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/* glpios02.c (preprocess current subproblem) */
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/***********************************************************************
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* This code is part of GLPK (GNU Linear Programming Kit).
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*
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* Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008,
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* 2009, 2010 Andrew Makhorin, Department for Applied Informatics,
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* Moscow Aviation Institute, Moscow, Russia. All rights reserved.
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* E-mail: <mao@gnu.org>.
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*
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* GLPK is free software: you can redistribute it and/or modify it
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* under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* GLPK is distributed in the hope that it will be useful, but WITHOUT
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* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
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* or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
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* License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with GLPK. If not, see <http://www.gnu.org/licenses/>.
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***********************************************************************/
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#include "glpios.h"
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/***********************************************************************
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* prepare_row_info - prepare row info to determine implied bounds
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*
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* Given a row (linear form)
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*
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* n
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* sum a[j] * x[j] (1)
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* j=1
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*
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* and bounds of columns (variables)
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*
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* l[j] <= x[j] <= u[j] (2)
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*
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* this routine computes f_min, j_min, f_max, j_max needed to determine
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* implied bounds.
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*
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* ALGORITHM
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*
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* Let J+ = {j : a[j] > 0} and J- = {j : a[j] < 0}.
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*
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* Parameters f_min and j_min are computed as follows:
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*
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* 1) if there is no x[k] such that k in J+ and l[k] = -inf or k in J-
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* and u[k] = +inf, then
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*
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* f_min := sum a[j] * l[j] + sum a[j] * u[j]
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* j in J+ j in J-
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* (3)
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* j_min := 0
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*
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* 2) if there is exactly one x[k] such that k in J+ and l[k] = -inf
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* or k in J- and u[k] = +inf, then
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*
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* f_min := sum a[j] * l[j] + sum a[j] * u[j]
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* j in J+\{k} j in J-\{k}
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* (4)
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* j_min := k
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*
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* 3) if there are two or more x[k] such that k in J+ and l[k] = -inf
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* or k in J- and u[k] = +inf, then
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*
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* f_min := -inf
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* (5)
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* j_min := 0
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*
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* Parameters f_max and j_max are computed in a similar way as follows:
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*
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* 1) if there is no x[k] such that k in J+ and u[k] = +inf or k in J-
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* and l[k] = -inf, then
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*
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* f_max := sum a[j] * u[j] + sum a[j] * l[j]
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* j in J+ j in J-
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* (6)
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* j_max := 0
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*
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* 2) if there is exactly one x[k] such that k in J+ and u[k] = +inf
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* or k in J- and l[k] = -inf, then
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*
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* f_max := sum a[j] * u[j] + sum a[j] * l[j]
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* j in J+\{k} j in J-\{k}
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* (7)
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* j_max := k
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*
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* 3) if there are two or more x[k] such that k in J+ and u[k] = +inf
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* or k in J- and l[k] = -inf, then
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*
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* f_max := +inf
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* (8)
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* j_max := 0 */
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struct f_info
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{ int j_min, j_max;
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double f_min, f_max;
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};
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static void prepare_row_info(int n, const double a[], const double l[],
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const double u[], struct f_info *f)
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{ int j, j_min, j_max;
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double f_min, f_max;
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xassert(n >= 0);
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/* determine f_min and j_min */
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f_min = 0.0, j_min = 0;
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for (j = 1; j <= n; j++)
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{ if (a[j] > 0.0)
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{ if (l[j] == -DBL_MAX)
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{ if (j_min == 0)
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j_min = j;
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else
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{ f_min = -DBL_MAX, j_min = 0;
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break;
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}
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}
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else
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f_min += a[j] * l[j];
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}
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else if (a[j] < 0.0)
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{ if (u[j] == +DBL_MAX)
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{ if (j_min == 0)
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j_min = j;
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else
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{ f_min = -DBL_MAX, j_min = 0;
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break;
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}
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}
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else
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f_min += a[j] * u[j];
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}
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else
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xassert(a != a);
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}
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f->f_min = f_min, f->j_min = j_min;
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/* determine f_max and j_max */
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f_max = 0.0, j_max = 0;
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for (j = 1; j <= n; j++)
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{ if (a[j] > 0.0)
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{ if (u[j] == +DBL_MAX)
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{ if (j_max == 0)
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j_max = j;
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else
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{ f_max = +DBL_MAX, j_max = 0;
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break;
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}
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}
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else
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f_max += a[j] * u[j];
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}
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else if (a[j] < 0.0)
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{ if (l[j] == -DBL_MAX)
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{ if (j_max == 0)
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j_max = j;
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else
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{ f_max = +DBL_MAX, j_max = 0;
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break;
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}
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}
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else
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f_max += a[j] * l[j];
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}
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else
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xassert(a != a);
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}
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f->f_max = f_max, f->j_max = j_max;
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return;
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}
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/***********************************************************************
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* row_implied_bounds - determine row implied bounds
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*
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|
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* Given a row (linear form)
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|
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*
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* n
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|
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* sum a[j] * x[j]
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* j=1
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alpar@1
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*
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* and bounds of columns (variables)
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*
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* l[j] <= x[j] <= u[j]
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*
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* this routine determines implied bounds of the row.
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*
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|
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* ALGORITHM
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|
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*
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* Let J+ = {j : a[j] > 0} and J- = {j : a[j] < 0}.
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*
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|
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* The implied lower bound of the row is computed as follows:
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|
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*
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* L' := sum a[j] * l[j] + sum a[j] * u[j] (9)
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* j in J+ j in J-
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|
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*
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|
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* and as it follows from (3), (4), and (5):
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*
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* L' := if j_min = 0 then f_min else -inf (10)
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*
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|
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* The implied upper bound of the row is computed as follows:
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*
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* U' := sum a[j] * u[j] + sum a[j] * l[j] (11)
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* j in J+ j in J-
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*
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* and as it follows from (6), (7), and (8):
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|
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*
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* U' := if j_max = 0 then f_max else +inf (12)
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|
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*
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* The implied bounds are stored in locations LL and UU. */
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static void row_implied_bounds(const struct f_info *f, double *LL,
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double *UU)
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{ *LL = (f->j_min == 0 ? f->f_min : -DBL_MAX);
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|
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*UU = (f->j_max == 0 ? f->f_max : +DBL_MAX);
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|
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return;
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|
216 |
}
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|
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|
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/***********************************************************************
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alpar@1
|
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* col_implied_bounds - determine column implied bounds
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|
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*
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* Given a row (constraint)
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alpar@1
|
222 |
*
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|
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* n
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|
224 |
* L <= sum a[j] * x[j] <= U (13)
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* j=1
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*
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|
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* and bounds of columns (variables)
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*
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|
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* l[j] <= x[j] <= u[j]
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alpar@1
|
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*
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|
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* this routine determines implied bounds of variable x[k].
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|
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*
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|
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* It is assumed that if L != -inf, the lower bound of the row can be
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|
234 |
* active, and if U != +inf, the upper bound of the row can be active.
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|
235 |
*
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alpar@1
|
236 |
* ALGORITHM
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|
237 |
*
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|
238 |
* From (13) it follows that
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alpar@1
|
239 |
*
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alpar@1
|
240 |
* L <= sum a[j] * x[j] + a[k] * x[k] <= U
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alpar@1
|
241 |
* j!=k
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alpar@1
|
242 |
* or
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alpar@1
|
243 |
*
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alpar@1
|
244 |
* L - sum a[j] * x[j] <= a[k] * x[k] <= U - sum a[j] * x[j]
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alpar@1
|
245 |
* j!=k j!=k
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alpar@1
|
246 |
*
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alpar@1
|
247 |
* Thus, if the row lower bound L can be active, implied lower bound of
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alpar@1
|
248 |
* term a[k] * x[k] can be determined as follows:
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alpar@1
|
249 |
*
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alpar@1
|
250 |
* ilb(a[k] * x[k]) = min(L - sum a[j] * x[j]) =
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alpar@1
|
251 |
* j!=k
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alpar@1
|
252 |
* (14)
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alpar@1
|
253 |
* = L - max sum a[j] * x[j]
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alpar@1
|
254 |
* j!=k
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alpar@1
|
255 |
*
|
alpar@1
|
256 |
* where, as it follows from (6), (7), and (8)
|
alpar@1
|
257 |
*
|
alpar@1
|
258 |
* / f_max - a[k] * u[k], j_max = 0, a[k] > 0
|
alpar@1
|
259 |
* |
|
alpar@1
|
260 |
* | f_max - a[k] * l[k], j_max = 0, a[k] < 0
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alpar@1
|
261 |
* max sum a[j] * x[j] = {
|
alpar@1
|
262 |
* j!=k | f_max, j_max = k
|
alpar@1
|
263 |
* |
|
alpar@1
|
264 |
* \ +inf, j_max != 0
|
alpar@1
|
265 |
*
|
alpar@1
|
266 |
* and if the upper bound U can be active, implied upper bound of term
|
alpar@1
|
267 |
* a[k] * x[k] can be determined as follows:
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alpar@1
|
268 |
*
|
alpar@1
|
269 |
* iub(a[k] * x[k]) = max(U - sum a[j] * x[j]) =
|
alpar@1
|
270 |
* j!=k
|
alpar@1
|
271 |
* (15)
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alpar@1
|
272 |
* = U - min sum a[j] * x[j]
|
alpar@1
|
273 |
* j!=k
|
alpar@1
|
274 |
*
|
alpar@1
|
275 |
* where, as it follows from (3), (4), and (5)
|
alpar@1
|
276 |
*
|
alpar@1
|
277 |
* / f_min - a[k] * l[k], j_min = 0, a[k] > 0
|
alpar@1
|
278 |
* |
|
alpar@1
|
279 |
* | f_min - a[k] * u[k], j_min = 0, a[k] < 0
|
alpar@1
|
280 |
* min sum a[j] * x[j] = {
|
alpar@1
|
281 |
* j!=k | f_min, j_min = k
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alpar@1
|
282 |
* |
|
alpar@1
|
283 |
* \ -inf, j_min != 0
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alpar@1
|
284 |
*
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alpar@1
|
285 |
* Since
|
alpar@1
|
286 |
*
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alpar@1
|
287 |
* ilb(a[k] * x[k]) <= a[k] * x[k] <= iub(a[k] * x[k])
|
alpar@1
|
288 |
*
|
alpar@1
|
289 |
* implied lower and upper bounds of x[k] are determined as follows:
|
alpar@1
|
290 |
*
|
alpar@1
|
291 |
* l'[k] := if a[k] > 0 then ilb / a[k] else ulb / a[k] (16)
|
alpar@1
|
292 |
*
|
alpar@1
|
293 |
* u'[k] := if a[k] > 0 then ulb / a[k] else ilb / a[k] (17)
|
alpar@1
|
294 |
*
|
alpar@1
|
295 |
* The implied bounds are stored in locations ll and uu. */
|
alpar@1
|
296 |
|
alpar@1
|
297 |
static void col_implied_bounds(const struct f_info *f, int n,
|
alpar@1
|
298 |
const double a[], double L, double U, const double l[],
|
alpar@1
|
299 |
const double u[], int k, double *ll, double *uu)
|
alpar@1
|
300 |
{ double ilb, iub;
|
alpar@1
|
301 |
xassert(n >= 0);
|
alpar@1
|
302 |
xassert(1 <= k && k <= n);
|
alpar@1
|
303 |
/* determine implied lower bound of term a[k] * x[k] (14) */
|
alpar@1
|
304 |
if (L == -DBL_MAX || f->f_max == +DBL_MAX)
|
alpar@1
|
305 |
ilb = -DBL_MAX;
|
alpar@1
|
306 |
else if (f->j_max == 0)
|
alpar@1
|
307 |
{ if (a[k] > 0.0)
|
alpar@1
|
308 |
{ xassert(u[k] != +DBL_MAX);
|
alpar@1
|
309 |
ilb = L - (f->f_max - a[k] * u[k]);
|
alpar@1
|
310 |
}
|
alpar@1
|
311 |
else if (a[k] < 0.0)
|
alpar@1
|
312 |
{ xassert(l[k] != -DBL_MAX);
|
alpar@1
|
313 |
ilb = L - (f->f_max - a[k] * l[k]);
|
alpar@1
|
314 |
}
|
alpar@1
|
315 |
else
|
alpar@1
|
316 |
xassert(a != a);
|
alpar@1
|
317 |
}
|
alpar@1
|
318 |
else if (f->j_max == k)
|
alpar@1
|
319 |
ilb = L - f->f_max;
|
alpar@1
|
320 |
else
|
alpar@1
|
321 |
ilb = -DBL_MAX;
|
alpar@1
|
322 |
/* determine implied upper bound of term a[k] * x[k] (15) */
|
alpar@1
|
323 |
if (U == +DBL_MAX || f->f_min == -DBL_MAX)
|
alpar@1
|
324 |
iub = +DBL_MAX;
|
alpar@1
|
325 |
else if (f->j_min == 0)
|
alpar@1
|
326 |
{ if (a[k] > 0.0)
|
alpar@1
|
327 |
{ xassert(l[k] != -DBL_MAX);
|
alpar@1
|
328 |
iub = U - (f->f_min - a[k] * l[k]);
|
alpar@1
|
329 |
}
|
alpar@1
|
330 |
else if (a[k] < 0.0)
|
alpar@1
|
331 |
{ xassert(u[k] != +DBL_MAX);
|
alpar@1
|
332 |
iub = U - (f->f_min - a[k] * u[k]);
|
alpar@1
|
333 |
}
|
alpar@1
|
334 |
else
|
alpar@1
|
335 |
xassert(a != a);
|
alpar@1
|
336 |
}
|
alpar@1
|
337 |
else if (f->j_min == k)
|
alpar@1
|
338 |
iub = U - f->f_min;
|
alpar@1
|
339 |
else
|
alpar@1
|
340 |
iub = +DBL_MAX;
|
alpar@1
|
341 |
/* determine implied bounds of x[k] (16) and (17) */
|
alpar@1
|
342 |
#if 1
|
alpar@1
|
343 |
/* do not use a[k] if it has small magnitude to prevent wrong
|
alpar@1
|
344 |
implied bounds; for example, 1e-15 * x1 >= x2 + x3, where
|
alpar@1
|
345 |
x1 >= -10, x2, x3 >= 0, would lead to wrong conclusion that
|
alpar@1
|
346 |
x1 >= 0 */
|
alpar@1
|
347 |
if (fabs(a[k]) < 1e-6)
|
alpar@1
|
348 |
*ll = -DBL_MAX, *uu = +DBL_MAX; else
|
alpar@1
|
349 |
#endif
|
alpar@1
|
350 |
if (a[k] > 0.0)
|
alpar@1
|
351 |
{ *ll = (ilb == -DBL_MAX ? -DBL_MAX : ilb / a[k]);
|
alpar@1
|
352 |
*uu = (iub == +DBL_MAX ? +DBL_MAX : iub / a[k]);
|
alpar@1
|
353 |
}
|
alpar@1
|
354 |
else if (a[k] < 0.0)
|
alpar@1
|
355 |
{ *ll = (iub == +DBL_MAX ? -DBL_MAX : iub / a[k]);
|
alpar@1
|
356 |
*uu = (ilb == -DBL_MAX ? +DBL_MAX : ilb / a[k]);
|
alpar@1
|
357 |
}
|
alpar@1
|
358 |
else
|
alpar@1
|
359 |
xassert(a != a);
|
alpar@1
|
360 |
return;
|
alpar@1
|
361 |
}
|
alpar@1
|
362 |
|
alpar@1
|
363 |
/***********************************************************************
|
alpar@1
|
364 |
* check_row_bounds - check and relax original row bounds
|
alpar@1
|
365 |
*
|
alpar@1
|
366 |
* Given a row (constraint)
|
alpar@1
|
367 |
*
|
alpar@1
|
368 |
* n
|
alpar@1
|
369 |
* L <= sum a[j] * x[j] <= U
|
alpar@1
|
370 |
* j=1
|
alpar@1
|
371 |
*
|
alpar@1
|
372 |
* and bounds of columns (variables)
|
alpar@1
|
373 |
*
|
alpar@1
|
374 |
* l[j] <= x[j] <= u[j]
|
alpar@1
|
375 |
*
|
alpar@1
|
376 |
* this routine checks the original row bounds L and U for feasibility
|
alpar@1
|
377 |
* and redundancy. If the original lower bound L or/and upper bound U
|
alpar@1
|
378 |
* cannot be active due to bounds of variables, the routine remove them
|
alpar@1
|
379 |
* replacing by -inf or/and +inf, respectively.
|
alpar@1
|
380 |
*
|
alpar@1
|
381 |
* If no primal infeasibility is detected, the routine returns zero,
|
alpar@1
|
382 |
* otherwise non-zero. */
|
alpar@1
|
383 |
|
alpar@1
|
384 |
static int check_row_bounds(const struct f_info *f, double *L_,
|
alpar@1
|
385 |
double *U_)
|
alpar@1
|
386 |
{ int ret = 0;
|
alpar@1
|
387 |
double L = *L_, U = *U_, LL, UU;
|
alpar@1
|
388 |
/* determine implied bounds of the row */
|
alpar@1
|
389 |
row_implied_bounds(f, &LL, &UU);
|
alpar@1
|
390 |
/* check if the original lower bound is infeasible */
|
alpar@1
|
391 |
if (L != -DBL_MAX)
|
alpar@1
|
392 |
{ double eps = 1e-3 * (1.0 + fabs(L));
|
alpar@1
|
393 |
if (UU < L - eps)
|
alpar@1
|
394 |
{ ret = 1;
|
alpar@1
|
395 |
goto done;
|
alpar@1
|
396 |
}
|
alpar@1
|
397 |
}
|
alpar@1
|
398 |
/* check if the original upper bound is infeasible */
|
alpar@1
|
399 |
if (U != +DBL_MAX)
|
alpar@1
|
400 |
{ double eps = 1e-3 * (1.0 + fabs(U));
|
alpar@1
|
401 |
if (LL > U + eps)
|
alpar@1
|
402 |
{ ret = 1;
|
alpar@1
|
403 |
goto done;
|
alpar@1
|
404 |
}
|
alpar@1
|
405 |
}
|
alpar@1
|
406 |
/* check if the original lower bound is redundant */
|
alpar@1
|
407 |
if (L != -DBL_MAX)
|
alpar@1
|
408 |
{ double eps = 1e-12 * (1.0 + fabs(L));
|
alpar@1
|
409 |
if (LL > L - eps)
|
alpar@1
|
410 |
{ /* it cannot be active, so remove it */
|
alpar@1
|
411 |
*L_ = -DBL_MAX;
|
alpar@1
|
412 |
}
|
alpar@1
|
413 |
}
|
alpar@1
|
414 |
/* check if the original upper bound is redundant */
|
alpar@1
|
415 |
if (U != +DBL_MAX)
|
alpar@1
|
416 |
{ double eps = 1e-12 * (1.0 + fabs(U));
|
alpar@1
|
417 |
if (UU < U + eps)
|
alpar@1
|
418 |
{ /* it cannot be active, so remove it */
|
alpar@1
|
419 |
*U_ = +DBL_MAX;
|
alpar@1
|
420 |
}
|
alpar@1
|
421 |
}
|
alpar@1
|
422 |
done: return ret;
|
alpar@1
|
423 |
}
|
alpar@1
|
424 |
|
alpar@1
|
425 |
/***********************************************************************
|
alpar@1
|
426 |
* check_col_bounds - check and tighten original column bounds
|
alpar@1
|
427 |
*
|
alpar@1
|
428 |
* Given a row (constraint)
|
alpar@1
|
429 |
*
|
alpar@1
|
430 |
* n
|
alpar@1
|
431 |
* L <= sum a[j] * x[j] <= U
|
alpar@1
|
432 |
* j=1
|
alpar@1
|
433 |
*
|
alpar@1
|
434 |
* and bounds of columns (variables)
|
alpar@1
|
435 |
*
|
alpar@1
|
436 |
* l[j] <= x[j] <= u[j]
|
alpar@1
|
437 |
*
|
alpar@1
|
438 |
* for column (variable) x[j] this routine checks the original column
|
alpar@1
|
439 |
* bounds l[j] and u[j] for feasibility and redundancy. If the original
|
alpar@1
|
440 |
* lower bound l[j] or/and upper bound u[j] cannot be active due to
|
alpar@1
|
441 |
* bounds of the constraint and other variables, the routine tighten
|
alpar@1
|
442 |
* them replacing by corresponding implied bounds, if possible.
|
alpar@1
|
443 |
*
|
alpar@1
|
444 |
* NOTE: It is assumed that if L != -inf, the row lower bound can be
|
alpar@1
|
445 |
* active, and if U != +inf, the row upper bound can be active.
|
alpar@1
|
446 |
*
|
alpar@1
|
447 |
* The flag means that variable x[j] is required to be integer.
|
alpar@1
|
448 |
*
|
alpar@1
|
449 |
* New actual bounds for x[j] are stored in locations lj and uj.
|
alpar@1
|
450 |
*
|
alpar@1
|
451 |
* If no primal infeasibility is detected, the routine returns zero,
|
alpar@1
|
452 |
* otherwise non-zero. */
|
alpar@1
|
453 |
|
alpar@1
|
454 |
static int check_col_bounds(const struct f_info *f, int n,
|
alpar@1
|
455 |
const double a[], double L, double U, const double l[],
|
alpar@1
|
456 |
const double u[], int flag, int j, double *_lj, double *_uj)
|
alpar@1
|
457 |
{ int ret = 0;
|
alpar@1
|
458 |
double lj, uj, ll, uu;
|
alpar@1
|
459 |
xassert(n >= 0);
|
alpar@1
|
460 |
xassert(1 <= j && j <= n);
|
alpar@1
|
461 |
lj = l[j], uj = u[j];
|
alpar@1
|
462 |
/* determine implied bounds of the column */
|
alpar@1
|
463 |
col_implied_bounds(f, n, a, L, U, l, u, j, &ll, &uu);
|
alpar@1
|
464 |
/* if x[j] is integral, round its implied bounds */
|
alpar@1
|
465 |
if (flag)
|
alpar@1
|
466 |
{ if (ll != -DBL_MAX)
|
alpar@1
|
467 |
ll = (ll - floor(ll) < 1e-3 ? floor(ll) : ceil(ll));
|
alpar@1
|
468 |
if (uu != +DBL_MAX)
|
alpar@1
|
469 |
uu = (ceil(uu) - uu < 1e-3 ? ceil(uu) : floor(uu));
|
alpar@1
|
470 |
}
|
alpar@1
|
471 |
/* check if the original lower bound is infeasible */
|
alpar@1
|
472 |
if (lj != -DBL_MAX)
|
alpar@1
|
473 |
{ double eps = 1e-3 * (1.0 + fabs(lj));
|
alpar@1
|
474 |
if (uu < lj - eps)
|
alpar@1
|
475 |
{ ret = 1;
|
alpar@1
|
476 |
goto done;
|
alpar@1
|
477 |
}
|
alpar@1
|
478 |
}
|
alpar@1
|
479 |
/* check if the original upper bound is infeasible */
|
alpar@1
|
480 |
if (uj != +DBL_MAX)
|
alpar@1
|
481 |
{ double eps = 1e-3 * (1.0 + fabs(uj));
|
alpar@1
|
482 |
if (ll > uj + eps)
|
alpar@1
|
483 |
{ ret = 1;
|
alpar@1
|
484 |
goto done;
|
alpar@1
|
485 |
}
|
alpar@1
|
486 |
}
|
alpar@1
|
487 |
/* check if the original lower bound is redundant */
|
alpar@1
|
488 |
if (ll != -DBL_MAX)
|
alpar@1
|
489 |
{ double eps = 1e-3 * (1.0 + fabs(ll));
|
alpar@1
|
490 |
if (lj < ll - eps)
|
alpar@1
|
491 |
{ /* it cannot be active, so tighten it */
|
alpar@1
|
492 |
lj = ll;
|
alpar@1
|
493 |
}
|
alpar@1
|
494 |
}
|
alpar@1
|
495 |
/* check if the original upper bound is redundant */
|
alpar@1
|
496 |
if (uu != +DBL_MAX)
|
alpar@1
|
497 |
{ double eps = 1e-3 * (1.0 + fabs(uu));
|
alpar@1
|
498 |
if (uj > uu + eps)
|
alpar@1
|
499 |
{ /* it cannot be active, so tighten it */
|
alpar@1
|
500 |
uj = uu;
|
alpar@1
|
501 |
}
|
alpar@1
|
502 |
}
|
alpar@1
|
503 |
/* due to round-off errors it may happen that lj > uj (although
|
alpar@1
|
504 |
lj < uj + eps, since no primal infeasibility is detected), so
|
alpar@1
|
505 |
adjuct the new actual bounds to provide lj <= uj */
|
alpar@1
|
506 |
if (!(lj == -DBL_MAX || uj == +DBL_MAX))
|
alpar@1
|
507 |
{ double t1 = fabs(lj), t2 = fabs(uj);
|
alpar@1
|
508 |
double eps = 1e-10 * (1.0 + (t1 <= t2 ? t1 : t2));
|
alpar@1
|
509 |
if (lj > uj - eps)
|
alpar@1
|
510 |
{ if (lj == l[j])
|
alpar@1
|
511 |
uj = lj;
|
alpar@1
|
512 |
else if (uj == u[j])
|
alpar@1
|
513 |
lj = uj;
|
alpar@1
|
514 |
else if (t1 <= t2)
|
alpar@1
|
515 |
uj = lj;
|
alpar@1
|
516 |
else
|
alpar@1
|
517 |
lj = uj;
|
alpar@1
|
518 |
}
|
alpar@1
|
519 |
}
|
alpar@1
|
520 |
*_lj = lj, *_uj = uj;
|
alpar@1
|
521 |
done: return ret;
|
alpar@1
|
522 |
}
|
alpar@1
|
523 |
|
alpar@1
|
524 |
/***********************************************************************
|
alpar@1
|
525 |
* check_efficiency - check if change in column bounds is efficient
|
alpar@1
|
526 |
*
|
alpar@1
|
527 |
* Given the original bounds of a column l and u and its new actual
|
alpar@1
|
528 |
* bounds l' and u' (possibly tighten by the routine check_col_bounds)
|
alpar@1
|
529 |
* this routine checks if the change in the column bounds is efficient
|
alpar@1
|
530 |
* enough. If so, the routine returns non-zero, otherwise zero.
|
alpar@1
|
531 |
*
|
alpar@1
|
532 |
* The flag means that the variable is required to be integer. */
|
alpar@1
|
533 |
|
alpar@1
|
534 |
static int check_efficiency(int flag, double l, double u, double ll,
|
alpar@1
|
535 |
double uu)
|
alpar@1
|
536 |
{ int eff = 0;
|
alpar@1
|
537 |
/* check efficiency for lower bound */
|
alpar@1
|
538 |
if (l < ll)
|
alpar@1
|
539 |
{ if (flag || l == -DBL_MAX)
|
alpar@1
|
540 |
eff++;
|
alpar@1
|
541 |
else
|
alpar@1
|
542 |
{ double r;
|
alpar@1
|
543 |
if (u == +DBL_MAX)
|
alpar@1
|
544 |
r = 1.0 + fabs(l);
|
alpar@1
|
545 |
else
|
alpar@1
|
546 |
r = 1.0 + (u - l);
|
alpar@1
|
547 |
if (ll - l >= 0.25 * r)
|
alpar@1
|
548 |
eff++;
|
alpar@1
|
549 |
}
|
alpar@1
|
550 |
}
|
alpar@1
|
551 |
/* check efficiency for upper bound */
|
alpar@1
|
552 |
if (u > uu)
|
alpar@1
|
553 |
{ if (flag || u == +DBL_MAX)
|
alpar@1
|
554 |
eff++;
|
alpar@1
|
555 |
else
|
alpar@1
|
556 |
{ double r;
|
alpar@1
|
557 |
if (l == -DBL_MAX)
|
alpar@1
|
558 |
r = 1.0 + fabs(u);
|
alpar@1
|
559 |
else
|
alpar@1
|
560 |
r = 1.0 + (u - l);
|
alpar@1
|
561 |
if (u - uu >= 0.25 * r)
|
alpar@1
|
562 |
eff++;
|
alpar@1
|
563 |
}
|
alpar@1
|
564 |
}
|
alpar@1
|
565 |
return eff;
|
alpar@1
|
566 |
}
|
alpar@1
|
567 |
|
alpar@1
|
568 |
/***********************************************************************
|
alpar@1
|
569 |
* basic_preprocessing - perform basic preprocessing
|
alpar@1
|
570 |
*
|
alpar@1
|
571 |
* This routine performs basic preprocessing of the specified MIP that
|
alpar@1
|
572 |
* includes relaxing some row bounds and tightening some column bounds.
|
alpar@1
|
573 |
*
|
alpar@1
|
574 |
* On entry the arrays L and U contains original row bounds, and the
|
alpar@1
|
575 |
* arrays l and u contains original column bounds:
|
alpar@1
|
576 |
*
|
alpar@1
|
577 |
* L[0] is the lower bound of the objective row;
|
alpar@1
|
578 |
* L[i], i = 1,...,m, is the lower bound of i-th row;
|
alpar@1
|
579 |
* U[0] is the upper bound of the objective row;
|
alpar@1
|
580 |
* U[i], i = 1,...,m, is the upper bound of i-th row;
|
alpar@1
|
581 |
* l[0] is not used;
|
alpar@1
|
582 |
* l[j], j = 1,...,n, is the lower bound of j-th column;
|
alpar@1
|
583 |
* u[0] is not used;
|
alpar@1
|
584 |
* u[j], j = 1,...,n, is the upper bound of j-th column.
|
alpar@1
|
585 |
*
|
alpar@1
|
586 |
* On exit the arrays L, U, l, and u contain new actual bounds of rows
|
alpar@1
|
587 |
* and column in the same locations.
|
alpar@1
|
588 |
*
|
alpar@1
|
589 |
* The parameters nrs and num specify an initial list of rows to be
|
alpar@1
|
590 |
* processed:
|
alpar@1
|
591 |
*
|
alpar@1
|
592 |
* nrs is the number of rows in the initial list, 0 <= nrs <= m+1;
|
alpar@1
|
593 |
* num[0] is not used;
|
alpar@1
|
594 |
* num[1,...,nrs] are row numbers (0 means the objective row).
|
alpar@1
|
595 |
*
|
alpar@1
|
596 |
* The parameter max_pass specifies the maximal number of times that
|
alpar@1
|
597 |
* each row can be processed, max_pass > 0.
|
alpar@1
|
598 |
*
|
alpar@1
|
599 |
* If no primal infeasibility is detected, the routine returns zero,
|
alpar@1
|
600 |
* otherwise non-zero. */
|
alpar@1
|
601 |
|
alpar@1
|
602 |
static int basic_preprocessing(glp_prob *mip, double L[], double U[],
|
alpar@1
|
603 |
double l[], double u[], int nrs, const int num[], int max_pass)
|
alpar@1
|
604 |
{ int m = mip->m;
|
alpar@1
|
605 |
int n = mip->n;
|
alpar@1
|
606 |
struct f_info f;
|
alpar@1
|
607 |
int i, j, k, len, size, ret = 0;
|
alpar@1
|
608 |
int *ind, *list, *mark, *pass;
|
alpar@1
|
609 |
double *val, *lb, *ub;
|
alpar@1
|
610 |
xassert(0 <= nrs && nrs <= m+1);
|
alpar@1
|
611 |
xassert(max_pass > 0);
|
alpar@1
|
612 |
/* allocate working arrays */
|
alpar@1
|
613 |
ind = xcalloc(1+n, sizeof(int));
|
alpar@1
|
614 |
list = xcalloc(1+m+1, sizeof(int));
|
alpar@1
|
615 |
mark = xcalloc(1+m+1, sizeof(int));
|
alpar@1
|
616 |
memset(&mark[0], 0, (m+1) * sizeof(int));
|
alpar@1
|
617 |
pass = xcalloc(1+m+1, sizeof(int));
|
alpar@1
|
618 |
memset(&pass[0], 0, (m+1) * sizeof(int));
|
alpar@1
|
619 |
val = xcalloc(1+n, sizeof(double));
|
alpar@1
|
620 |
lb = xcalloc(1+n, sizeof(double));
|
alpar@1
|
621 |
ub = xcalloc(1+n, sizeof(double));
|
alpar@1
|
622 |
/* initialize the list of rows to be processed */
|
alpar@1
|
623 |
size = 0;
|
alpar@1
|
624 |
for (k = 1; k <= nrs; k++)
|
alpar@1
|
625 |
{ i = num[k];
|
alpar@1
|
626 |
xassert(0 <= i && i <= m);
|
alpar@1
|
627 |
/* duplicate row numbers are not allowed */
|
alpar@1
|
628 |
xassert(!mark[i]);
|
alpar@1
|
629 |
list[++size] = i, mark[i] = 1;
|
alpar@1
|
630 |
}
|
alpar@1
|
631 |
xassert(size == nrs);
|
alpar@1
|
632 |
/* process rows in the list until it becomes empty */
|
alpar@1
|
633 |
while (size > 0)
|
alpar@1
|
634 |
{ /* get a next row from the list */
|
alpar@1
|
635 |
i = list[size--], mark[i] = 0;
|
alpar@1
|
636 |
/* increase the row processing count */
|
alpar@1
|
637 |
pass[i]++;
|
alpar@1
|
638 |
/* if the row is free, skip it */
|
alpar@1
|
639 |
if (L[i] == -DBL_MAX && U[i] == +DBL_MAX) continue;
|
alpar@1
|
640 |
/* obtain coefficients of the row */
|
alpar@1
|
641 |
len = 0;
|
alpar@1
|
642 |
if (i == 0)
|
alpar@1
|
643 |
{ for (j = 1; j <= n; j++)
|
alpar@1
|
644 |
{ GLPCOL *col = mip->col[j];
|
alpar@1
|
645 |
if (col->coef != 0.0)
|
alpar@1
|
646 |
len++, ind[len] = j, val[len] = col->coef;
|
alpar@1
|
647 |
}
|
alpar@1
|
648 |
}
|
alpar@1
|
649 |
else
|
alpar@1
|
650 |
{ GLPROW *row = mip->row[i];
|
alpar@1
|
651 |
GLPAIJ *aij;
|
alpar@1
|
652 |
for (aij = row->ptr; aij != NULL; aij = aij->r_next)
|
alpar@1
|
653 |
len++, ind[len] = aij->col->j, val[len] = aij->val;
|
alpar@1
|
654 |
}
|
alpar@1
|
655 |
/* determine lower and upper bounds of columns corresponding
|
alpar@1
|
656 |
to non-zero row coefficients */
|
alpar@1
|
657 |
for (k = 1; k <= len; k++)
|
alpar@1
|
658 |
j = ind[k], lb[k] = l[j], ub[k] = u[j];
|
alpar@1
|
659 |
/* prepare the row info to determine implied bounds */
|
alpar@1
|
660 |
prepare_row_info(len, val, lb, ub, &f);
|
alpar@1
|
661 |
/* check and relax bounds of the row */
|
alpar@1
|
662 |
if (check_row_bounds(&f, &L[i], &U[i]))
|
alpar@1
|
663 |
{ /* the feasible region is empty */
|
alpar@1
|
664 |
ret = 1;
|
alpar@1
|
665 |
goto done;
|
alpar@1
|
666 |
}
|
alpar@1
|
667 |
/* if the row became free, drop it */
|
alpar@1
|
668 |
if (L[i] == -DBL_MAX && U[i] == +DBL_MAX) continue;
|
alpar@1
|
669 |
/* process columns having non-zero coefficients in the row */
|
alpar@1
|
670 |
for (k = 1; k <= len; k++)
|
alpar@1
|
671 |
{ GLPCOL *col;
|
alpar@1
|
672 |
int flag, eff;
|
alpar@1
|
673 |
double ll, uu;
|
alpar@1
|
674 |
/* take a next column in the row */
|
alpar@1
|
675 |
j = ind[k], col = mip->col[j];
|
alpar@1
|
676 |
flag = col->kind != GLP_CV;
|
alpar@1
|
677 |
/* check and tighten bounds of the column */
|
alpar@1
|
678 |
if (check_col_bounds(&f, len, val, L[i], U[i], lb, ub,
|
alpar@1
|
679 |
flag, k, &ll, &uu))
|
alpar@1
|
680 |
{ /* the feasible region is empty */
|
alpar@1
|
681 |
ret = 1;
|
alpar@1
|
682 |
goto done;
|
alpar@1
|
683 |
}
|
alpar@1
|
684 |
/* check if change in the column bounds is efficient */
|
alpar@1
|
685 |
eff = check_efficiency(flag, l[j], u[j], ll, uu);
|
alpar@1
|
686 |
/* set new actual bounds of the column */
|
alpar@1
|
687 |
l[j] = ll, u[j] = uu;
|
alpar@1
|
688 |
/* if the change is efficient, add all rows affected by the
|
alpar@1
|
689 |
corresponding column, to the list */
|
alpar@1
|
690 |
if (eff > 0)
|
alpar@1
|
691 |
{ GLPAIJ *aij;
|
alpar@1
|
692 |
for (aij = col->ptr; aij != NULL; aij = aij->c_next)
|
alpar@1
|
693 |
{ int ii = aij->row->i;
|
alpar@1
|
694 |
/* if the row was processed maximal number of times,
|
alpar@1
|
695 |
skip it */
|
alpar@1
|
696 |
if (pass[ii] >= max_pass) continue;
|
alpar@1
|
697 |
/* if the row is free, skip it */
|
alpar@1
|
698 |
if (L[ii] == -DBL_MAX && U[ii] == +DBL_MAX) continue;
|
alpar@1
|
699 |
/* put the row into the list */
|
alpar@1
|
700 |
if (mark[ii] == 0)
|
alpar@1
|
701 |
{ xassert(size <= m);
|
alpar@1
|
702 |
list[++size] = ii, mark[ii] = 1;
|
alpar@1
|
703 |
}
|
alpar@1
|
704 |
}
|
alpar@1
|
705 |
}
|
alpar@1
|
706 |
}
|
alpar@1
|
707 |
}
|
alpar@1
|
708 |
done: /* free working arrays */
|
alpar@1
|
709 |
xfree(ind);
|
alpar@1
|
710 |
xfree(list);
|
alpar@1
|
711 |
xfree(mark);
|
alpar@1
|
712 |
xfree(pass);
|
alpar@1
|
713 |
xfree(val);
|
alpar@1
|
714 |
xfree(lb);
|
alpar@1
|
715 |
xfree(ub);
|
alpar@1
|
716 |
return ret;
|
alpar@1
|
717 |
}
|
alpar@1
|
718 |
|
alpar@1
|
719 |
/***********************************************************************
|
alpar@1
|
720 |
* NAME
|
alpar@1
|
721 |
*
|
alpar@1
|
722 |
* ios_preprocess_node - preprocess current subproblem
|
alpar@1
|
723 |
*
|
alpar@1
|
724 |
* SYNOPSIS
|
alpar@1
|
725 |
*
|
alpar@1
|
726 |
* #include "glpios.h"
|
alpar@1
|
727 |
* int ios_preprocess_node(glp_tree *tree, int max_pass);
|
alpar@1
|
728 |
*
|
alpar@1
|
729 |
* DESCRIPTION
|
alpar@1
|
730 |
*
|
alpar@1
|
731 |
* The routine ios_preprocess_node performs basic preprocessing of the
|
alpar@1
|
732 |
* current subproblem.
|
alpar@1
|
733 |
*
|
alpar@1
|
734 |
* RETURNS
|
alpar@1
|
735 |
*
|
alpar@1
|
736 |
* If no primal infeasibility is detected, the routine returns zero,
|
alpar@1
|
737 |
* otherwise non-zero. */
|
alpar@1
|
738 |
|
alpar@1
|
739 |
int ios_preprocess_node(glp_tree *tree, int max_pass)
|
alpar@1
|
740 |
{ glp_prob *mip = tree->mip;
|
alpar@1
|
741 |
int m = mip->m;
|
alpar@1
|
742 |
int n = mip->n;
|
alpar@1
|
743 |
int i, j, nrs, *num, ret = 0;
|
alpar@1
|
744 |
double *L, *U, *l, *u;
|
alpar@1
|
745 |
/* the current subproblem must exist */
|
alpar@1
|
746 |
xassert(tree->curr != NULL);
|
alpar@1
|
747 |
/* determine original row bounds */
|
alpar@1
|
748 |
L = xcalloc(1+m, sizeof(double));
|
alpar@1
|
749 |
U = xcalloc(1+m, sizeof(double));
|
alpar@1
|
750 |
switch (mip->mip_stat)
|
alpar@1
|
751 |
{ case GLP_UNDEF:
|
alpar@1
|
752 |
L[0] = -DBL_MAX, U[0] = +DBL_MAX;
|
alpar@1
|
753 |
break;
|
alpar@1
|
754 |
case GLP_FEAS:
|
alpar@1
|
755 |
switch (mip->dir)
|
alpar@1
|
756 |
{ case GLP_MIN:
|
alpar@1
|
757 |
L[0] = -DBL_MAX, U[0] = mip->mip_obj - mip->c0;
|
alpar@1
|
758 |
break;
|
alpar@1
|
759 |
case GLP_MAX:
|
alpar@1
|
760 |
L[0] = mip->mip_obj - mip->c0, U[0] = +DBL_MAX;
|
alpar@1
|
761 |
break;
|
alpar@1
|
762 |
default:
|
alpar@1
|
763 |
xassert(mip != mip);
|
alpar@1
|
764 |
}
|
alpar@1
|
765 |
break;
|
alpar@1
|
766 |
default:
|
alpar@1
|
767 |
xassert(mip != mip);
|
alpar@1
|
768 |
}
|
alpar@1
|
769 |
for (i = 1; i <= m; i++)
|
alpar@1
|
770 |
{ L[i] = glp_get_row_lb(mip, i);
|
alpar@1
|
771 |
U[i] = glp_get_row_ub(mip, i);
|
alpar@1
|
772 |
}
|
alpar@1
|
773 |
/* determine original column bounds */
|
alpar@1
|
774 |
l = xcalloc(1+n, sizeof(double));
|
alpar@1
|
775 |
u = xcalloc(1+n, sizeof(double));
|
alpar@1
|
776 |
for (j = 1; j <= n; j++)
|
alpar@1
|
777 |
{ l[j] = glp_get_col_lb(mip, j);
|
alpar@1
|
778 |
u[j] = glp_get_col_ub(mip, j);
|
alpar@1
|
779 |
}
|
alpar@1
|
780 |
/* build the initial list of rows to be analyzed */
|
alpar@1
|
781 |
nrs = m + 1;
|
alpar@1
|
782 |
num = xcalloc(1+nrs, sizeof(int));
|
alpar@1
|
783 |
for (i = 1; i <= nrs; i++) num[i] = i - 1;
|
alpar@1
|
784 |
/* perform basic preprocessing */
|
alpar@1
|
785 |
if (basic_preprocessing(mip , L, U, l, u, nrs, num, max_pass))
|
alpar@1
|
786 |
{ ret = 1;
|
alpar@1
|
787 |
goto done;
|
alpar@1
|
788 |
}
|
alpar@1
|
789 |
/* set new actual (relaxed) row bounds */
|
alpar@1
|
790 |
for (i = 1; i <= m; i++)
|
alpar@1
|
791 |
{ /* consider only non-active rows to keep dual feasibility */
|
alpar@1
|
792 |
if (glp_get_row_stat(mip, i) == GLP_BS)
|
alpar@1
|
793 |
{ if (L[i] == -DBL_MAX && U[i] == +DBL_MAX)
|
alpar@1
|
794 |
glp_set_row_bnds(mip, i, GLP_FR, 0.0, 0.0);
|
alpar@1
|
795 |
else if (U[i] == +DBL_MAX)
|
alpar@1
|
796 |
glp_set_row_bnds(mip, i, GLP_LO, L[i], 0.0);
|
alpar@1
|
797 |
else if (L[i] == -DBL_MAX)
|
alpar@1
|
798 |
glp_set_row_bnds(mip, i, GLP_UP, 0.0, U[i]);
|
alpar@1
|
799 |
}
|
alpar@1
|
800 |
}
|
alpar@1
|
801 |
/* set new actual (tightened) column bounds */
|
alpar@1
|
802 |
for (j = 1; j <= n; j++)
|
alpar@1
|
803 |
{ int type;
|
alpar@1
|
804 |
if (l[j] == -DBL_MAX && u[j] == +DBL_MAX)
|
alpar@1
|
805 |
type = GLP_FR;
|
alpar@1
|
806 |
else if (u[j] == +DBL_MAX)
|
alpar@1
|
807 |
type = GLP_LO;
|
alpar@1
|
808 |
else if (l[j] == -DBL_MAX)
|
alpar@1
|
809 |
type = GLP_UP;
|
alpar@1
|
810 |
else if (l[j] != u[j])
|
alpar@1
|
811 |
type = GLP_DB;
|
alpar@1
|
812 |
else
|
alpar@1
|
813 |
type = GLP_FX;
|
alpar@1
|
814 |
glp_set_col_bnds(mip, j, type, l[j], u[j]);
|
alpar@1
|
815 |
}
|
alpar@1
|
816 |
done: /* free working arrays and return */
|
alpar@1
|
817 |
xfree(L);
|
alpar@1
|
818 |
xfree(U);
|
alpar@1
|
819 |
xfree(l);
|
alpar@1
|
820 |
xfree(u);
|
alpar@1
|
821 |
xfree(num);
|
alpar@1
|
822 |
return ret;
|
alpar@1
|
823 |
}
|
alpar@1
|
824 |
|
alpar@1
|
825 |
/* eof */
|