the bounds of the variable (only make sense when sol is optimal) */
567  if( !SCIPisInfinity(scip, -SCIPvarGetLbLocal(var)) )
568  assert(SCIPisFeasLE(scip, SCIPvarGetLbLocal(var), SCIPvarGetNLPSol(var)));
569  if( !SCIPisInfinity(scip, SCIPvarGetUbLocal(var)) )
570  assert(SCIPisFeasLE(scip, SCIPvarGetNLPSol(var), SCIPvarGetUbLocal(var)));
571 
572  /*SCIPdebugMsg(scip, "NLP sol (LP sol): %s = %f (%g)\n", SCIPvarGetName(var),
573  * SCIPvarGetNLPSol(var), SCIPgetSolVal(scip, sol, var));
574  */
575 
576  distance += SQR( SCIPvarGetNLPSol(var) - SCIPgetSolVal(scip, sol, var) );
577  }
578 
579  SCIPdebugMsg(scip, "NLP objval: %e, distance: %e\n", SCIPgetNLPObjval(scip), distance);
580  }
581 #endif
582 
583  /* free solution */
584  SCIP_CALL( SCIPfreeSol(scip, &projection) );
585  break;
586 
589  /* fallthrough;
590  * @todo: write what it means to be locinfeasible and why it can't be used to cutoff the node */
592  /* unknown... assume numerical issues */
593  nlpunstable = TRUE;
594  break;
595 
597  default:
598  SCIPerrorMessage("Projection NLP is not unbounded by construction, should not get here!\n");
599  SCIPABORT();
600  nlpunstable = TRUE;
601  }
602 
603  /* if nlp is detected to be unstable, don't try to separate again */
604  if( nlpunstable )
605  {
606  /* @todo: maybe change objective function to \sum [(x_i - x_i^*)/max(|x_i^*|, 1)]^2
607  * or some other scaling when unstable and try again.
608  * maybe free it here */
609  sepadata->skipsepa = TRUE;
610  }
611 
612  /* reset objective */
613  BMSclearMemoryArray(linvals, nlpinvars);
614  SCIP_CALL( SCIPnlpiChgLinearCoefs(sepadata->nlpi, sepadata->nlpiprob, -1, nlpinvars, lininds, linvals) );
615 
616 CLEANUP:
617  /* free memory */
618  SCIPfreeBufferArray(scip, &lininds);
619  SCIPfreeBufferArray(scip, &linvals);
620 
621  return SCIP_OKAY;
622 }
623 
624 /** computes the violation and maximum violation of the convex nlrows stored in sepadata wrt sol */
625 static
627  SCIP* scip, /**< SCIP data structure */
628  SCIP_SEPADATA* sepadata, /**< separator data */
629  SCIP_SOL* sol, /**< solution that should be separated */
630  SCIP_Real* maxviolation /**< buffer to store maximum violation */
631  )
632 {
633  SCIP_NLROW* nlrow;
634  int i;
635 
636  assert(sepadata != NULL);
637  assert(sepadata->nnlrows > 0);
638  assert(sepadata->nlrows != NULL);
639  assert(sepadata->convexsides != NULL);
640  assert(sepadata->constraintviolation != NULL);
641 
642  *maxviolation = 0.0;
643  for( i = 0; i < sepadata->nnlrows; i++ )
644  {
645  SCIP_Real activity;
646  SCIP_Real violation;
647 
648  nlrow = sepadata->nlrows[i];
649 
650  /* get activity of nlrow */
651  SCIP_CALL( SCIPgetNlRowSolActivity(scip, nlrow, sol, &activity) );
652 
653  /* violation = max{activity - rhs, 0.0} when convex and max{lhs - activity, 0.0} when concave */
654  if( sepadata->convexsides[i] == RHS )
655  {
657  assert(!SCIPisInfinity(scip, SCIPnlrowGetRhs(nlrow)));
658 
659  violation = activity - SCIPnlrowGetRhs(nlrow);
660  sepadata->constraintviolation[i] = MAX(violation, 0.0);
661  }
662  if( sepadata->convexsides[i] == LHS )
663  {
665  assert(!SCIPisInfinity(scip, -SCIPnlrowGetLhs(nlrow)));
666 
667  violation = SCIPnlrowGetLhs(nlrow) - activity;
668  sepadata->constraintviolation[i] = MAX(violation, 0.0);
669  }
670 
671  /* compute maximum */
672  if( *maxviolation < sepadata->constraintviolation[i] )
673  *maxviolation = sepadata->constraintviolation[i];
674  }
675 
676  SCIPdebugMsg(scip, "Maximum violation %g\n", *maxviolation);
677 
678  return SCIP_OKAY;
679 }
680 
681 
682 /** stores, from the constraints represented by nlrows, the nonlinear convex ones in sepadata */
683 static
685  SCIP* scip, /**< SCIP data structure */
686  SCIP_SEPADATA* sepadata, /**< separator data */
687  SCIP_NLROW** nlrows, /**< nlrows from which to store convex ones */
688  int nnlrows /**< number of nlrows */
689  )
690 {
691  int i;
692 
693  assert(scip != NULL);
694  assert(sepadata != NULL);
695 
696  SCIPdebugMsg(scip, "storing convex nlrows\n");
697 
698  sepadata->nlrowssize = nnlrows;
699  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(sepadata->nlrows), nnlrows) );
700  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(sepadata->convexsides), nnlrows) );
701  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(sepadata->constraintviolation), nnlrows) );
702 
703  /* count the number of nonlinear convex rows and store them */
704  sepadata->nnlrows = 0;
705  for( i = 0; i < nnlrows; ++i )
706  {
707  SCIP_NLROW* nlrow;
708 
709  nlrow = nlrows[i];
710  assert(nlrow != NULL);
711 
712  /* linear case */
714  (SCIPnlrowGetNQuadElems(nlrow) == 0 && SCIPnlrowGetExprtree(nlrow) == NULL) )
715  continue;
716 
717  /* nonlinear case */
719  {
720  sepadata->convexsides[sepadata->nnlrows] = RHS;
721  sepadata->nlrows[sepadata->nnlrows] = nlrow;
722  ++(sepadata->nnlrows);
723  }
724  else if( !SCIPisInfinity(scip, -SCIPnlrowGetLhs(nlrow)) && SCIPnlrowGetCurvature(nlrow) == SCIP_EXPRCURV_CONCAVE )
725  {
726  sepadata->convexsides[sepadata->nnlrows] = LHS;
727  sepadata->nlrows[sepadata->nnlrows] = nlrow;
728  ++(sepadata->nnlrows);
729  }
730  }
731 
732  return SCIP_OKAY;
733 }
734 
735 
736 /*
737  * Callback methods of separator
738  */
739 
740 
741 /** destructor of separator to free user data (called when SCIP is exiting) */
742 static
743 SCIP_DECL_SEPAFREE(sepaFreeConvexproj)
744 { /*lint --e{715}*/
745  SCIP_SEPADATA* sepadata;
746 
747  assert(strcmp(SCIPsepaGetName(sepa), SEPA_NAME) == 0);
748 
749  /* free separator data */
750  sepadata = SCIPsepaGetData(sepa);
751  assert(sepadata != NULL);
752 
753  SCIP_CALL( sepadataClear(scip, sepadata) );
754 
755  SCIPfreeBlockMemory(scip, &sepadata);
756 
757  SCIPsepaSetData(sepa, NULL);
758 
759  return SCIP_OKAY;
760 }
761 
762 /** solving process deinitialization method of separator (called before branch and bound process data is freed) */
763 static
764 SCIP_DECL_SEPAEXITSOL(sepaExitsolConvexproj)
765 { /*lint --e{715}*/
766  SCIP_SEPADATA* sepadata;
767 
768  assert(sepa != NULL);
769 
770  sepadata = SCIPsepaGetData(sepa);
771 
772  assert(sepadata != NULL);
773 
774  SCIP_CALL( sepadataClear(scip, sepadata) );
775 
776  return SCIP_OKAY;
777 }
778 
779 
780 /** LP solution separation method of separator */
781 static
782 SCIP_DECL_SEPAEXECLP(sepaExeclpConvexproj)
783 { /*lint --e{715}*/
784  SCIP_Real maxviolation;
785  SCIP_SOL* lpsol;
786  SCIP_SEPADATA* sepadata;
787 
788  *result = SCIP_DIDNOTRUN;
789 
790  sepadata = SCIPsepaGetData(sepa);
791  assert(sepadata != NULL);
792 
793  /* do not run if there is no interesting convex relaxation (with at least one nonlinear convex constraint),
794  * or if we have found it to be numerically unstable
795  * @todo: should it be with at least 2 nonlinear convex constraints?
796  */
797  if( sepadata->skipsepa )
798  {
799  SCIPdebugMsg(scip, "not running because convex relaxation is uninteresting or numerically unstable\n");
800  return SCIP_OKAY;
801  }
802 
803  /* the separator needs an NLP solver */
804  if( SCIPgetNNlpis(scip) == 0 )
805  return SCIP_OKAY;
806 
807  /* only call separator up to a maximum depth */
808  if( sepadata->maxdepth >= 0 && SCIPgetDepth(scip) > sepadata->maxdepth )
809  return SCIP_OKAY;
810 
811  /* only call separator, if we are not close to terminating */
812  if( SCIPisStopped(scip) )
813  return SCIP_OKAY;
814 
815  /* do not run if SCIP does not have constructed an NLP */
816  if( !SCIPisNLPConstructed(scip) )
817  {
818  SCIPdebugMsg(scip, "NLP not constructed, skipping convex projection separator\n");
819  return SCIP_OKAY;
820  }
821 
822  /* recompute convex NLP relaxation if the variable set changed and we are still at the root node
823  * @todo: does it make sense to do this??? */
824  if( sepadata->nlpiprob != NULL && SCIPgetNVars(scip) != sepadata->nlpinvars && SCIPgetDepth(scip) == 0 )
825  {
826  SCIP_CALL( sepadataClear(scip, sepadata) );
827  assert(sepadata->nlpiprob == NULL);
828  }
829 
830  /* create or update convex NLP relaxation */
831  if( sepadata->nlpiprob == NULL )
832  {
833  /* store convex nonlinear constraints */
835 
836  /* check that convex NLP relaxation is interesting (more than one nonlinear constraint) */
837  if( sepadata->nnlrows < 1 )
838  {
839  SCIPdebugMsg(scip, "convex relaxation uninteresting, don't run\n");
840  sepadata->skipsepa = TRUE;
841  return SCIP_OKAY;
842  }
843 
844  /* create the expression interpreter */
845  SCIP_CALL( SCIPexprintCreate(SCIPblkmem(scip), &sepadata->exprinterpreter) );
846 
847  sepadata->nlpinvars = SCIPgetNVars(scip);
848  sepadata->nlpi = SCIPgetNlpis(scip)[0];
849  assert(sepadata->nlpi != NULL);
850 
851  SCIP_CALL( SCIPnlpiCreateProblem(sepadata->nlpi, &sepadata->nlpiprob, "convexproj-nlp") );
852  SCIP_CALL( SCIPhashmapCreate(&sepadata->var2nlpiidx, SCIPblkmem(scip), sepadata->nlpinvars) );
853  SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &sepadata->nlpivars, SCIPgetVars(scip), sepadata->nlpinvars) ); /*lint !e666*/
854 
856  sepadata->nlpiprob, sepadata->var2nlpiidx, NULL, NULL, SCIPgetCutoffbound(scip), FALSE, TRUE) );
857 
858  /* add rows of the LP */
859  if( SCIPgetDepth(scip) == 0 )
860  {
861  SCIP_CALL( SCIPaddNlpiProbRows(scip, sepadata->nlpi, sepadata->nlpiprob, sepadata->var2nlpiidx,
863  }
864 
865  /* set quadratic part of objective function */
866  SCIP_CALL( setQuadraticObj(scip, sepadata) );
867  }
868  else
869  {
870  SCIP_CALL( SCIPupdateNlpiProb(scip, sepadata->nlpi, sepadata->nlpiprob, sepadata->var2nlpiidx,
871  sepadata->nlpivars, sepadata->nlpinvars, SCIPgetCutoffbound(scip)) );
872  }
873 
874  /* assert that the lp solution satisfies the cutoff bound; if this fails then we shouldn't have a cutoff bound in the
875  * nlpi, since then the projection could be in the interior of the actual convex relaxation */
878 
879  /* get current sol: LP or pseudo solution if LP sol is not available */
881 
882  /* do not run if current solution's violation is small */
883  SCIP_CALL( computeMaxViolation(scip, sepadata, lpsol, &maxviolation) );
884  if( maxviolation < VIOLATIONFAC * SCIPfeastol(scip) )
885  {
886  SCIPdebugMsg(scip, "solution doesn't violate constraints enough, do not separate\n");
887  SCIP_CALL( SCIPfreeSol(scip, &lpsol) );
888  return SCIP_OKAY;
889  }
890 
891  /* run the separator */
892  *result = SCIP_DIDNOTFIND;
893 
894  /* separateCuts computes the projection and then gradient cuts on each constraint that was originally violated */
895  SCIP_CALL( separateCuts(scip, sepa, lpsol, result) );
896 
897  /* free memory */
898  SCIP_CALL( SCIPfreeSol(scip, &lpsol) );
899 
900  return SCIP_OKAY;
901 }
902 
903 
904 /*
905  * separator specific interface methods
906  */
907 
908 /** creates the convexproj separator and includes it in SCIP */
910  SCIP* scip /**< SCIP data structure */
911  )
912 {
913  SCIP_SEPADATA* sepadata;
914  SCIP_SEPA* sepa;
915 
916  /* create convexproj separator data */
917  SCIP_CALL( SCIPallocBlockMemory(scip, &sepadata) );
918 
919  /* this sets all data in sepadata to 0 */
920  BMSclearMemory(sepadata);
921 
922  /* include separator */
925  sepaExeclpConvexproj, NULL,
926  sepadata) );
927  assert(sepa != NULL);
928 
929  /* set non fundamental callbacks via setter functions */
930  SCIP_CALL( SCIPsetSepaFree(scip, sepa, sepaFreeConvexproj) );
931  SCIP_CALL( SCIPsetSepaExitsol(scip, sepa, sepaExitsolConvexproj) );
932 
933  /* add convexproj separator parameters */
934  SCIP_CALL( SCIPaddIntParam(scip, "separating/" SEPA_NAME "/maxdepth",
935  "maximal depth at which the separator is applied (-1: unlimited)",
936  &sepadata->maxdepth, FALSE, DEFAULT_MAXDEPTH, -1, INT_MAX, NULL, NULL) );
937 
938  SCIP_CALL( SCIPaddIntParam(scip, "separating/" SEPA_NAME "/nlpiterlimit",
939  "iteration limit of NLP solver; 0 for no limit",
940  &sepadata->nlpiterlimit, TRUE, DEFAULT_NLPITERLIM, 0, INT_MAX, NULL, NULL) );
941 
942  SCIP_CALL( SCIPaddRealParam(scip, "separating/" SEPA_NAME "/nlptimelimit",
943  "time limit of NLP solver; 0.0 for no limit",
944  &sepadata->nlptimelimit, TRUE, DEFAULT_NLPTIMELIMIT, 0.0, SCIP_REAL_MAX, NULL, NULL) );
945 
946  return SCIP_OKAY;
947 }
enum SCIP_Result SCIP_RESULT
Definition: type_result.h:52
#define SCIPfreeBlockMemoryArray(scip, ptr, num)
Definition: scip_mem.h:97
SCIP_Real SCIPfeastol(SCIP *scip)
SCIP_RETCODE SCIPfreeSol(SCIP *scip, SCIP_SOL **sol)
Definition: scip_sol.c:977
SCIP_Real SCIPdualfeastol(SCIP *scip)
convexproj separator
SCIP_Bool SCIPisStopped(SCIP *scip)
Definition: scip_general.c:687
SCIP_Real SCIPgetNLPObjval(SCIP *scip)
Definition: scip_nlp.c:690
static SCIP_RETCODE storeNonlinearConvexNlrows(SCIP *scip, SCIP_SEPADATA *sepadata, SCIP_NLROW **nlrows, int nnlrows)
SCIP_EXPRTREE * SCIPnlrowGetExprtree(SCIP_NLROW *nlrow)
Definition: nlp.c:3370
#define SCIPallocBlockMemoryArray(scip, ptr, num)
Definition: scip_mem.h:80
SCIP_RETCODE SCIPsetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var, SCIP_Real val)
Definition: scip_sol.c:1213
public methods for SCIP parameter handling
methods to interpret (evaluate) an expression tree "fast"
int SCIPgetNLPRows(SCIP *scip)
Definition: scip_lp.c:596
static SCIP_DECL_SEPAEXECLP(sepaExeclpConvexproj)
static SCIP_RETCODE computeMaxViolation(SCIP *scip, SCIP_SEPADATA *sepadata, SCIP_SOL *sol, SCIP_Real *maxviolation)
public methods for memory management
SCIP_NLPI ** SCIPgetNlpis(SCIP *scip)
Definition: scip_nlp.c:119
SCIP_EXPORT SCIP_Real SCIPvarGetNLPSol(SCIP_VAR *var)
Definition: var.c:18054
#define SCIP_MAXSTRLEN
Definition: def.h:273
SCIP_RETCODE SCIPprintNlRow(SCIP *scip, SCIP_NLROW *nlrow, FILE *file)
Definition: scip_nlp.c:2031
SCIP_Real SCIPgetSolVal(SCIP *scip, SCIP_SOL *sol, SCIP_VAR *var)
Definition: scip_sol.c:1353
internal methods for NLPI solver interfaces
SCIP_RETCODE SCIPprintRow(SCIP *scip, SCIP_ROW *row, FILE *file)
Definition: scip_lp.c:2152
static SCIP_DECL_SEPAEXITSOL(sepaExitsolConvexproj)
public methods for timing
SCIP_RETCODE SCIPnlpiCreateProblem(SCIP_NLPI *nlpi, SCIP_NLPIPROBLEM **problem, const char *name)
Definition: nlpi.c:212
int SCIPgetNVars(SCIP *scip)
Definition: scip_prob.c:1986
SCIP_Real SCIPgetSolvingTime(SCIP *scip)
Definition: scip_timing.c:360
#define FALSE
Definition: def.h:73
static SCIP_RETCODE setQuadraticObj(SCIP *scip, SCIP_SEPADATA *sepadata)
#define TRUE
Definition: def.h:72
#define SCIPdebug(x)
Definition: pub_message.h:84
enum SCIP_Retcode SCIP_RETCODE
Definition: type_retcode.h:54
SCIP_EXPORT SCIP_RETCODE SCIPexprintGrad(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree, SCIP_Real *varvals, SCIP_Bool new_varvals, SCIP_Real *val, SCIP_Real *gradient)
SCIP_Bool SCIPisFeasLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
public methods for problem variables
#define SCIPfreeBlockMemory(scip, ptr)
Definition: scip_mem.h:95
SCIP_RETCODE SCIPflushRowExtensions(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1604
SCIP_RETCODE SCIPnlpiSetRealPar(SCIP_NLPI *nlpi, SCIP_NLPIPROBLEM *problem, SCIP_NLPPARAM type, SCIP_Real dval)
Definition: nlpi.c:672
#define SCIPfreeBufferArray(scip, ptr)
Definition: scip_mem.h:123
#define SCIPallocBlockMemory(scip, ptr)
Definition: scip_mem.h:78
#define SCIPdebugMsg
Definition: scip_message.h:69
public methods for separator plugins
SCIP_Real SCIPgetCutoffbound(SCIP *scip)
SCIP_VAR ** x
Definition: circlepacking.c:54
SCIP_LPSOLSTAT SCIPgetLPSolstat(SCIP *scip)
Definition: scip_lp.c:159
SCIP_Bool SCIPisInfinity(SCIP *scip, SCIP_Real val)
SCIP_Real SCIPgetCutEfficacy(SCIP *scip, SCIP_SOL *sol, SCIP_ROW *cut)
Definition: scip_cut.c:65
SCIP_ROW ** SCIPgetLPRows(SCIP *scip)
Definition: scip_lp.c:575
public methods for numerical tolerances
SCIP_RETCODE SCIPnlpiSetObjective(SCIP_NLPI *nlpi, SCIP_NLPIPROBLEM *problem, int nlins, const int *lininds, const SCIP_Real *linvals, int nquadelems, const SCIP_QUADELEM *quadelems, const int *exprvaridxs, const SCIP_EXPRTREE *exprtree, const SCIP_Real constant)
Definition: nlpi.c:301
SCIP_RETCODE SCIPcreateSol(SCIP *scip, SCIP_SOL **sol, SCIP_HEUR *heur)
Definition: scip_sol.c:320
public methods for expressions, expression trees, expression graphs, and related stuff ...
public methods for querying solving statistics
SCIP_Bool SCIPisLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
int SCIPhashmapGetImageInt(SCIP_HASHMAP *hashmap, void *origin)
Definition: misc.c:3220
public methods for the branch-and-bound tree
SCIP_Bool SCIPhashmapExists(SCIP_HASHMAP *hashmap, void *origin)
Definition: misc.c:3362
#define SCIPduplicateBlockMemoryArray(scip, ptr, source, num)
Definition: scip_mem.h:92
SCIP_Real coef
Definition: type_expr.h:104
SCIP_RETCODE SCIPcacheRowExtensions(SCIP *scip, SCIP_ROW *row)
Definition: scip_lp.c:1581
#define SEPA_PRIORITY
SCIP_NLROW ** SCIPgetNLPNlRows(SCIP *scip)
Definition: scip_nlp.c:417
SCIP_RETCODE SCIPincludeSepaConvexproj(SCIP *scip)
#define SCIPerrorMessage
Definition: pub_message.h:55
#define SCIPdebugPrintf
Definition: pub_message.h:90
SCIP_RETCODE SCIPnlpiGetSolution(SCIP_NLPI *nlpi, SCIP_NLPIPROBLEM *problem, SCIP_Real **primalvalues, SCIP_Real **consdualvalues, SCIP_Real **varlbdualvalues, SCIP_Real **varubdualvalues, SCIP_Real *objval)
Definition: nlpi.c:538
SCIP_RETCODE SCIPreleaseRow(SCIP *scip, SCIP_ROW **row)
Definition: scip_lp.c:1508
public methods for nonlinear functions
SCIP_VAR ** SCIPgetVars(SCIP *scip)
Definition: scip_prob.c:1941
BMS_BLKMEM * SCIPblkmem(SCIP *scip)
Definition: scip_mem.c:48
SCIP_NLPSOLSTAT SCIPnlpiGetSolstat(SCIP_NLPI *nlpi, SCIP_NLPIPROBLEM *problem)
Definition: nlpi.c:512
int SCIPnlrowGetNQuadElems(SCIP_NLROW *nlrow)
Definition: nlp.c:3329
SCIP_EXPORT SCIP_RETCODE SCIPexprintFree(SCIP_EXPRINT **exprint)
#define NULL
Definition: lpi_spx1.cpp:155
#define REALABS(x)
Definition: def.h:187
SCIP_RETCODE SCIPcreateNlpiProb(SCIP *scip, SCIP_NLPI *nlpi, SCIP_NLROW **nlrows, int nnlrows, SCIP_NLPIPROBLEM *nlpiprob, SCIP_HASHMAP *var2idx, SCIP_HASHMAP *nlrow2idx, SCIP_Real *nlscore, SCIP_Real cutoffbound, SCIP_Bool setobj, SCIP_Bool onlyconvex)
SCIP_RETCODE SCIPcreateCurrentSol(SCIP *scip, SCIP_SOL **sol, SCIP_HEUR *heur)
Definition: scip_sol.c:475
int SCIPexprtreeGetNVars(SCIP_EXPRTREE *tree)
Definition: expr.c:8614
#define SEPA_DESC
#define SCIP_CALL(x)
Definition: def.h:364
int SCIPnlrowGetNLinearVars(SCIP_NLROW *nlrow)
Definition: nlp.c:3252
int SCIPgetNNLPNlRows(SCIP *scip)
Definition: scip_nlp.c:439
SCIP_EXPORT SCIP_SEPADATA * SCIPsepaGetData(SCIP_SEPA *sepa)
Definition: sepa.c:608
SCIP_EXPORT const char * SCIPsepaGetName(SCIP_SEPA *sepa)
Definition: sepa.c:697
SCIP_QUADELEM * SCIPnlrowGetQuadElems(SCIP_NLROW *nlrow)
Definition: nlp.c:3339
SCIP_EXPORT SCIP_RETCODE SCIPexprintCreate(BMS_BLKMEM *blkmem, SCIP_EXPRINT **exprint)
SCIP_Real SCIPgetLPObjval(SCIP *scip)
Definition: scip_lp.c:238
public methods for NLP management
SCIP_RETCODE SCIPgetRealParam(SCIP *scip, const char *name, SCIP_Real *value)
Definition: scip_param.c:298
SCIP_Bool SCIPisFeasZero(SCIP *scip, SCIP_Real val)
SCIP_EXPRCURV SCIPnlrowGetCurvature(SCIP_NLROW *nlrow)
Definition: nlp.c:3400
#define SCIPallocBufferArray(scip, ptr, num)
Definition: scip_mem.h:111
SCIP_Real SCIPinfinity(SCIP *scip)
public data structures and miscellaneous methods
SCIP_Real SCIPnlrowGetRhs(SCIP_NLROW *nlrow)
Definition: nlp.c:3390
int SCIPgetDepth(SCIP *scip)
Definition: scip_tree.c:638
#define SCIP_Bool
Definition: def.h:70
static SCIP_RETCODE separateCuts(SCIP *scip, SCIP_SEPA *sepa, SCIP_SOL *sol, SCIP_RESULT *result)
SCIP_RETCODE SCIPhashmapCreate(SCIP_HASHMAP **hashmap, BMS_BLKMEM *blkmem, int mapsize)
Definition: misc.c:3013
SCIP_VAR ** SCIPgetNLPVars(SCIP *scip)
Definition: scip_nlp.c:277
SCIP_Bool SCIPisNLPConstructed(SCIP *scip)
Definition: scip_nlp.c:210
SCIP_RETCODE SCIPincludeSepaBasic(SCIP *scip, SCIP_SEPA **sepa, const char *name, const char *desc, int priority, int freq, SCIP_Real maxbounddist, SCIP_Bool usessubscip, SCIP_Bool delay, SCIP_DECL_SEPAEXECLP((*sepaexeclp)), SCIP_DECL_SEPAEXECSOL((*sepaexecsol)), SCIP_SEPADATA *sepadata)
Definition: scip_sepa.c:100
int SCIPgetNNlpis(SCIP *scip)
Definition: scip_nlp.c:132
static SCIP_RETCODE computeGradient(SCIP *scip, SCIP_EXPRINT *exprint, SCIP_SOL *projection, SCIP_EXPRTREE *exprtree, SCIP_Real *grad)
SCIP_EXPRINTDATA * SCIPexprtreeGetInterpreterData(SCIP_EXPRTREE *tree)
Definition: expr.c:8659
SCIP_RETCODE SCIPnlpiSetIntPar(SCIP_NLPI *nlpi, SCIP_NLPIPROBLEM *problem, SCIP_NLPPARAM type, int ival)
Definition: nlpi.c:637
#define MAX(x, y)
Definition: tclique_def.h:83
#define DEFAULT_MAXDEPTH
#define SEPA_NAME
public methods for cuts and aggregation rows
SCIP_VAR ** SCIPexprtreeGetVars(SCIP_EXPRTREE *tree)
Definition: nlp.c:103
SCIP_Bool SCIPisCutEfficacious(SCIP *scip, SCIP_SOL *sol, SCIP_ROW *cut)
Definition: scip_cut.c:88
SCIP_RETCODE SCIPnlpiSolve(SCIP_NLPI *nlpi, SCIP_NLPIPROBLEM *problem)
Definition: nlpi.c:498
SCIP_Real SCIPnlrowGetLhs(SCIP_NLROW *nlrow)
Definition: nlp.c:3380
SCIP_Bool SCIPisFeasGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
#define BMSclearMemory(ptr)
Definition: memory.h:121
SCIP_Real * SCIPnlrowGetLinearCoefs(SCIP_NLROW *nlrow)
Definition: nlp.c:3272
SCIP_EXPORT SCIP_Real SCIPvarGetLbLocal(SCIP_VAR *var)
Definition: var.c:17723
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:130
public methods for the LP relaxation, rows and columns
SCIP_RETCODE SCIPnlpiChgLinearCoefs(SCIP_NLPI *nlpi, SCIP_NLPIPROBLEM *problem, const int idx, int nvals, const int *varidxs, const SCIP_Real *vals)
Definition: nlpi.c:396
#define SCIP_REAL_MAX
Definition: def.h:164
public methods for nonlinear relaxations
SCIP_EXPORT SCIP_Real SCIPvarGetUbLocal(SCIP_VAR *var)
Definition: var.c:17733
static SCIP_RETCODE generateCut(SCIP *scip, SCIP_SEPA *sepa, SCIP_EXPRINT *exprint, SCIP_SOL *projection, SCIP_NLROW *nlrow, CONVEXSIDE convexside, SCIP_Real activity, SCIP_ROW **row)
#define DEFAULT_NLPITERLIM
SCIP_RETCODE SCIPaddRow(SCIP *scip, SCIP_ROW *row, SCIP_Bool forcecut, SCIP_Bool *infeasible)
Definition: scip_cut.c:221
#define SEPA_FREQ
general public methods
public methods for solutions
SCIP_RETCODE SCIPupdateNlpiProb(SCIP *scip, SCIP_NLPI *nlpi, SCIP_NLPIPROBLEM *nlpiprob, SCIP_HASHMAP *var2nlpiidx, SCIP_VAR **nlpivars, int nlpinvars, SCIP_Real cutoffbound)
SCIP_RETCODE SCIPchgRowRhs(SCIP *scip, SCIP_ROW *row, SCIP_Real rhs)
Definition: scip_lp.c:1553
SCIP_RETCODE SCIPchgRowLhs(SCIP *scip, SCIP_ROW *row, SCIP_Real lhs)
Definition: scip_lp.c:1529
SCIP_Bool SCIPisHugeValue(SCIP *scip, SCIP_Real val)
SCIP_RETCODE SCIPaddVarToRow(SCIP *scip, SCIP_ROW *row, SCIP_VAR *var, SCIP_Real val)
Definition: scip_lp.c:1641
SCIP_RETCODE SCIPnlpiFreeProblem(SCIP_NLPI *nlpi, SCIP_NLPIPROBLEM **problem)
Definition: nlpi.c:225
public methods for message output
int SCIPsnprintf(char *t, int len, const char *s,...)
Definition: misc.c:10590
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:74
SCIP_RETCODE SCIPprintSol(SCIP *scip, SCIP_SOL *sol, FILE *file, SCIP_Bool printzeros)
Definition: scip_sol.c:1767
const char * SCIPnlrowGetName(SCIP_NLROW *nlrow)
Definition: nlp.c:3419
void SCIPhashmapFree(SCIP_HASHMAP **hashmap)
Definition: misc.c:3047
#define SEPA_USESSUBSCIP
#define SCIP_Real
Definition: def.h:163
#define NLPVERBOSITY
public methods for message handling
static SCIP_DECL_SEPAFREE(sepaFreeConvexproj)
SCIP_VAR ** SCIPnlrowGetQuadVars(SCIP_NLROW *nlrow)
Definition: nlp.c:3292
SCIP_RETCODE SCIPsetSepaExitsol(SCIP *scip, SCIP_SEPA *sepa, SCIP_DECL_SEPAEXITSOL((*sepaexitsol)))
Definition: scip_sepa.c:222
SCIP_EXPORT void SCIPsepaSetData(SCIP_SEPA *sepa, SCIP_SEPADATA *sepadata)
Definition: sepa.c:618
ConvexSide
SCIP_VAR ** SCIPnlrowGetLinearVars(SCIP_NLROW *nlrow)
Definition: nlp.c:3262
#define SEPA_MAXBOUNDDIST
public methods for separators
#define BMSclearMemoryArray(ptr, num)
Definition: memory.h:122
SCIP_RETCODE SCIPsetSepaFree(SCIP *scip, SCIP_SEPA *sepa, SCIP_DECL_SEPAFREE((*sepafree)))
Definition: scip_sepa.c:158
#define SEPA_DELAY
#define SCIPABORT()
Definition: def.h:336
public methods for global and local (sub)problems
enum ConvexSide CONVEXSIDE
SCIP_RETCODE SCIPaddNlpiProbRows(SCIP *scip, SCIP_NLPI *nlpi, SCIP_NLPIPROBLEM *nlpiprob, SCIP_HASHMAP *var2idx, SCIP_ROW **rows, int nrows)
#define DEFAULT_NLPTIMELIMIT
struct SCIP_SepaData SCIP_SEPADATA
Definition: type_sepa.h:43
SCIP_EXPORT SCIP_RETCODE SCIPexprintCompile(SCIP_EXPRINT *exprint, SCIP_EXPRTREE *tree)
SCIP_RETCODE SCIPgetNlRowSolActivity(SCIP *scip, SCIP_NLROW *nlrow, SCIP_SOL *sol, SCIP_Real *activity)
Definition: scip_nlp.c:1938
int SCIPgetNNLPVars(SCIP *scip)
Definition: scip_nlp.c:299
SCIP_RETCODE SCIPcreateEmptyRowSepa(SCIP *scip, SCIP_ROW **row, SCIP_SEPA *sepa, const char *name, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool removable)
Definition: scip_lp.c:1399
static SCIP_RETCODE sepadataClear(SCIP *scip, SCIP_SEPADATA *sepadata)
#define VIOLATIONFAC
memory allocation routines