aboutsummaryrefslogtreecommitdiffstats
path: root/test/monniaux/glpk-4.65/src/intopt/fpump.c
blob: 0bdd6d4e5fca4cca2fe4fd7a0504483f981b6ea1 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
/* fpump.c (feasibility pump heuristic) */

/***********************************************************************
*  This code is part of GLPK (GNU Linear Programming Kit).
*
*  Copyright (C) 2009-2018 Andrew Makhorin, Department for Applied
*  Informatics, Moscow Aviation Institute, Moscow, Russia. All rights
*  reserved. E-mail: <mao@gnu.org>.
*
*  GLPK is free software: you can redistribute it and/or modify it
*  under the terms of the GNU General Public License as published by
*  the Free Software Foundation, either version 3 of the License, or
*  (at your option) any later version.
*
*  GLPK is distributed in the hope that it will be useful, but WITHOUT
*  ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
*  or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
*  License for more details.
*
*  You should have received a copy of the GNU General Public License
*  along with GLPK. If not, see <http://www.gnu.org/licenses/>.
***********************************************************************/

#include "env.h"
#include "ios.h"
#include "rng.h"

/***********************************************************************
*  NAME
*
*  ios_feas_pump - feasibility pump heuristic
*
*  SYNOPSIS
*
*  #include "glpios.h"
*  void ios_feas_pump(glp_tree *T);
*
*  DESCRIPTION
*
*  The routine ios_feas_pump is a simple implementation of the Feasi-
*  bility Pump heuristic.
*
*  REFERENCES
*
*  M.Fischetti, F.Glover, and A.Lodi. "The feasibility pump." Math.
*  Program., Ser. A 104, pp. 91-104 (2005). */

struct VAR
{     /* binary variable */
      int j;
      /* ordinal number */
      int x;
      /* value in the rounded solution (0 or 1) */
      double d;
      /* sorting key */
};

static int CDECL fcmp(const void *x, const void *y)
{     /* comparison routine */
      const struct VAR *vx = x, *vy = y;
      if (vx->d > vy->d)
         return -1;
      else if (vx->d < vy->d)
         return +1;
      else
         return 0;
}

void ios_feas_pump(glp_tree *T)
{     glp_prob *P = T->mip;
      int n = P->n;
      glp_prob *lp = NULL;
      struct VAR *var = NULL;
      RNG *rand = NULL;
      GLPCOL *col;
      glp_smcp parm;
      int j, k, new_x, nfail, npass, nv, ret, stalling;
      double dist, tol;
      xassert(glp_get_status(P) == GLP_OPT);
      /* this heuristic is applied only once on the root level */
      if (!(T->curr->level == 0 && T->curr->solved == 1)) goto done;
      /* determine number of binary variables */
      nv = 0;
      for (j = 1; j <= n; j++)
      {  col = P->col[j];
         /* if x[j] is continuous, skip it */
         if (col->kind == GLP_CV) continue;
         /* if x[j] is fixed, skip it */
         if (col->type == GLP_FX) continue;
         /* x[j] is non-fixed integer */
         xassert(col->kind == GLP_IV);
         if (col->type == GLP_DB && col->lb == 0.0 && col->ub == 1.0)
         {  /* x[j] is binary */
            nv++;
         }
         else
         {  /* x[j] is general integer */
            if (T->parm->msg_lev >= GLP_MSG_ALL)
               xprintf("FPUMP heuristic cannot be applied due to genera"
                  "l integer variables\n");
            goto done;
         }
      }
      /* there must be at least one binary variable */
      if (nv == 0) goto done;
      if (T->parm->msg_lev >= GLP_MSG_ALL)
         xprintf("Applying FPUMP heuristic...\n");
      /* build the list of binary variables */
      var = xcalloc(1+nv, sizeof(struct VAR));
      k = 0;
      for (j = 1; j <= n; j++)
      {  col = P->col[j];
         if (col->kind == GLP_IV && col->type == GLP_DB)
            var[++k].j = j;
      }
      xassert(k == nv);
      /* create working problem object */
      lp = glp_create_prob();
more: /* copy the original problem object to keep it intact */
      glp_copy_prob(lp, P, GLP_OFF);
      /* we are interested to find an integer feasible solution, which
         is better than the best known one */
      if (P->mip_stat == GLP_FEAS)
      {  int *ind;
         double *val, bnd;
         /* add a row and make it identical to the objective row */
         glp_add_rows(lp, 1);
         ind = xcalloc(1+n, sizeof(int));
         val = xcalloc(1+n, sizeof(double));
         for (j = 1; j <= n; j++)
         {  ind[j] = j;
            val[j] = P->col[j]->coef;
         }
         glp_set_mat_row(lp, lp->m, n, ind, val);
         xfree(ind);
         xfree(val);
         /* introduce upper (minimization) or lower (maximization)
            bound to the original objective function; note that this
            additional constraint is not violated at the optimal point
            to LP relaxation */
#if 0 /* modified by xypron <xypron.glpk@gmx.de> */
         if (P->dir == GLP_MIN)
         {  bnd = P->mip_obj - 0.10 * (1.0 + fabs(P->mip_obj));
            if (bnd < P->obj_val) bnd = P->obj_val;
            glp_set_row_bnds(lp, lp->m, GLP_UP, 0.0, bnd - P->c0);
         }
         else if (P->dir == GLP_MAX)
         {  bnd = P->mip_obj + 0.10 * (1.0 + fabs(P->mip_obj));
            if (bnd > P->obj_val) bnd = P->obj_val;
            glp_set_row_bnds(lp, lp->m, GLP_LO, bnd - P->c0, 0.0);
         }
         else
            xassert(P != P);
#else
         bnd = 0.1 * P->obj_val + 0.9 * P->mip_obj;
         /* xprintf("bnd = %f\n", bnd); */
         if (P->dir == GLP_MIN)
            glp_set_row_bnds(lp, lp->m, GLP_UP, 0.0, bnd - P->c0);
         else if (P->dir == GLP_MAX)
            glp_set_row_bnds(lp, lp->m, GLP_LO, bnd - P->c0, 0.0);
         else
            xassert(P != P);
#endif
      }
      /* reset pass count */
      npass = 0;
      /* invalidate the rounded point */
      for (k = 1; k <= nv; k++)
         var[k].x = -1;
pass: /* next pass starts here */
      npass++;
      if (T->parm->msg_lev >= GLP_MSG_ALL)
         xprintf("Pass %d\n", npass);
      /* initialize minimal distance between the basic point and the
         rounded one obtained during this pass */
      dist = DBL_MAX;
      /* reset failure count (the number of succeeded iterations failed
         to improve the distance) */
      nfail = 0;
      /* if it is not the first pass, perturb the last rounded point
         rather than construct it from the basic solution */
      if (npass > 1)
      {  double rho, temp;
         if (rand == NULL)
            rand = rng_create_rand();
         for (k = 1; k <= nv; k++)
         {  j = var[k].j;
            col = lp->col[j];
            rho = rng_uniform(rand, -0.3, 0.7);
            if (rho < 0.0) rho = 0.0;
            temp = fabs((double)var[k].x - col->prim);
            if (temp + rho > 0.5) var[k].x = 1 - var[k].x;
         }
         goto skip;
      }
loop: /* innermost loop begins here */
      /* round basic solution (which is assumed primal feasible) */
      stalling = 1;
      for (k = 1; k <= nv; k++)
      {  col = lp->col[var[k].j];
         if (col->prim < 0.5)
         {  /* rounded value is 0 */
            new_x = 0;
         }
         else
         {  /* rounded value is 1 */
            new_x = 1;
         }
         if (var[k].x != new_x)
         {  stalling = 0;
            var[k].x = new_x;
         }
      }
      /* if the rounded point has not changed (stalling), choose and
         flip some its entries heuristically */
      if (stalling)
      {  /* compute d[j] = |x[j] - round(x[j])| */
         for (k = 1; k <= nv; k++)
         {  col = lp->col[var[k].j];
            var[k].d = fabs(col->prim - (double)var[k].x);
         }
         /* sort the list of binary variables by descending d[j] */
         qsort(&var[1], nv, sizeof(struct VAR), fcmp);
         /* choose and flip some rounded components */
         for (k = 1; k <= nv; k++)
         {  if (k >= 5 && var[k].d < 0.35 || k >= 10) break;
            var[k].x = 1 - var[k].x;
         }
      }
skip: /* check if the time limit has been exhausted */
      if (T->parm->tm_lim < INT_MAX &&
         (double)(T->parm->tm_lim - 1) <=
         1000.0 * xdifftime(xtime(), T->tm_beg)) goto done;
      /* build the objective, which is the distance between the current
         (basic) point and the rounded one */
      lp->dir = GLP_MIN;
      lp->c0 = 0.0;
      for (j = 1; j <= n; j++)
         lp->col[j]->coef = 0.0;
      for (k = 1; k <= nv; k++)
      {  j = var[k].j;
         if (var[k].x == 0)
            lp->col[j]->coef = +1.0;
         else
         {  lp->col[j]->coef = -1.0;
            lp->c0 += 1.0;
         }
      }
      /* minimize the distance with the simplex method */
      glp_init_smcp(&parm);
      if (T->parm->msg_lev <= GLP_MSG_ERR)
         parm.msg_lev = T->parm->msg_lev;
      else if (T->parm->msg_lev <= GLP_MSG_ALL)
      {  parm.msg_lev = GLP_MSG_ON;
         parm.out_dly = 10000;
      }
      ret = glp_simplex(lp, &parm);
      if (ret != 0)
      {  if (T->parm->msg_lev >= GLP_MSG_ERR)
            xprintf("Warning: glp_simplex returned %d\n", ret);
         goto done;
      }
      ret = glp_get_status(lp);
      if (ret != GLP_OPT)
      {  if (T->parm->msg_lev >= GLP_MSG_ERR)
            xprintf("Warning: glp_get_status returned %d\n", ret);
         goto done;
      }
      if (T->parm->msg_lev >= GLP_MSG_DBG)
         xprintf("delta = %g\n", lp->obj_val);
      /* check if the basic solution is integer feasible; note that it
         may be so even if the minimial distance is positive */
      tol = 0.3 * T->parm->tol_int;
      for (k = 1; k <= nv; k++)
      {  col = lp->col[var[k].j];
         if (tol < col->prim && col->prim < 1.0 - tol) break;
      }
      if (k > nv)
      {  /* okay; the basic solution seems to be integer feasible */
         double *x = xcalloc(1+n, sizeof(double));
         for (j = 1; j <= n; j++)
         {  x[j] = lp->col[j]->prim;
            if (P->col[j]->kind == GLP_IV) x[j] = floor(x[j] + 0.5);
         }
#if 1 /* modified by xypron <xypron.glpk@gmx.de> */
         /* reset direction and right-hand side of objective */
         lp->c0  = P->c0;
         lp->dir = P->dir;
         /* fix integer variables */
         for (k = 1; k <= nv; k++)
#if 0 /* 18/VI-2013; fixed by mao
       * this bug causes numerical instability, because column statuses
       * are not changed appropriately */
         {  lp->col[var[k].j]->lb   = x[var[k].j];
            lp->col[var[k].j]->ub   = x[var[k].j];
            lp->col[var[k].j]->type = GLP_FX;
         }
#else
            glp_set_col_bnds(lp, var[k].j, GLP_FX, x[var[k].j], 0.);
#endif
         /* copy original objective function */
         for (j = 1; j <= n; j++)
            lp->col[j]->coef = P->col[j]->coef;
         /* solve original LP and copy result */
         ret = glp_simplex(lp, &parm);
         if (ret != 0)
         {  if (T->parm->msg_lev >= GLP_MSG_ERR)
               xprintf("Warning: glp_simplex returned %d\n", ret);
#if 1 /* 17/III-2016: fix memory leak */
            xfree(x);
#endif
            goto done;
         }
         ret = glp_get_status(lp);
         if (ret != GLP_OPT)
         {  if (T->parm->msg_lev >= GLP_MSG_ERR)
               xprintf("Warning: glp_get_status returned %d\n", ret);
#if 1 /* 17/III-2016: fix memory leak */
            xfree(x);
#endif
            goto done;
         }
         for (j = 1; j <= n; j++)
            if (P->col[j]->kind != GLP_IV) x[j] = lp->col[j]->prim;
#endif
         ret = glp_ios_heur_sol(T, x);
         xfree(x);
         if (ret == 0)
         {  /* the integer solution is accepted */
            if (ios_is_hopeful(T, T->curr->bound))
            {  /* it is reasonable to apply the heuristic once again */
               goto more;
            }
            else
            {  /* the best known integer feasible solution just found
                  is close to optimal solution to LP relaxation */
               goto done;
            }
         }
      }
      /* the basic solution is fractional */
      if (dist == DBL_MAX ||
          lp->obj_val <= dist - 1e-6 * (1.0 + dist))
      {  /* the distance is reducing */
         nfail = 0, dist = lp->obj_val;
      }
      else
      {  /* improving the distance failed */
         nfail++;
      }
      if (nfail < 3) goto loop;
      if (npass < 5) goto pass;
done: /* delete working objects */
      if (lp != NULL) glp_delete_prob(lp);
      if (var != NULL) xfree(var);
      if (rand != NULL) rng_delete_rand(rand);
      return;
}

/* eof */