Beispiel #1
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 <*****@*****.**> */
         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 <*****@*****.**> */
         /* 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);
            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;
         }
         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;
            }
         }
      }
Beispiel #2
0
MPL *mpl_initialize(void)
{     MPL *mpl;
      mpl = xmalloc(sizeof(MPL));
      /* scanning segment */
      mpl->line = 0;
      mpl->c = 0;
      mpl->token = 0;
      mpl->imlen = 0;
      mpl->image = xcalloc(MAX_LENGTH+1, sizeof(char));
      mpl->image[0] = '\0';
      mpl->value = 0.0;
      mpl->b_token = 0;
      mpl->b_imlen = 0;
      mpl->b_image = xcalloc(MAX_LENGTH+1, sizeof(char));
      mpl->b_image[0] = '\0';
      mpl->b_value = 0.0;
      mpl->f_dots = 0;
      mpl->f_scan = 0;
      mpl->f_token = 0;
      mpl->f_imlen = 0;
      mpl->f_image = xcalloc(MAX_LENGTH+1, sizeof(char));
      mpl->f_image[0] = '\0';
      mpl->f_value = 0.0;
      mpl->context = xcalloc(CONTEXT_SIZE, sizeof(char));
      memset(mpl->context, ' ', CONTEXT_SIZE);
      mpl->c_ptr = 0;
      mpl->flag_d = 0;
      /* translating segment */
      mpl->pool = dmp_create_poolx(0);
      mpl->tree = avl_create_tree(avl_strcmp, NULL);
      mpl->model = NULL;
      mpl->flag_x = 0;
      mpl->as_within = 0;
      mpl->as_in = 0;
      mpl->as_binary = 0;
      mpl->flag_s = 0;
      /* common segment */
      mpl->strings = dmp_create_poolx(sizeof(STRING));
      mpl->symbols = dmp_create_poolx(sizeof(SYMBOL));
      mpl->tuples = dmp_create_poolx(sizeof(TUPLE));
      mpl->arrays = dmp_create_poolx(sizeof(ARRAY));
      mpl->members = dmp_create_poolx(sizeof(MEMBER));
      mpl->elemvars = dmp_create_poolx(sizeof(ELEMVAR));
      mpl->formulae = dmp_create_poolx(sizeof(FORMULA));
      mpl->elemcons = dmp_create_poolx(sizeof(ELEMCON));
      mpl->a_list = NULL;
      mpl->sym_buf = xcalloc(255+1, sizeof(char));
      mpl->sym_buf[0] = '\0';
      mpl->tup_buf = xcalloc(255+1, sizeof(char));
      mpl->tup_buf[0] = '\0';
      /* generating/postsolving segment */
      mpl->rand = rng_create_rand();
      mpl->flag_p = 0;
      mpl->stmt = NULL;
#if 1 /* 11/II-2008 */
      mpl->dca = NULL;
#endif
      mpl->m = 0;
      mpl->n = 0;
      mpl->row = NULL;
      mpl->col = NULL;
      /* input/output segment */
      mpl->in_fp = NULL;
      mpl->in_file = NULL;
      mpl->out_fp = NULL;
      mpl->out_file = NULL;
      mpl->prt_fp = NULL;
      mpl->prt_file = NULL;
      /* solver interface segment */
      if (setjmp(mpl->jump)) xassert(mpl != mpl);
      mpl->phase = 0;
      mpl->mod_file = NULL;
      mpl->mpl_buf = xcalloc(255+1, sizeof(char));
      mpl->mpl_buf[0] = '\0';
      return mpl;
}