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1 /* glpapi13.c (branch-and-bound interface routines) */
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2
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3 /***********************************************************************
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4 * This code is part of GLPK (GNU Linear Programming Kit).
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5 *
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6 * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008,
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7 * 2009, 2010, 2011 Andrew Makhorin, Department for Applied Informatics,
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8 * Moscow Aviation Institute, Moscow, Russia. All rights reserved.
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9 * E-mail: <mao@gnu.org>.
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10 *
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11 * GLPK is free software: you can redistribute it and/or modify it
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12 * under the terms of the GNU General Public License as published by
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13 * the Free Software Foundation, either version 3 of the License, or
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14 * (at your option) any later version.
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15 *
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16 * GLPK is distributed in the hope that it will be useful, but WITHOUT
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17 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
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18 * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
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19 * License for more details.
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20 *
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21 * You should have received a copy of the GNU General Public License
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22 * along with GLPK. If not, see <http://www.gnu.org/licenses/>.
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23 ***********************************************************************/
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24
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25 #include "glpios.h"
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26
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27 /***********************************************************************
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28 * NAME
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29 *
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30 * glp_ios_reason - determine reason for calling the callback routine
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31 *
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32 * SYNOPSIS
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33 *
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34 * glp_ios_reason(glp_tree *tree);
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35 *
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36 * RETURNS
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37 *
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38 * The routine glp_ios_reason returns a code, which indicates why the
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39 * user-defined callback routine is being called. */
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40
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41 int glp_ios_reason(glp_tree *tree)
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42 { return
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43 tree->reason;
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44 }
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45
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46 /***********************************************************************
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47 * NAME
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48 *
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49 * glp_ios_get_prob - access the problem object
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50 *
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51 * SYNOPSIS
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52 *
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53 * glp_prob *glp_ios_get_prob(glp_tree *tree);
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54 *
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55 * DESCRIPTION
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56 *
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57 * The routine glp_ios_get_prob can be called from the user-defined
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58 * callback routine to access the problem object, which is used by the
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59 * MIP solver. It is the original problem object passed to the routine
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60 * glp_intopt if the MIP presolver is not used; otherwise it is an
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61 * internal problem object built by the presolver. If the current
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62 * subproblem exists, LP segment of the problem object corresponds to
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63 * its LP relaxation.
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64 *
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65 * RETURNS
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66 *
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67 * The routine glp_ios_get_prob returns a pointer to the problem object
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68 * used by the MIP solver. */
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69
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70 glp_prob *glp_ios_get_prob(glp_tree *tree)
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71 { return
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72 tree->mip;
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73 }
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74
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75 /***********************************************************************
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76 * NAME
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77 *
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78 * glp_ios_tree_size - determine size of the branch-and-bound tree
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79 *
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80 * SYNOPSIS
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81 *
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82 * void glp_ios_tree_size(glp_tree *tree, int *a_cnt, int *n_cnt,
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83 * int *t_cnt);
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84 *
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85 * DESCRIPTION
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86 *
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87 * The routine glp_ios_tree_size stores the following three counts which
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88 * characterize the current size of the branch-and-bound tree:
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89 *
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90 * a_cnt is the current number of active nodes, i.e. the current size of
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91 * the active list;
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92 *
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93 * n_cnt is the current number of all (active and inactive) nodes;
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94 *
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95 * t_cnt is the total number of nodes including those which have been
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96 * already removed from the tree. This count is increased whenever
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97 * a new node appears in the tree and never decreased.
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98 *
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99 * If some of the parameters a_cnt, n_cnt, t_cnt is a null pointer, the
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100 * corresponding count is not stored. */
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101
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102 void glp_ios_tree_size(glp_tree *tree, int *a_cnt, int *n_cnt,
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103 int *t_cnt)
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104 { if (a_cnt != NULL) *a_cnt = tree->a_cnt;
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105 if (n_cnt != NULL) *n_cnt = tree->n_cnt;
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106 if (t_cnt != NULL) *t_cnt = tree->t_cnt;
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107 return;
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108 }
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109
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110 /***********************************************************************
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111 * NAME
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112 *
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113 * glp_ios_curr_node - determine current active subproblem
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114 *
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115 * SYNOPSIS
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116 *
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117 * int glp_ios_curr_node(glp_tree *tree);
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118 *
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119 * RETURNS
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120 *
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121 * The routine glp_ios_curr_node returns the reference number of the
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122 * current active subproblem. However, if the current subproblem does
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123 * not exist, the routine returns zero. */
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124
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125 int glp_ios_curr_node(glp_tree *tree)
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126 { IOSNPD *node;
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alpar@9
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127 /* obtain pointer to the current subproblem */
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128 node = tree->curr;
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129 /* return its reference number */
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130 return node == NULL ? 0 : node->p;
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131 }
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132
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133 /***********************************************************************
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134 * NAME
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135 *
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136 * glp_ios_next_node - determine next active subproblem
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137 *
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138 * SYNOPSIS
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alpar@9
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139 *
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140 * int glp_ios_next_node(glp_tree *tree, int p);
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alpar@9
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141 *
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142 * RETURNS
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143 *
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144 * If the parameter p is zero, the routine glp_ios_next_node returns
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145 * the reference number of the first active subproblem. However, if the
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146 * tree is empty, zero is returned.
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alpar@9
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147 *
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148 * If the parameter p is not zero, it must specify the reference number
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149 * of some active subproblem, in which case the routine returns the
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150 * reference number of the next active subproblem. However, if there is
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151 * no next active subproblem in the list, zero is returned.
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152 *
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153 * All subproblems in the active list are ordered chronologically, i.e.
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154 * subproblem A precedes subproblem B if A was created before B. */
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155
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156 int glp_ios_next_node(glp_tree *tree, int p)
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157 { IOSNPD *node;
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158 if (p == 0)
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alpar@9
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159 { /* obtain pointer to the first active subproblem */
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160 node = tree->head;
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161 }
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162 else
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163 { /* obtain pointer to the specified subproblem */
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164 if (!(1 <= p && p <= tree->nslots))
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165 err: xerror("glp_ios_next_node: p = %d; invalid subproblem refer"
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166 "ence number\n", p);
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167 node = tree->slot[p].node;
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168 if (node == NULL) goto err;
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169 /* the specified subproblem must be active */
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170 if (node->count != 0)
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171 xerror("glp_ios_next_node: p = %d; subproblem not in the ac"
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172 "tive list\n", p);
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alpar@9
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173 /* obtain pointer to the next active subproblem */
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174 node = node->next;
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175 }
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alpar@9
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176 /* return the reference number */
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177 return node == NULL ? 0 : node->p;
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178 }
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179
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180 /***********************************************************************
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alpar@9
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181 * NAME
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182 *
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183 * glp_ios_prev_node - determine previous active subproblem
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184 *
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185 * SYNOPSIS
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186 *
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187 * int glp_ios_prev_node(glp_tree *tree, int p);
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188 *
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189 * RETURNS
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190 *
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191 * If the parameter p is zero, the routine glp_ios_prev_node returns
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192 * the reference number of the last active subproblem. However, if the
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193 * tree is empty, zero is returned.
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alpar@9
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194 *
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195 * If the parameter p is not zero, it must specify the reference number
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196 * of some active subproblem, in which case the routine returns the
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197 * reference number of the previous active subproblem. However, if there
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198 * is no previous active subproblem in the list, zero is returned.
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199 *
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200 * All subproblems in the active list are ordered chronologically, i.e.
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201 * subproblem A precedes subproblem B if A was created before B. */
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202
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203 int glp_ios_prev_node(glp_tree *tree, int p)
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204 { IOSNPD *node;
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205 if (p == 0)
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alpar@9
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206 { /* obtain pointer to the last active subproblem */
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207 node = tree->tail;
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208 }
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209 else
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210 { /* obtain pointer to the specified subproblem */
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211 if (!(1 <= p && p <= tree->nslots))
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212 err: xerror("glp_ios_prev_node: p = %d; invalid subproblem refer"
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213 "ence number\n", p);
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214 node = tree->slot[p].node;
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215 if (node == NULL) goto err;
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216 /* the specified subproblem must be active */
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217 if (node->count != 0)
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218 xerror("glp_ios_prev_node: p = %d; subproblem not in the ac"
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219 "tive list\n", p);
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220 /* obtain pointer to the previous active subproblem */
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221 node = node->prev;
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222 }
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alpar@9
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223 /* return the reference number */
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224 return node == NULL ? 0 : node->p;
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225 }
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226
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227 /***********************************************************************
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228 * NAME
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alpar@9
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229 *
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230 * glp_ios_up_node - determine parent subproblem
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231 *
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232 * SYNOPSIS
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alpar@9
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233 *
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234 * int glp_ios_up_node(glp_tree *tree, int p);
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235 *
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236 * RETURNS
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237 *
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238 * The parameter p must specify the reference number of some (active or
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239 * inactive) subproblem, in which case the routine iet_get_up_node
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240 * returns the reference number of its parent subproblem. However, if
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241 * the specified subproblem is the root of the tree and, therefore, has
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242 * no parent, the routine returns zero. */
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243
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244 int glp_ios_up_node(glp_tree *tree, int p)
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245 { IOSNPD *node;
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alpar@9
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246 /* obtain pointer to the specified subproblem */
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alpar@9
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247 if (!(1 <= p && p <= tree->nslots))
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248 err: xerror("glp_ios_up_node: p = %d; invalid subproblem reference "
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alpar@9
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249 "number\n", p);
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250 node = tree->slot[p].node;
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251 if (node == NULL) goto err;
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alpar@9
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252 /* obtain pointer to the parent subproblem */
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253 node = node->up;
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alpar@9
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254 /* return the reference number */
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255 return node == NULL ? 0 : node->p;
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alpar@9
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256 }
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257
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alpar@9
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258 /***********************************************************************
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alpar@9
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259 * NAME
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alpar@9
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260 *
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alpar@9
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261 * glp_ios_node_level - determine subproblem level
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alpar@9
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262 *
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alpar@9
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263 * SYNOPSIS
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alpar@9
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264 *
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265 * int glp_ios_node_level(glp_tree *tree, int p);
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alpar@9
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266 *
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267 * RETURNS
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alpar@9
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268 *
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alpar@9
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269 * The routine glp_ios_node_level returns the level of the subproblem,
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270 * whose reference number is p, in the branch-and-bound tree. (The root
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271 * subproblem has level 0, and the level of any other subproblem is the
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272 * level of its parent plus one.) */
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273
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274 int glp_ios_node_level(glp_tree *tree, int p)
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alpar@9
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275 { IOSNPD *node;
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alpar@9
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276 /* obtain pointer to the specified subproblem */
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alpar@9
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277 if (!(1 <= p && p <= tree->nslots))
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278 err: xerror("glp_ios_node_level: p = %d; invalid subproblem referen"
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alpar@9
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279 "ce number\n", p);
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280 node = tree->slot[p].node;
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alpar@9
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281 if (node == NULL) goto err;
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alpar@9
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282 /* return the node level */
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alpar@9
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283 return node->level;
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alpar@9
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284 }
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alpar@9
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285
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alpar@9
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286 /***********************************************************************
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alpar@9
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287 * NAME
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alpar@9
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288 *
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alpar@9
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289 * glp_ios_node_bound - determine subproblem local bound
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alpar@9
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290 *
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alpar@9
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291 * SYNOPSIS
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alpar@9
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292 *
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alpar@9
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293 * double glp_ios_node_bound(glp_tree *tree, int p);
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alpar@9
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294 *
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alpar@9
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295 * RETURNS
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alpar@9
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296 *
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alpar@9
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297 * The routine glp_ios_node_bound returns the local bound for (active or
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alpar@9
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298 * inactive) subproblem, whose reference number is p.
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alpar@9
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299 *
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alpar@9
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300 * COMMENTS
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alpar@9
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301 *
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alpar@9
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302 * The local bound for subproblem p is an lower (minimization) or upper
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alpar@9
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303 * (maximization) bound for integer optimal solution to this subproblem
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alpar@9
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304 * (not to the original problem). This bound is local in the sense that
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alpar@9
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305 * only subproblems in the subtree rooted at node p cannot have better
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alpar@9
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306 * integer feasible solutions.
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alpar@9
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307 *
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alpar@9
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308 * On creating a subproblem (due to the branching step) its local bound
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alpar@9
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309 * is inherited from its parent and then may get only stronger (never
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alpar@9
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310 * weaker). For the root subproblem its local bound is initially set to
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alpar@9
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311 * -DBL_MAX (minimization) or +DBL_MAX (maximization) and then improved
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alpar@9
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312 * as the root LP relaxation has been solved.
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alpar@9
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313 *
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alpar@9
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314 * Note that the local bound is not necessarily the optimal objective
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alpar@9
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315 * value to corresponding LP relaxation; it may be stronger. */
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alpar@9
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316
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alpar@9
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317 double glp_ios_node_bound(glp_tree *tree, int p)
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alpar@9
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318 { IOSNPD *node;
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alpar@9
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319 /* obtain pointer to the specified subproblem */
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alpar@9
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320 if (!(1 <= p && p <= tree->nslots))
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alpar@9
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321 err: xerror("glp_ios_node_bound: p = %d; invalid subproblem referen"
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alpar@9
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322 "ce number\n", p);
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alpar@9
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323 node = tree->slot[p].node;
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alpar@9
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324 if (node == NULL) goto err;
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alpar@9
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325 /* return the node local bound */
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alpar@9
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326 return node->bound;
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alpar@9
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327 }
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alpar@9
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328
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alpar@9
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329 /***********************************************************************
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alpar@9
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330 * NAME
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alpar@9
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331 *
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alpar@9
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332 * glp_ios_best_node - find active subproblem with best local bound
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alpar@9
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333 *
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alpar@9
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334 * SYNOPSIS
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alpar@9
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335 *
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alpar@9
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336 * int glp_ios_best_node(glp_tree *tree);
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alpar@9
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337 *
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alpar@9
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338 * RETURNS
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alpar@9
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339 *
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alpar@9
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340 * The routine glp_ios_best_node returns the reference number of the
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alpar@9
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341 * active subproblem, whose local bound is best (i.e. smallest in case
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alpar@9
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342 * of minimization or largest in case of maximization). However, if the
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alpar@9
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343 * tree is empty, the routine returns zero.
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alpar@9
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344 *
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alpar@9
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345 * COMMENTS
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alpar@9
|
346 *
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alpar@9
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347 * The best local bound is an lower (minimization) or upper
|
alpar@9
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348 * (maximization) bound for integer optimal solution to the original
|
alpar@9
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349 * MIP problem. */
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alpar@9
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350
|
alpar@9
|
351 int glp_ios_best_node(glp_tree *tree)
|
alpar@9
|
352 { return
|
alpar@9
|
353 ios_best_node(tree);
|
alpar@9
|
354 }
|
alpar@9
|
355
|
alpar@9
|
356 /***********************************************************************
|
alpar@9
|
357 * NAME
|
alpar@9
|
358 *
|
alpar@9
|
359 * glp_ios_mip_gap - compute relative MIP gap
|
alpar@9
|
360 *
|
alpar@9
|
361 * SYNOPSIS
|
alpar@9
|
362 *
|
alpar@9
|
363 * double glp_ios_mip_gap(glp_tree *tree);
|
alpar@9
|
364 *
|
alpar@9
|
365 * DESCRIPTION
|
alpar@9
|
366 *
|
alpar@9
|
367 * The routine glp_ios_mip_gap computes the relative MIP gap with the
|
alpar@9
|
368 * following formula:
|
alpar@9
|
369 *
|
alpar@9
|
370 * gap = |best_mip - best_bnd| / (|best_mip| + DBL_EPSILON),
|
alpar@9
|
371 *
|
alpar@9
|
372 * where best_mip is the best integer feasible solution found so far,
|
alpar@9
|
373 * best_bnd is the best (global) bound. If no integer feasible solution
|
alpar@9
|
374 * has been found yet, gap is set to DBL_MAX.
|
alpar@9
|
375 *
|
alpar@9
|
376 * RETURNS
|
alpar@9
|
377 *
|
alpar@9
|
378 * The routine glp_ios_mip_gap returns the relative MIP gap. */
|
alpar@9
|
379
|
alpar@9
|
380 double glp_ios_mip_gap(glp_tree *tree)
|
alpar@9
|
381 { return
|
alpar@9
|
382 ios_relative_gap(tree);
|
alpar@9
|
383 }
|
alpar@9
|
384
|
alpar@9
|
385 /***********************************************************************
|
alpar@9
|
386 * NAME
|
alpar@9
|
387 *
|
alpar@9
|
388 * glp_ios_node_data - access subproblem application-specific data
|
alpar@9
|
389 *
|
alpar@9
|
390 * SYNOPSIS
|
alpar@9
|
391 *
|
alpar@9
|
392 * void *glp_ios_node_data(glp_tree *tree, int p);
|
alpar@9
|
393 *
|
alpar@9
|
394 * DESCRIPTION
|
alpar@9
|
395 *
|
alpar@9
|
396 * The routine glp_ios_node_data allows the application accessing a
|
alpar@9
|
397 * memory block allocated for the subproblem (which may be active or
|
alpar@9
|
398 * inactive), whose reference number is p.
|
alpar@9
|
399 *
|
alpar@9
|
400 * The size of the block is defined by the control parameter cb_size
|
alpar@9
|
401 * passed to the routine glp_intopt. The block is initialized by binary
|
alpar@9
|
402 * zeros on creating corresponding subproblem, and its contents is kept
|
alpar@9
|
403 * until the subproblem will be removed from the tree.
|
alpar@9
|
404 *
|
alpar@9
|
405 * The application may use these memory blocks to store specific data
|
alpar@9
|
406 * for each subproblem.
|
alpar@9
|
407 *
|
alpar@9
|
408 * RETURNS
|
alpar@9
|
409 *
|
alpar@9
|
410 * The routine glp_ios_node_data returns a pointer to the memory block
|
alpar@9
|
411 * for the specified subproblem. Note that if cb_size = 0, the routine
|
alpar@9
|
412 * returns a null pointer. */
|
alpar@9
|
413
|
alpar@9
|
414 void *glp_ios_node_data(glp_tree *tree, int p)
|
alpar@9
|
415 { IOSNPD *node;
|
alpar@9
|
416 /* obtain pointer to the specified subproblem */
|
alpar@9
|
417 if (!(1 <= p && p <= tree->nslots))
|
alpar@9
|
418 err: xerror("glp_ios_node_level: p = %d; invalid subproblem referen"
|
alpar@9
|
419 "ce number\n", p);
|
alpar@9
|
420 node = tree->slot[p].node;
|
alpar@9
|
421 if (node == NULL) goto err;
|
alpar@9
|
422 /* return pointer to the application-specific data */
|
alpar@9
|
423 return node->data;
|
alpar@9
|
424 }
|
alpar@9
|
425
|
alpar@9
|
426 /***********************************************************************
|
alpar@9
|
427 * NAME
|
alpar@9
|
428 *
|
alpar@9
|
429 * glp_ios_row_attr - retrieve additional row attributes
|
alpar@9
|
430 *
|
alpar@9
|
431 * SYNOPSIS
|
alpar@9
|
432 *
|
alpar@9
|
433 * void glp_ios_row_attr(glp_tree *tree, int i, glp_attr *attr);
|
alpar@9
|
434 *
|
alpar@9
|
435 * DESCRIPTION
|
alpar@9
|
436 *
|
alpar@9
|
437 * The routine glp_ios_row_attr retrieves additional attributes of row
|
alpar@9
|
438 * i and stores them in the structure glp_attr. */
|
alpar@9
|
439
|
alpar@9
|
440 void glp_ios_row_attr(glp_tree *tree, int i, glp_attr *attr)
|
alpar@9
|
441 { GLPROW *row;
|
alpar@9
|
442 if (!(1 <= i && i <= tree->mip->m))
|
alpar@9
|
443 xerror("glp_ios_row_attr: i = %d; row number out of range\n",
|
alpar@9
|
444 i);
|
alpar@9
|
445 row = tree->mip->row[i];
|
alpar@9
|
446 attr->level = row->level;
|
alpar@9
|
447 attr->origin = row->origin;
|
alpar@9
|
448 attr->klass = row->klass;
|
alpar@9
|
449 return;
|
alpar@9
|
450 }
|
alpar@9
|
451
|
alpar@9
|
452 /**********************************************************************/
|
alpar@9
|
453
|
alpar@9
|
454 int glp_ios_pool_size(glp_tree *tree)
|
alpar@9
|
455 { /* determine current size of the cut pool */
|
alpar@9
|
456 if (tree->reason != GLP_ICUTGEN)
|
alpar@9
|
457 xerror("glp_ios_pool_size: operation not allowed\n");
|
alpar@9
|
458 xassert(tree->local != NULL);
|
alpar@9
|
459 return tree->local->size;
|
alpar@9
|
460 }
|
alpar@9
|
461
|
alpar@9
|
462 /**********************************************************************/
|
alpar@9
|
463
|
alpar@9
|
464 int glp_ios_add_row(glp_tree *tree,
|
alpar@9
|
465 const char *name, int klass, int flags, int len, const int ind[],
|
alpar@9
|
466 const double val[], int type, double rhs)
|
alpar@9
|
467 { /* add row (constraint) to the cut pool */
|
alpar@9
|
468 int num;
|
alpar@9
|
469 if (tree->reason != GLP_ICUTGEN)
|
alpar@9
|
470 xerror("glp_ios_add_row: operation not allowed\n");
|
alpar@9
|
471 xassert(tree->local != NULL);
|
alpar@9
|
472 num = ios_add_row(tree, tree->local, name, klass, flags, len,
|
alpar@9
|
473 ind, val, type, rhs);
|
alpar@9
|
474 return num;
|
alpar@9
|
475 }
|
alpar@9
|
476
|
alpar@9
|
477 /**********************************************************************/
|
alpar@9
|
478
|
alpar@9
|
479 void glp_ios_del_row(glp_tree *tree, int i)
|
alpar@9
|
480 { /* remove row (constraint) from the cut pool */
|
alpar@9
|
481 if (tree->reason != GLP_ICUTGEN)
|
alpar@9
|
482 xerror("glp_ios_del_row: operation not allowed\n");
|
alpar@9
|
483 ios_del_row(tree, tree->local, i);
|
alpar@9
|
484 return;
|
alpar@9
|
485 }
|
alpar@9
|
486
|
alpar@9
|
487 /**********************************************************************/
|
alpar@9
|
488
|
alpar@9
|
489 void glp_ios_clear_pool(glp_tree *tree)
|
alpar@9
|
490 { /* remove all rows (constraints) from the cut pool */
|
alpar@9
|
491 if (tree->reason != GLP_ICUTGEN)
|
alpar@9
|
492 xerror("glp_ios_clear_pool: operation not allowed\n");
|
alpar@9
|
493 ios_clear_pool(tree, tree->local);
|
alpar@9
|
494 return;
|
alpar@9
|
495 }
|
alpar@9
|
496
|
alpar@9
|
497 /***********************************************************************
|
alpar@9
|
498 * NAME
|
alpar@9
|
499 *
|
alpar@9
|
500 * glp_ios_can_branch - check if can branch upon specified variable
|
alpar@9
|
501 *
|
alpar@9
|
502 * SYNOPSIS
|
alpar@9
|
503 *
|
alpar@9
|
504 * int glp_ios_can_branch(glp_tree *tree, int j);
|
alpar@9
|
505 *
|
alpar@9
|
506 * RETURNS
|
alpar@9
|
507 *
|
alpar@9
|
508 * If j-th variable (column) can be used to branch upon, the routine
|
alpar@9
|
509 * glp_ios_can_branch returns non-zero, otherwise zero. */
|
alpar@9
|
510
|
alpar@9
|
511 int glp_ios_can_branch(glp_tree *tree, int j)
|
alpar@9
|
512 { if (!(1 <= j && j <= tree->mip->n))
|
alpar@9
|
513 xerror("glp_ios_can_branch: j = %d; column number out of range"
|
alpar@9
|
514 "\n", j);
|
alpar@9
|
515 return tree->non_int[j];
|
alpar@9
|
516 }
|
alpar@9
|
517
|
alpar@9
|
518 /***********************************************************************
|
alpar@9
|
519 * NAME
|
alpar@9
|
520 *
|
alpar@9
|
521 * glp_ios_branch_upon - choose variable to branch upon
|
alpar@9
|
522 *
|
alpar@9
|
523 * SYNOPSIS
|
alpar@9
|
524 *
|
alpar@9
|
525 * void glp_ios_branch_upon(glp_tree *tree, int j, int sel);
|
alpar@9
|
526 *
|
alpar@9
|
527 * DESCRIPTION
|
alpar@9
|
528 *
|
alpar@9
|
529 * The routine glp_ios_branch_upon can be called from the user-defined
|
alpar@9
|
530 * callback routine in response to the reason GLP_IBRANCH to choose a
|
alpar@9
|
531 * branching variable, whose ordinal number is j. Should note that only
|
alpar@9
|
532 * variables, for which the routine glp_ios_can_branch returns non-zero,
|
alpar@9
|
533 * can be used to branch upon.
|
alpar@9
|
534 *
|
alpar@9
|
535 * The parameter sel is a flag that indicates which branch (subproblem)
|
alpar@9
|
536 * should be selected next to continue the search:
|
alpar@9
|
537 *
|
alpar@9
|
538 * GLP_DN_BRNCH - select down-branch;
|
alpar@9
|
539 * GLP_UP_BRNCH - select up-branch;
|
alpar@9
|
540 * GLP_NO_BRNCH - use general selection technique. */
|
alpar@9
|
541
|
alpar@9
|
542 void glp_ios_branch_upon(glp_tree *tree, int j, int sel)
|
alpar@9
|
543 { if (!(1 <= j && j <= tree->mip->n))
|
alpar@9
|
544 xerror("glp_ios_branch_upon: j = %d; column number out of rang"
|
alpar@9
|
545 "e\n", j);
|
alpar@9
|
546 if (!(sel == GLP_DN_BRNCH || sel == GLP_UP_BRNCH ||
|
alpar@9
|
547 sel == GLP_NO_BRNCH))
|
alpar@9
|
548 xerror("glp_ios_branch_upon: sel = %d: invalid branch selectio"
|
alpar@9
|
549 "n flag\n", sel);
|
alpar@9
|
550 if (!(tree->non_int[j]))
|
alpar@9
|
551 xerror("glp_ios_branch_upon: j = %d; variable cannot be used t"
|
alpar@9
|
552 "o branch upon\n", j);
|
alpar@9
|
553 if (tree->br_var != 0)
|
alpar@9
|
554 xerror("glp_ios_branch_upon: branching variable already chosen"
|
alpar@9
|
555 "\n");
|
alpar@9
|
556 tree->br_var = j;
|
alpar@9
|
557 tree->br_sel = sel;
|
alpar@9
|
558 return;
|
alpar@9
|
559 }
|
alpar@9
|
560
|
alpar@9
|
561 /***********************************************************************
|
alpar@9
|
562 * NAME
|
alpar@9
|
563 *
|
alpar@9
|
564 * glp_ios_select_node - select subproblem to continue the search
|
alpar@9
|
565 *
|
alpar@9
|
566 * SYNOPSIS
|
alpar@9
|
567 *
|
alpar@9
|
568 * void glp_ios_select_node(glp_tree *tree, int p);
|
alpar@9
|
569 *
|
alpar@9
|
570 * DESCRIPTION
|
alpar@9
|
571 *
|
alpar@9
|
572 * The routine glp_ios_select_node can be called from the user-defined
|
alpar@9
|
573 * callback routine in response to the reason GLP_ISELECT to select an
|
alpar@9
|
574 * active subproblem, whose reference number is p. The search will be
|
alpar@9
|
575 * continued from the subproblem selected. */
|
alpar@9
|
576
|
alpar@9
|
577 void glp_ios_select_node(glp_tree *tree, int p)
|
alpar@9
|
578 { IOSNPD *node;
|
alpar@9
|
579 /* obtain pointer to the specified subproblem */
|
alpar@9
|
580 if (!(1 <= p && p <= tree->nslots))
|
alpar@9
|
581 err: xerror("glp_ios_select_node: p = %d; invalid subproblem refere"
|
alpar@9
|
582 "nce number\n", p);
|
alpar@9
|
583 node = tree->slot[p].node;
|
alpar@9
|
584 if (node == NULL) goto err;
|
alpar@9
|
585 /* the specified subproblem must be active */
|
alpar@9
|
586 if (node->count != 0)
|
alpar@9
|
587 xerror("glp_ios_select_node: p = %d; subproblem not in the act"
|
alpar@9
|
588 "ive list\n", p);
|
alpar@9
|
589 /* no subproblem must be selected yet */
|
alpar@9
|
590 if (tree->next_p != 0)
|
alpar@9
|
591 xerror("glp_ios_select_node: subproblem already selected\n");
|
alpar@9
|
592 /* select the specified subproblem to continue the search */
|
alpar@9
|
593 tree->next_p = p;
|
alpar@9
|
594 return;
|
alpar@9
|
595 }
|
alpar@9
|
596
|
alpar@9
|
597 /***********************************************************************
|
alpar@9
|
598 * NAME
|
alpar@9
|
599 *
|
alpar@9
|
600 * glp_ios_heur_sol - provide solution found by heuristic
|
alpar@9
|
601 *
|
alpar@9
|
602 * SYNOPSIS
|
alpar@9
|
603 *
|
alpar@9
|
604 * int glp_ios_heur_sol(glp_tree *tree, const double x[]);
|
alpar@9
|
605 *
|
alpar@9
|
606 * DESCRIPTION
|
alpar@9
|
607 *
|
alpar@9
|
608 * The routine glp_ios_heur_sol can be called from the user-defined
|
alpar@9
|
609 * callback routine in response to the reason GLP_IHEUR to provide an
|
alpar@9
|
610 * integer feasible solution found by a primal heuristic.
|
alpar@9
|
611 *
|
alpar@9
|
612 * Primal values of *all* variables (columns) found by the heuristic
|
alpar@9
|
613 * should be placed in locations x[1], ..., x[n], where n is the number
|
alpar@9
|
614 * of columns in the original problem object. Note that the routine
|
alpar@9
|
615 * glp_ios_heur_sol *does not* check primal feasibility of the solution
|
alpar@9
|
616 * provided.
|
alpar@9
|
617 *
|
alpar@9
|
618 * Using the solution passed in the array x the routine computes value
|
alpar@9
|
619 * of the objective function. If the objective value is better than the
|
alpar@9
|
620 * best known integer feasible solution, the routine computes values of
|
alpar@9
|
621 * auxiliary variables (rows) and stores all solution components in the
|
alpar@9
|
622 * problem object.
|
alpar@9
|
623 *
|
alpar@9
|
624 * RETURNS
|
alpar@9
|
625 *
|
alpar@9
|
626 * If the provided solution is accepted, the routine glp_ios_heur_sol
|
alpar@9
|
627 * returns zero. Otherwise, if the provided solution is rejected, the
|
alpar@9
|
628 * routine returns non-zero. */
|
alpar@9
|
629
|
alpar@9
|
630 int glp_ios_heur_sol(glp_tree *tree, const double x[])
|
alpar@9
|
631 { glp_prob *mip = tree->mip;
|
alpar@9
|
632 int m = tree->orig_m;
|
alpar@9
|
633 int n = tree->n;
|
alpar@9
|
634 int i, j;
|
alpar@9
|
635 double obj;
|
alpar@9
|
636 xassert(mip->m >= m);
|
alpar@9
|
637 xassert(mip->n == n);
|
alpar@9
|
638 /* check values of integer variables and compute value of the
|
alpar@9
|
639 objective function */
|
alpar@9
|
640 obj = mip->c0;
|
alpar@9
|
641 for (j = 1; j <= n; j++)
|
alpar@9
|
642 { GLPCOL *col = mip->col[j];
|
alpar@9
|
643 if (col->kind == GLP_IV)
|
alpar@9
|
644 { /* provided value must be integral */
|
alpar@9
|
645 if (x[j] != floor(x[j])) return 1;
|
alpar@9
|
646 }
|
alpar@9
|
647 obj += col->coef * x[j];
|
alpar@9
|
648 }
|
alpar@9
|
649 /* check if the provided solution is better than the best known
|
alpar@9
|
650 integer feasible solution */
|
alpar@9
|
651 if (mip->mip_stat == GLP_FEAS)
|
alpar@9
|
652 { switch (mip->dir)
|
alpar@9
|
653 { case GLP_MIN:
|
alpar@9
|
654 if (obj >= tree->mip->mip_obj) return 1;
|
alpar@9
|
655 break;
|
alpar@9
|
656 case GLP_MAX:
|
alpar@9
|
657 if (obj <= tree->mip->mip_obj) return 1;
|
alpar@9
|
658 break;
|
alpar@9
|
659 default:
|
alpar@9
|
660 xassert(mip != mip);
|
alpar@9
|
661 }
|
alpar@9
|
662 }
|
alpar@9
|
663 /* it is better; store it in the problem object */
|
alpar@9
|
664 if (tree->parm->msg_lev >= GLP_MSG_ON)
|
alpar@9
|
665 xprintf("Solution found by heuristic: %.12g\n", obj);
|
alpar@9
|
666 mip->mip_stat = GLP_FEAS;
|
alpar@9
|
667 mip->mip_obj = obj;
|
alpar@9
|
668 for (j = 1; j <= n; j++)
|
alpar@9
|
669 mip->col[j]->mipx = x[j];
|
alpar@9
|
670 for (i = 1; i <= m; i++)
|
alpar@9
|
671 { GLPROW *row = mip->row[i];
|
alpar@9
|
672 GLPAIJ *aij;
|
alpar@9
|
673 row->mipx = 0.0;
|
alpar@9
|
674 for (aij = row->ptr; aij != NULL; aij = aij->r_next)
|
alpar@9
|
675 row->mipx += aij->val * aij->col->mipx;
|
alpar@9
|
676 }
|
alpar@9
|
677 return 0;
|
alpar@9
|
678 }
|
alpar@9
|
679
|
alpar@9
|
680 /***********************************************************************
|
alpar@9
|
681 * NAME
|
alpar@9
|
682 *
|
alpar@9
|
683 * glp_ios_terminate - terminate the solution process.
|
alpar@9
|
684 *
|
alpar@9
|
685 * SYNOPSIS
|
alpar@9
|
686 *
|
alpar@9
|
687 * void glp_ios_terminate(glp_tree *tree);
|
alpar@9
|
688 *
|
alpar@9
|
689 * DESCRIPTION
|
alpar@9
|
690 *
|
alpar@9
|
691 * The routine glp_ios_terminate sets a flag indicating that the MIP
|
alpar@9
|
692 * solver should prematurely terminate the search. */
|
alpar@9
|
693
|
alpar@9
|
694 void glp_ios_terminate(glp_tree *tree)
|
alpar@9
|
695 { if (tree->parm->msg_lev >= GLP_MSG_DBG)
|
alpar@9
|
696 xprintf("The search is prematurely terminated due to applicati"
|
alpar@9
|
697 "on request\n");
|
alpar@9
|
698 tree->stop = 1;
|
alpar@9
|
699 return;
|
alpar@9
|
700 }
|
alpar@9
|
701
|
alpar@9
|
702 /* eof */
|