1 | /* glpapi06.c (simplex method 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 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 | #include "glpnpp.h" |
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27 | #include "glpspx.h" |
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28 | |
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29 | /*********************************************************************** |
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30 | * NAME |
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31 | * |
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32 | * glp_simplex - solve LP problem with the simplex method |
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33 | * |
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34 | * SYNOPSIS |
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35 | * |
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36 | * int glp_simplex(glp_prob *P, const glp_smcp *parm); |
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37 | * |
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38 | * DESCRIPTION |
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39 | * |
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40 | * The routine glp_simplex is a driver to the LP solver based on the |
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41 | * simplex method. This routine retrieves problem data from the |
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42 | * specified problem object, calls the solver to solve the problem |
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43 | * instance, and stores results of computations back into the problem |
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44 | * object. |
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45 | * |
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46 | * The simplex solver has a set of control parameters. Values of the |
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47 | * control parameters can be passed in a structure glp_smcp, which the |
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48 | * parameter parm points to. |
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49 | * |
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50 | * The parameter parm can be specified as NULL, in which case the LP |
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51 | * solver uses default settings. |
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52 | * |
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53 | * RETURNS |
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54 | * |
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55 | * 0 The LP problem instance has been successfully solved. This code |
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56 | * does not necessarily mean that the solver has found optimal |
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57 | * solution. It only means that the solution process was successful. |
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58 | * |
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59 | * GLP_EBADB |
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60 | * Unable to start the search, because the initial basis specified |
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61 | * in the problem object is invalid--the number of basic (auxiliary |
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62 | * and structural) variables is not the same as the number of rows in |
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63 | * the problem object. |
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64 | * |
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65 | * GLP_ESING |
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66 | * Unable to start the search, because the basis matrix correspodning |
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67 | * to the initial basis is singular within the working precision. |
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68 | * |
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69 | * GLP_ECOND |
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70 | * Unable to start the search, because the basis matrix correspodning |
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71 | * to the initial basis is ill-conditioned, i.e. its condition number |
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72 | * is too large. |
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73 | * |
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74 | * GLP_EBOUND |
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75 | * Unable to start the search, because some double-bounded variables |
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76 | * have incorrect bounds. |
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77 | * |
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78 | * GLP_EFAIL |
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79 | * The search was prematurely terminated due to the solver failure. |
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80 | * |
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81 | * GLP_EOBJLL |
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82 | * The search was prematurely terminated, because the objective |
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83 | * function being maximized has reached its lower limit and continues |
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84 | * decreasing (dual simplex only). |
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85 | * |
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86 | * GLP_EOBJUL |
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87 | * The search was prematurely terminated, because the objective |
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88 | * function being minimized has reached its upper limit and continues |
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89 | * increasing (dual simplex only). |
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90 | * |
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91 | * GLP_EITLIM |
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92 | * The search was prematurely terminated, because the simplex |
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93 | * iteration limit has been exceeded. |
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94 | * |
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95 | * GLP_ETMLIM |
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96 | * The search was prematurely terminated, because the time limit has |
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97 | * been exceeded. |
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98 | * |
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99 | * GLP_ENOPFS |
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100 | * The LP problem instance has no primal feasible solution (only if |
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101 | * the LP presolver is used). |
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102 | * |
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103 | * GLP_ENODFS |
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104 | * The LP problem instance has no dual feasible solution (only if the |
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105 | * LP presolver is used). */ |
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106 | |
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107 | static void trivial_lp(glp_prob *P, const glp_smcp *parm) |
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108 | { /* solve trivial LP which has empty constraint matrix */ |
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109 | GLPROW *row; |
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110 | GLPCOL *col; |
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111 | int i, j; |
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112 | double p_infeas, d_infeas, zeta; |
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113 | P->valid = 0; |
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114 | P->pbs_stat = P->dbs_stat = GLP_FEAS; |
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115 | P->obj_val = P->c0; |
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116 | P->some = 0; |
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117 | p_infeas = d_infeas = 0.0; |
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118 | /* make all auxiliary variables basic */ |
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119 | for (i = 1; i <= P->m; i++) |
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120 | { row = P->row[i]; |
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121 | row->stat = GLP_BS; |
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122 | row->prim = row->dual = 0.0; |
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123 | /* check primal feasibility */ |
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124 | if (row->type == GLP_LO || row->type == GLP_DB || |
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125 | row->type == GLP_FX) |
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126 | { /* row has lower bound */ |
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127 | if (row->lb > + parm->tol_bnd) |
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128 | { P->pbs_stat = GLP_NOFEAS; |
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129 | if (P->some == 0 && parm->meth != GLP_PRIMAL) |
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130 | P->some = i; |
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131 | } |
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132 | if (p_infeas < + row->lb) |
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133 | p_infeas = + row->lb; |
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134 | } |
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135 | if (row->type == GLP_UP || row->type == GLP_DB || |
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136 | row->type == GLP_FX) |
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137 | { /* row has upper bound */ |
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138 | if (row->ub < - parm->tol_bnd) |
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139 | { P->pbs_stat = GLP_NOFEAS; |
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140 | if (P->some == 0 && parm->meth != GLP_PRIMAL) |
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141 | P->some = i; |
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142 | } |
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143 | if (p_infeas < - row->ub) |
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144 | p_infeas = - row->ub; |
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145 | } |
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146 | } |
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147 | /* determine scale factor for the objective row */ |
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148 | zeta = 1.0; |
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149 | for (j = 1; j <= P->n; j++) |
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150 | { col = P->col[j]; |
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151 | if (zeta < fabs(col->coef)) zeta = fabs(col->coef); |
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152 | } |
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153 | zeta = (P->dir == GLP_MIN ? +1.0 : -1.0) / zeta; |
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154 | /* make all structural variables non-basic */ |
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155 | for (j = 1; j <= P->n; j++) |
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156 | { col = P->col[j]; |
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157 | if (col->type == GLP_FR) |
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158 | col->stat = GLP_NF, col->prim = 0.0; |
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159 | else if (col->type == GLP_LO) |
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160 | lo: col->stat = GLP_NL, col->prim = col->lb; |
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161 | else if (col->type == GLP_UP) |
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162 | up: col->stat = GLP_NU, col->prim = col->ub; |
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163 | else if (col->type == GLP_DB) |
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164 | { if (zeta * col->coef > 0.0) |
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165 | goto lo; |
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166 | else if (zeta * col->coef < 0.0) |
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167 | goto up; |
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168 | else if (fabs(col->lb) <= fabs(col->ub)) |
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169 | goto lo; |
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170 | else |
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171 | goto up; |
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172 | } |
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173 | else if (col->type == GLP_FX) |
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174 | col->stat = GLP_NS, col->prim = col->lb; |
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175 | col->dual = col->coef; |
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176 | P->obj_val += col->coef * col->prim; |
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177 | /* check dual feasibility */ |
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178 | if (col->type == GLP_FR || col->type == GLP_LO) |
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179 | { /* column has no upper bound */ |
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180 | if (zeta * col->dual < - parm->tol_dj) |
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181 | { P->dbs_stat = GLP_NOFEAS; |
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182 | if (P->some == 0 && parm->meth == GLP_PRIMAL) |
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183 | P->some = P->m + j; |
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184 | } |
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185 | if (d_infeas < - zeta * col->dual) |
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186 | d_infeas = - zeta * col->dual; |
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187 | } |
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188 | if (col->type == GLP_FR || col->type == GLP_UP) |
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189 | { /* column has no lower bound */ |
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190 | if (zeta * col->dual > + parm->tol_dj) |
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191 | { P->dbs_stat = GLP_NOFEAS; |
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192 | if (P->some == 0 && parm->meth == GLP_PRIMAL) |
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193 | P->some = P->m + j; |
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194 | } |
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195 | if (d_infeas < + zeta * col->dual) |
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196 | d_infeas = + zeta * col->dual; |
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197 | } |
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198 | } |
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199 | /* simulate the simplex solver output */ |
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200 | if (parm->msg_lev >= GLP_MSG_ON && parm->out_dly == 0) |
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201 | { xprintf("~%6d: obj = %17.9e infeas = %10.3e\n", P->it_cnt, |
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202 | P->obj_val, parm->meth == GLP_PRIMAL ? p_infeas : d_infeas); |
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203 | } |
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204 | if (parm->msg_lev >= GLP_MSG_ALL && parm->out_dly == 0) |
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205 | { if (P->pbs_stat == GLP_FEAS && P->dbs_stat == GLP_FEAS) |
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206 | xprintf("OPTIMAL SOLUTION FOUND\n"); |
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207 | else if (P->pbs_stat == GLP_NOFEAS) |
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208 | xprintf("PROBLEM HAS NO FEASIBLE SOLUTION\n"); |
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209 | else if (parm->meth == GLP_PRIMAL) |
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210 | xprintf("PROBLEM HAS UNBOUNDED SOLUTION\n"); |
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211 | else |
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212 | xprintf("PROBLEM HAS NO DUAL FEASIBLE SOLUTION\n"); |
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213 | } |
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214 | return; |
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215 | } |
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216 | |
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217 | static int solve_lp(glp_prob *P, const glp_smcp *parm) |
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218 | { /* solve LP directly without using the preprocessor */ |
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219 | int ret; |
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220 | if (!glp_bf_exists(P)) |
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221 | { ret = glp_factorize(P); |
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222 | if (ret == 0) |
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223 | ; |
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224 | else if (ret == GLP_EBADB) |
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225 | { if (parm->msg_lev >= GLP_MSG_ERR) |
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226 | xprintf("glp_simplex: initial basis is invalid\n"); |
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227 | } |
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228 | else if (ret == GLP_ESING) |
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229 | { if (parm->msg_lev >= GLP_MSG_ERR) |
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230 | xprintf("glp_simplex: initial basis is singular\n"); |
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231 | } |
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232 | else if (ret == GLP_ECOND) |
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233 | { if (parm->msg_lev >= GLP_MSG_ERR) |
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234 | xprintf( |
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235 | "glp_simplex: initial basis is ill-conditioned\n"); |
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236 | } |
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237 | else |
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238 | xassert(ret != ret); |
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239 | if (ret != 0) goto done; |
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240 | } |
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241 | if (parm->meth == GLP_PRIMAL) |
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242 | ret = spx_primal(P, parm); |
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243 | else if (parm->meth == GLP_DUALP) |
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244 | { ret = spx_dual(P, parm); |
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245 | if (ret == GLP_EFAIL && P->valid) |
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246 | ret = spx_primal(P, parm); |
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247 | } |
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248 | else if (parm->meth == GLP_DUAL) |
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249 | ret = spx_dual(P, parm); |
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250 | else |
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251 | xassert(parm != parm); |
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252 | done: return ret; |
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253 | } |
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254 | |
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255 | static int preprocess_and_solve_lp(glp_prob *P, const glp_smcp *parm) |
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256 | { /* solve LP using the preprocessor */ |
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257 | NPP *npp; |
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258 | glp_prob *lp = NULL; |
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259 | glp_bfcp bfcp; |
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260 | int ret; |
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261 | if (parm->msg_lev >= GLP_MSG_ALL) |
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262 | xprintf("Preprocessing...\n"); |
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263 | /* create preprocessor workspace */ |
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264 | npp = npp_create_wksp(); |
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265 | /* load original problem into the preprocessor workspace */ |
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266 | npp_load_prob(npp, P, GLP_OFF, GLP_SOL, GLP_OFF); |
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267 | /* process LP prior to applying primal/dual simplex method */ |
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268 | ret = npp_simplex(npp, parm); |
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269 | if (ret == 0) |
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270 | ; |
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271 | else if (ret == GLP_ENOPFS) |
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272 | { if (parm->msg_lev >= GLP_MSG_ALL) |
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273 | xprintf("PROBLEM HAS NO PRIMAL FEASIBLE SOLUTION\n"); |
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274 | } |
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275 | else if (ret == GLP_ENODFS) |
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276 | { if (parm->msg_lev >= GLP_MSG_ALL) |
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277 | xprintf("PROBLEM HAS NO DUAL FEASIBLE SOLUTION\n"); |
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278 | } |
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279 | else |
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280 | xassert(ret != ret); |
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281 | if (ret != 0) goto done; |
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282 | /* build transformed LP */ |
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283 | lp = glp_create_prob(); |
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284 | npp_build_prob(npp, lp); |
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285 | /* if the transformed LP is empty, it has empty solution, which |
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286 | is optimal */ |
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287 | if (lp->m == 0 && lp->n == 0) |
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288 | { lp->pbs_stat = lp->dbs_stat = GLP_FEAS; |
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289 | lp->obj_val = lp->c0; |
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290 | if (parm->msg_lev >= GLP_MSG_ON && parm->out_dly == 0) |
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291 | { xprintf("~%6d: obj = %17.9e infeas = %10.3e\n", P->it_cnt, |
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292 | lp->obj_val, 0.0); |
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293 | } |
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294 | if (parm->msg_lev >= GLP_MSG_ALL) |
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295 | xprintf("OPTIMAL SOLUTION FOUND BY LP PREPROCESSOR\n"); |
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296 | goto post; |
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297 | } |
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298 | if (parm->msg_lev >= GLP_MSG_ALL) |
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299 | { xprintf("%d row%s, %d column%s, %d non-zero%s\n", |
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300 | lp->m, lp->m == 1 ? "" : "s", lp->n, lp->n == 1 ? "" : "s", |
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301 | lp->nnz, lp->nnz == 1 ? "" : "s"); |
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302 | } |
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303 | /* inherit basis factorization control parameters */ |
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304 | glp_get_bfcp(P, &bfcp); |
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305 | glp_set_bfcp(lp, &bfcp); |
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306 | /* scale the transformed problem */ |
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307 | { ENV *env = get_env_ptr(); |
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308 | int term_out = env->term_out; |
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309 | if (!term_out || parm->msg_lev < GLP_MSG_ALL) |
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310 | env->term_out = GLP_OFF; |
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311 | else |
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312 | env->term_out = GLP_ON; |
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313 | glp_scale_prob(lp, GLP_SF_AUTO); |
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314 | env->term_out = term_out; |
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315 | } |
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316 | /* build advanced initial basis */ |
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317 | { ENV *env = get_env_ptr(); |
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318 | int term_out = env->term_out; |
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319 | if (!term_out || parm->msg_lev < GLP_MSG_ALL) |
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320 | env->term_out = GLP_OFF; |
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321 | else |
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322 | env->term_out = GLP_ON; |
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323 | glp_adv_basis(lp, 0); |
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324 | env->term_out = term_out; |
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325 | } |
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326 | /* solve the transformed LP */ |
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327 | lp->it_cnt = P->it_cnt; |
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328 | ret = solve_lp(lp, parm); |
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329 | P->it_cnt = lp->it_cnt; |
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330 | /* only optimal solution can be postprocessed */ |
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331 | if (!(ret == 0 && lp->pbs_stat == GLP_FEAS && lp->dbs_stat == |
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332 | GLP_FEAS)) |
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333 | { if (parm->msg_lev >= GLP_MSG_ERR) |
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334 | xprintf("glp_simplex: unable to recover undefined or non-op" |
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335 | "timal solution\n"); |
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336 | if (ret == 0) |
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337 | { if (lp->pbs_stat == GLP_NOFEAS) |
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338 | ret = GLP_ENOPFS; |
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339 | else if (lp->dbs_stat == GLP_NOFEAS) |
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340 | ret = GLP_ENODFS; |
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341 | else |
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342 | xassert(lp != lp); |
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343 | } |
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344 | goto done; |
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345 | } |
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346 | post: /* postprocess solution from the transformed LP */ |
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347 | npp_postprocess(npp, lp); |
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348 | /* the transformed LP is no longer needed */ |
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349 | glp_delete_prob(lp), lp = NULL; |
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350 | /* store solution to the original problem */ |
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351 | npp_unload_sol(npp, P); |
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352 | /* the original LP has been successfully solved */ |
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353 | ret = 0; |
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354 | done: /* delete the transformed LP, if it exists */ |
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355 | if (lp != NULL) glp_delete_prob(lp); |
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356 | /* delete preprocessor workspace */ |
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357 | npp_delete_wksp(npp); |
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358 | return ret; |
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359 | } |
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360 | |
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361 | int glp_simplex(glp_prob *P, const glp_smcp *parm) |
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362 | { /* solve LP problem with the simplex method */ |
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363 | glp_smcp _parm; |
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364 | int i, j, ret; |
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365 | /* check problem object */ |
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366 | if (P == NULL || P->magic != GLP_PROB_MAGIC) |
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367 | xerror("glp_simplex: P = %p; invalid problem object\n", P); |
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368 | if (P->tree != NULL && P->tree->reason != 0) |
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369 | xerror("glp_simplex: operation not allowed\n"); |
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370 | /* check control parameters */ |
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371 | if (parm == NULL) |
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372 | parm = &_parm, glp_init_smcp((glp_smcp *)parm); |
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373 | if (!(parm->msg_lev == GLP_MSG_OFF || |
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374 | parm->msg_lev == GLP_MSG_ERR || |
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375 | parm->msg_lev == GLP_MSG_ON || |
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376 | parm->msg_lev == GLP_MSG_ALL || |
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377 | parm->msg_lev == GLP_MSG_DBG)) |
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378 | xerror("glp_simplex: msg_lev = %d; invalid parameter\n", |
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379 | parm->msg_lev); |
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380 | if (!(parm->meth == GLP_PRIMAL || |
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381 | parm->meth == GLP_DUALP || |
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382 | parm->meth == GLP_DUAL)) |
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383 | xerror("glp_simplex: meth = %d; invalid parameter\n", |
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384 | parm->meth); |
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385 | if (!(parm->pricing == GLP_PT_STD || |
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386 | parm->pricing == GLP_PT_PSE)) |
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387 | xerror("glp_simplex: pricing = %d; invalid parameter\n", |
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388 | parm->pricing); |
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389 | if (!(parm->r_test == GLP_RT_STD || |
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390 | parm->r_test == GLP_RT_HAR)) |
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391 | xerror("glp_simplex: r_test = %d; invalid parameter\n", |
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392 | parm->r_test); |
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393 | if (!(0.0 < parm->tol_bnd && parm->tol_bnd < 1.0)) |
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394 | xerror("glp_simplex: tol_bnd = %g; invalid parameter\n", |
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395 | parm->tol_bnd); |
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396 | if (!(0.0 < parm->tol_dj && parm->tol_dj < 1.0)) |
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397 | xerror("glp_simplex: tol_dj = %g; invalid parameter\n", |
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398 | parm->tol_dj); |
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399 | if (!(0.0 < parm->tol_piv && parm->tol_piv < 1.0)) |
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400 | xerror("glp_simplex: tol_piv = %g; invalid parameter\n", |
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401 | parm->tol_piv); |
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402 | if (parm->it_lim < 0) |
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403 | xerror("glp_simplex: it_lim = %d; invalid parameter\n", |
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404 | parm->it_lim); |
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405 | if (parm->tm_lim < 0) |
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406 | xerror("glp_simplex: tm_lim = %d; invalid parameter\n", |
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407 | parm->tm_lim); |
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408 | if (parm->out_frq < 1) |
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409 | xerror("glp_simplex: out_frq = %d; invalid parameter\n", |
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410 | parm->out_frq); |
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411 | if (parm->out_dly < 0) |
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412 | xerror("glp_simplex: out_dly = %d; invalid parameter\n", |
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413 | parm->out_dly); |
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414 | if (!(parm->presolve == GLP_ON || parm->presolve == GLP_OFF)) |
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415 | xerror("glp_simplex: presolve = %d; invalid parameter\n", |
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416 | parm->presolve); |
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417 | /* basic solution is currently undefined */ |
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418 | P->pbs_stat = P->dbs_stat = GLP_UNDEF; |
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419 | P->obj_val = 0.0; |
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420 | P->some = 0; |
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421 | /* check bounds of double-bounded variables */ |
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422 | for (i = 1; i <= P->m; i++) |
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423 | { GLPROW *row = P->row[i]; |
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424 | if (row->type == GLP_DB && row->lb >= row->ub) |
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425 | { if (parm->msg_lev >= GLP_MSG_ERR) |
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426 | xprintf("glp_simplex: row %d: lb = %g, ub = %g; incorrec" |
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427 | "t bounds\n", i, row->lb, row->ub); |
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428 | ret = GLP_EBOUND; |
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429 | goto done; |
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430 | } |
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431 | } |
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432 | for (j = 1; j <= P->n; j++) |
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433 | { GLPCOL *col = P->col[j]; |
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434 | if (col->type == GLP_DB && col->lb >= col->ub) |
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435 | { if (parm->msg_lev >= GLP_MSG_ERR) |
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436 | xprintf("glp_simplex: column %d: lb = %g, ub = %g; incor" |
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437 | "rect bounds\n", j, col->lb, col->ub); |
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438 | ret = GLP_EBOUND; |
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439 | goto done; |
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440 | } |
---|
441 | } |
---|
442 | /* solve LP problem */ |
---|
443 | if (parm->msg_lev >= GLP_MSG_ALL) |
---|
444 | { xprintf("GLPK Simplex Optimizer, v%s\n", glp_version()); |
---|
445 | xprintf("%d row%s, %d column%s, %d non-zero%s\n", |
---|
446 | P->m, P->m == 1 ? "" : "s", P->n, P->n == 1 ? "" : "s", |
---|
447 | P->nnz, P->nnz == 1 ? "" : "s"); |
---|
448 | } |
---|
449 | if (P->nnz == 0) |
---|
450 | trivial_lp(P, parm), ret = 0; |
---|
451 | else if (!parm->presolve) |
---|
452 | ret = solve_lp(P, parm); |
---|
453 | else |
---|
454 | ret = preprocess_and_solve_lp(P, parm); |
---|
455 | done: /* return to the application program */ |
---|
456 | return ret; |
---|
457 | } |
---|
458 | |
---|
459 | /*********************************************************************** |
---|
460 | * NAME |
---|
461 | * |
---|
462 | * glp_init_smcp - initialize simplex method control parameters |
---|
463 | * |
---|
464 | * SYNOPSIS |
---|
465 | * |
---|
466 | * void glp_init_smcp(glp_smcp *parm); |
---|
467 | * |
---|
468 | * DESCRIPTION |
---|
469 | * |
---|
470 | * The routine glp_init_smcp initializes control parameters, which are |
---|
471 | * used by the simplex solver, with default values. |
---|
472 | * |
---|
473 | * Default values of the control parameters are stored in a glp_smcp |
---|
474 | * structure, which the parameter parm points to. */ |
---|
475 | |
---|
476 | void glp_init_smcp(glp_smcp *parm) |
---|
477 | { parm->msg_lev = GLP_MSG_ALL; |
---|
478 | parm->meth = GLP_PRIMAL; |
---|
479 | parm->pricing = GLP_PT_PSE; |
---|
480 | parm->r_test = GLP_RT_HAR; |
---|
481 | parm->tol_bnd = 1e-7; |
---|
482 | parm->tol_dj = 1e-7; |
---|
483 | parm->tol_piv = 1e-10; |
---|
484 | parm->obj_ll = -DBL_MAX; |
---|
485 | parm->obj_ul = +DBL_MAX; |
---|
486 | parm->it_lim = INT_MAX; |
---|
487 | parm->tm_lim = INT_MAX; |
---|
488 | parm->out_frq = 500; |
---|
489 | parm->out_dly = 0; |
---|
490 | parm->presolve = GLP_OFF; |
---|
491 | return; |
---|
492 | } |
---|
493 | |
---|
494 | /*********************************************************************** |
---|
495 | * NAME |
---|
496 | * |
---|
497 | * glp_get_status - retrieve generic status of basic solution |
---|
498 | * |
---|
499 | * SYNOPSIS |
---|
500 | * |
---|
501 | * int glp_get_status(glp_prob *lp); |
---|
502 | * |
---|
503 | * RETURNS |
---|
504 | * |
---|
505 | * The routine glp_get_status reports the generic status of the basic |
---|
506 | * solution for the specified problem object as follows: |
---|
507 | * |
---|
508 | * GLP_OPT - solution is optimal; |
---|
509 | * GLP_FEAS - solution is feasible; |
---|
510 | * GLP_INFEAS - solution is infeasible; |
---|
511 | * GLP_NOFEAS - problem has no feasible solution; |
---|
512 | * GLP_UNBND - problem has unbounded solution; |
---|
513 | * GLP_UNDEF - solution is undefined. */ |
---|
514 | |
---|
515 | int glp_get_status(glp_prob *lp) |
---|
516 | { int status; |
---|
517 | status = glp_get_prim_stat(lp); |
---|
518 | switch (status) |
---|
519 | { case GLP_FEAS: |
---|
520 | switch (glp_get_dual_stat(lp)) |
---|
521 | { case GLP_FEAS: |
---|
522 | status = GLP_OPT; |
---|
523 | break; |
---|
524 | case GLP_NOFEAS: |
---|
525 | status = GLP_UNBND; |
---|
526 | break; |
---|
527 | case GLP_UNDEF: |
---|
528 | case GLP_INFEAS: |
---|
529 | status = status; |
---|
530 | break; |
---|
531 | default: |
---|
532 | xassert(lp != lp); |
---|
533 | } |
---|
534 | break; |
---|
535 | case GLP_UNDEF: |
---|
536 | case GLP_INFEAS: |
---|
537 | case GLP_NOFEAS: |
---|
538 | status = status; |
---|
539 | break; |
---|
540 | default: |
---|
541 | xassert(lp != lp); |
---|
542 | } |
---|
543 | return status; |
---|
544 | } |
---|
545 | |
---|
546 | /*********************************************************************** |
---|
547 | * NAME |
---|
548 | * |
---|
549 | * glp_get_prim_stat - retrieve status of primal basic solution |
---|
550 | * |
---|
551 | * SYNOPSIS |
---|
552 | * |
---|
553 | * int glp_get_prim_stat(glp_prob *lp); |
---|
554 | * |
---|
555 | * RETURNS |
---|
556 | * |
---|
557 | * The routine glp_get_prim_stat reports the status of the primal basic |
---|
558 | * solution for the specified problem object as follows: |
---|
559 | * |
---|
560 | * GLP_UNDEF - primal solution is undefined; |
---|
561 | * GLP_FEAS - primal solution is feasible; |
---|
562 | * GLP_INFEAS - primal solution is infeasible; |
---|
563 | * GLP_NOFEAS - no primal feasible solution exists. */ |
---|
564 | |
---|
565 | int glp_get_prim_stat(glp_prob *lp) |
---|
566 | { int pbs_stat = lp->pbs_stat; |
---|
567 | return pbs_stat; |
---|
568 | } |
---|
569 | |
---|
570 | /*********************************************************************** |
---|
571 | * NAME |
---|
572 | * |
---|
573 | * glp_get_dual_stat - retrieve status of dual basic solution |
---|
574 | * |
---|
575 | * SYNOPSIS |
---|
576 | * |
---|
577 | * int glp_get_dual_stat(glp_prob *lp); |
---|
578 | * |
---|
579 | * RETURNS |
---|
580 | * |
---|
581 | * The routine glp_get_dual_stat reports the status of the dual basic |
---|
582 | * solution for the specified problem object as follows: |
---|
583 | * |
---|
584 | * GLP_UNDEF - dual solution is undefined; |
---|
585 | * GLP_FEAS - dual solution is feasible; |
---|
586 | * GLP_INFEAS - dual solution is infeasible; |
---|
587 | * GLP_NOFEAS - no dual feasible solution exists. */ |
---|
588 | |
---|
589 | int glp_get_dual_stat(glp_prob *lp) |
---|
590 | { int dbs_stat = lp->dbs_stat; |
---|
591 | return dbs_stat; |
---|
592 | } |
---|
593 | |
---|
594 | /*********************************************************************** |
---|
595 | * NAME |
---|
596 | * |
---|
597 | * glp_get_obj_val - retrieve objective value (basic solution) |
---|
598 | * |
---|
599 | * SYNOPSIS |
---|
600 | * |
---|
601 | * double glp_get_obj_val(glp_prob *lp); |
---|
602 | * |
---|
603 | * RETURNS |
---|
604 | * |
---|
605 | * The routine glp_get_obj_val returns value of the objective function |
---|
606 | * for basic solution. */ |
---|
607 | |
---|
608 | double glp_get_obj_val(glp_prob *lp) |
---|
609 | { /*struct LPXCPS *cps = lp->cps;*/ |
---|
610 | double z; |
---|
611 | z = lp->obj_val; |
---|
612 | /*if (cps->round && fabs(z) < 1e-9) z = 0.0;*/ |
---|
613 | return z; |
---|
614 | } |
---|
615 | |
---|
616 | /*********************************************************************** |
---|
617 | * NAME |
---|
618 | * |
---|
619 | * glp_get_row_stat - retrieve row status |
---|
620 | * |
---|
621 | * SYNOPSIS |
---|
622 | * |
---|
623 | * int glp_get_row_stat(glp_prob *lp, int i); |
---|
624 | * |
---|
625 | * RETURNS |
---|
626 | * |
---|
627 | * The routine glp_get_row_stat returns current status assigned to the |
---|
628 | * auxiliary variable associated with i-th row as follows: |
---|
629 | * |
---|
630 | * GLP_BS - basic variable; |
---|
631 | * GLP_NL - non-basic variable on its lower bound; |
---|
632 | * GLP_NU - non-basic variable on its upper bound; |
---|
633 | * GLP_NF - non-basic free (unbounded) variable; |
---|
634 | * GLP_NS - non-basic fixed variable. */ |
---|
635 | |
---|
636 | int glp_get_row_stat(glp_prob *lp, int i) |
---|
637 | { if (!(1 <= i && i <= lp->m)) |
---|
638 | xerror("glp_get_row_stat: i = %d; row number out of range\n", |
---|
639 | i); |
---|
640 | return lp->row[i]->stat; |
---|
641 | } |
---|
642 | |
---|
643 | /*********************************************************************** |
---|
644 | * NAME |
---|
645 | * |
---|
646 | * glp_get_row_prim - retrieve row primal value (basic solution) |
---|
647 | * |
---|
648 | * SYNOPSIS |
---|
649 | * |
---|
650 | * double glp_get_row_prim(glp_prob *lp, int i); |
---|
651 | * |
---|
652 | * RETURNS |
---|
653 | * |
---|
654 | * The routine glp_get_row_prim returns primal value of the auxiliary |
---|
655 | * variable associated with i-th row. */ |
---|
656 | |
---|
657 | double glp_get_row_prim(glp_prob *lp, int i) |
---|
658 | { /*struct LPXCPS *cps = lp->cps;*/ |
---|
659 | double prim; |
---|
660 | if (!(1 <= i && i <= lp->m)) |
---|
661 | xerror("glp_get_row_prim: i = %d; row number out of range\n", |
---|
662 | i); |
---|
663 | prim = lp->row[i]->prim; |
---|
664 | /*if (cps->round && fabs(prim) < 1e-9) prim = 0.0;*/ |
---|
665 | return prim; |
---|
666 | } |
---|
667 | |
---|
668 | /*********************************************************************** |
---|
669 | * NAME |
---|
670 | * |
---|
671 | * glp_get_row_dual - retrieve row dual value (basic solution) |
---|
672 | * |
---|
673 | * SYNOPSIS |
---|
674 | * |
---|
675 | * double glp_get_row_dual(glp_prob *lp, int i); |
---|
676 | * |
---|
677 | * RETURNS |
---|
678 | * |
---|
679 | * The routine glp_get_row_dual returns dual value (i.e. reduced cost) |
---|
680 | * of the auxiliary variable associated with i-th row. */ |
---|
681 | |
---|
682 | double glp_get_row_dual(glp_prob *lp, int i) |
---|
683 | { /*struct LPXCPS *cps = lp->cps;*/ |
---|
684 | double dual; |
---|
685 | if (!(1 <= i && i <= lp->m)) |
---|
686 | xerror("glp_get_row_dual: i = %d; row number out of range\n", |
---|
687 | i); |
---|
688 | dual = lp->row[i]->dual; |
---|
689 | /*if (cps->round && fabs(dual) < 1e-9) dual = 0.0;*/ |
---|
690 | return dual; |
---|
691 | } |
---|
692 | |
---|
693 | /*********************************************************************** |
---|
694 | * NAME |
---|
695 | * |
---|
696 | * glp_get_col_stat - retrieve column status |
---|
697 | * |
---|
698 | * SYNOPSIS |
---|
699 | * |
---|
700 | * int glp_get_col_stat(glp_prob *lp, int j); |
---|
701 | * |
---|
702 | * RETURNS |
---|
703 | * |
---|
704 | * The routine glp_get_col_stat returns current status assigned to the |
---|
705 | * structural variable associated with j-th column as follows: |
---|
706 | * |
---|
707 | * GLP_BS - basic variable; |
---|
708 | * GLP_NL - non-basic variable on its lower bound; |
---|
709 | * GLP_NU - non-basic variable on its upper bound; |
---|
710 | * GLP_NF - non-basic free (unbounded) variable; |
---|
711 | * GLP_NS - non-basic fixed variable. */ |
---|
712 | |
---|
713 | int glp_get_col_stat(glp_prob *lp, int j) |
---|
714 | { if (!(1 <= j && j <= lp->n)) |
---|
715 | xerror("glp_get_col_stat: j = %d; column number out of range\n" |
---|
716 | , j); |
---|
717 | return lp->col[j]->stat; |
---|
718 | } |
---|
719 | |
---|
720 | /*********************************************************************** |
---|
721 | * NAME |
---|
722 | * |
---|
723 | * glp_get_col_prim - retrieve column primal value (basic solution) |
---|
724 | * |
---|
725 | * SYNOPSIS |
---|
726 | * |
---|
727 | * double glp_get_col_prim(glp_prob *lp, int j); |
---|
728 | * |
---|
729 | * RETURNS |
---|
730 | * |
---|
731 | * The routine glp_get_col_prim returns primal value of the structural |
---|
732 | * variable associated with j-th column. */ |
---|
733 | |
---|
734 | double glp_get_col_prim(glp_prob *lp, int j) |
---|
735 | { /*struct LPXCPS *cps = lp->cps;*/ |
---|
736 | double prim; |
---|
737 | if (!(1 <= j && j <= lp->n)) |
---|
738 | xerror("glp_get_col_prim: j = %d; column number out of range\n" |
---|
739 | , j); |
---|
740 | prim = lp->col[j]->prim; |
---|
741 | /*if (cps->round && fabs(prim) < 1e-9) prim = 0.0;*/ |
---|
742 | return prim; |
---|
743 | } |
---|
744 | |
---|
745 | /*********************************************************************** |
---|
746 | * NAME |
---|
747 | * |
---|
748 | * glp_get_col_dual - retrieve column dual value (basic solution) |
---|
749 | * |
---|
750 | * SYNOPSIS |
---|
751 | * |
---|
752 | * double glp_get_col_dual(glp_prob *lp, int j); |
---|
753 | * |
---|
754 | * RETURNS |
---|
755 | * |
---|
756 | * The routine glp_get_col_dual returns dual value (i.e. reduced cost) |
---|
757 | * of the structural variable associated with j-th column. */ |
---|
758 | |
---|
759 | double glp_get_col_dual(glp_prob *lp, int j) |
---|
760 | { /*struct LPXCPS *cps = lp->cps;*/ |
---|
761 | double dual; |
---|
762 | if (!(1 <= j && j <= lp->n)) |
---|
763 | xerror("glp_get_col_dual: j = %d; column number out of range\n" |
---|
764 | , j); |
---|
765 | dual = lp->col[j]->dual; |
---|
766 | /*if (cps->round && fabs(dual) < 1e-9) dual = 0.0;*/ |
---|
767 | return dual; |
---|
768 | } |
---|
769 | |
---|
770 | /*********************************************************************** |
---|
771 | * NAME |
---|
772 | * |
---|
773 | * glp_get_unbnd_ray - determine variable causing unboundedness |
---|
774 | * |
---|
775 | * SYNOPSIS |
---|
776 | * |
---|
777 | * int glp_get_unbnd_ray(glp_prob *lp); |
---|
778 | * |
---|
779 | * RETURNS |
---|
780 | * |
---|
781 | * The routine glp_get_unbnd_ray returns the number k of a variable, |
---|
782 | * which causes primal or dual unboundedness. If 1 <= k <= m, it is |
---|
783 | * k-th auxiliary variable, and if m+1 <= k <= m+n, it is (k-m)-th |
---|
784 | * structural variable, where m is the number of rows, n is the number |
---|
785 | * of columns in the problem object. If such variable is not defined, |
---|
786 | * the routine returns 0. |
---|
787 | * |
---|
788 | * COMMENTS |
---|
789 | * |
---|
790 | * If it is not exactly known which version of the simplex solver |
---|
791 | * detected unboundedness, i.e. whether the unboundedness is primal or |
---|
792 | * dual, it is sufficient to check the status of the variable reported |
---|
793 | * with the routine glp_get_row_stat or glp_get_col_stat. If the |
---|
794 | * variable is non-basic, the unboundedness is primal, otherwise, if |
---|
795 | * the variable is basic, the unboundedness is dual (the latter case |
---|
796 | * means that the problem has no primal feasible dolution). */ |
---|
797 | |
---|
798 | int glp_get_unbnd_ray(glp_prob *lp) |
---|
799 | { int k; |
---|
800 | k = lp->some; |
---|
801 | xassert(k >= 0); |
---|
802 | if (k > lp->m + lp->n) k = 0; |
---|
803 | return k; |
---|
804 | } |
---|
805 | |
---|
806 | /* eof */ |
---|