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1 /* glpapi08.c (interior-point 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, 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 "glpapi.h"
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26 #include "glpipm.h"
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27 #include "glpnpp.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_interior - solve LP problem with the interior-point method
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33 *
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34 * SYNOPSIS
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35 *
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36 * int glp_interior(glp_prob *P, const glp_iptcp *parm);
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37 *
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38 * The routine glp_interior is a driver to the LP solver based on the
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39 * interior-point method.
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40 *
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41 * The interior-point solver has a set of control parameters. Values of
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42 * the control parameters can be passed in a structure glp_iptcp, which
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43 * the parameter parm points to.
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44 *
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45 * Currently this routine implements an easy variant of the primal-dual
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46 * interior-point method based on Mehrotra's technique.
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47 *
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48 * This routine transforms the original LP problem to an equivalent LP
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49 * problem in the standard formulation (all constraints are equalities,
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50 * all variables are non-negative), calls the routine ipm_main to solve
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51 * the transformed problem, and then transforms an obtained solution to
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52 * the solution of the original problem.
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53 *
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54 * RETURNS
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55 *
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56 * 0 The LP problem instance has been successfully solved. This code
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57 * does not necessarily mean that the solver has found optimal
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58 * solution. It only means that the solution process was successful.
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59 *
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60 * GLP_EFAIL
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61 * The problem has no rows/columns.
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62 *
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63 * GLP_ENOCVG
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64 * Very slow convergence or divergence.
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65 *
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66 * GLP_EITLIM
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67 * Iteration limit exceeded.
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68 *
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69 * GLP_EINSTAB
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70 * Numerical instability on solving Newtonian system. */
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71
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72 static void transform(NPP *npp)
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73 { /* transform LP to the standard formulation */
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74 NPPROW *row, *prev_row;
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75 NPPCOL *col, *prev_col;
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76 for (row = npp->r_tail; row != NULL; row = prev_row)
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77 { prev_row = row->prev;
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78 if (row->lb == -DBL_MAX && row->ub == +DBL_MAX)
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79 npp_free_row(npp, row);
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80 else if (row->lb == -DBL_MAX)
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81 npp_leq_row(npp, row);
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82 else if (row->ub == +DBL_MAX)
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83 npp_geq_row(npp, row);
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84 else if (row->lb != row->ub)
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85 { if (fabs(row->lb) < fabs(row->ub))
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86 npp_geq_row(npp, row);
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87 else
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88 npp_leq_row(npp, row);
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89 }
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90 }
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91 for (col = npp->c_tail; col != NULL; col = prev_col)
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92 { prev_col = col->prev;
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93 if (col->lb == -DBL_MAX && col->ub == +DBL_MAX)
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94 npp_free_col(npp, col);
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95 else if (col->lb == -DBL_MAX)
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96 npp_ubnd_col(npp, col);
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97 else if (col->ub == +DBL_MAX)
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98 { if (col->lb != 0.0)
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99 npp_lbnd_col(npp, col);
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100 }
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101 else if (col->lb != col->ub)
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102 { if (fabs(col->lb) < fabs(col->ub))
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103 { if (col->lb != 0.0)
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104 npp_lbnd_col(npp, col);
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105 }
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106 else
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107 npp_ubnd_col(npp, col);
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108 npp_dbnd_col(npp, col);
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109 }
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110 else
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111 npp_fixed_col(npp, col);
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112 }
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113 for (row = npp->r_head; row != NULL; row = row->next)
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114 xassert(row->lb == row->ub);
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115 for (col = npp->c_head; col != NULL; col = col->next)
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116 xassert(col->lb == 0.0 && col->ub == +DBL_MAX);
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117 return;
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118 }
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119
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120 int glp_interior(glp_prob *P, const glp_iptcp *parm)
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121 { glp_iptcp _parm;
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122 GLPROW *row;
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123 GLPCOL *col;
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124 NPP *npp = NULL;
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125 glp_prob *prob = NULL;
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126 int i, j, ret;
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127 /* check control parameters */
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128 if (parm == NULL)
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129 glp_init_iptcp(&_parm), parm = &_parm;
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130 if (!(parm->msg_lev == GLP_MSG_OFF ||
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131 parm->msg_lev == GLP_MSG_ERR ||
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132 parm->msg_lev == GLP_MSG_ON ||
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133 parm->msg_lev == GLP_MSG_ALL))
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134 xerror("glp_interior: msg_lev = %d; invalid parameter\n",
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135 parm->msg_lev);
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136 if (!(parm->ord_alg == GLP_ORD_NONE ||
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137 parm->ord_alg == GLP_ORD_QMD ||
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138 parm->ord_alg == GLP_ORD_AMD ||
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139 parm->ord_alg == GLP_ORD_SYMAMD))
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140 xerror("glp_interior: ord_alg = %d; invalid parameter\n",
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141 parm->ord_alg);
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142 /* interior-point solution is currently undefined */
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143 P->ipt_stat = GLP_UNDEF;
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144 P->ipt_obj = 0.0;
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145 /* check bounds of double-bounded variables */
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146 for (i = 1; i <= P->m; i++)
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147 { row = P->row[i];
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148 if (row->type == GLP_DB && row->lb >= row->ub)
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149 { if (parm->msg_lev >= GLP_MSG_ERR)
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150 xprintf("glp_interior: row %d: lb = %g, ub = %g; incorre"
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151 "ct bounds\n", i, row->lb, row->ub);
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152 ret = GLP_EBOUND;
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153 goto done;
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154 }
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155 }
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156 for (j = 1; j <= P->n; j++)
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157 { col = P->col[j];
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158 if (col->type == GLP_DB && col->lb >= col->ub)
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159 { if (parm->msg_lev >= GLP_MSG_ERR)
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160 xprintf("glp_interior: column %d: lb = %g, ub = %g; inco"
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161 "rrect bounds\n", j, col->lb, col->ub);
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162 ret = GLP_EBOUND;
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163 goto done;
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164 }
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165 }
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166 /* transform LP to the standard formulation */
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167 if (parm->msg_lev >= GLP_MSG_ALL)
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168 xprintf("Original LP has %d row(s), %d column(s), and %d non-z"
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169 "ero(s)\n", P->m, P->n, P->nnz);
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170 npp = npp_create_wksp();
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171 npp_load_prob(npp, P, GLP_OFF, GLP_IPT, GLP_ON);
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172 transform(npp);
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173 prob = glp_create_prob();
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174 npp_build_prob(npp, prob);
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175 if (parm->msg_lev >= GLP_MSG_ALL)
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176 xprintf("Working LP has %d row(s), %d column(s), and %d non-ze"
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177 "ro(s)\n", prob->m, prob->n, prob->nnz);
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178 #if 1
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179 /* currently empty problem cannot be solved */
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180 if (!(prob->m > 0 && prob->n > 0))
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181 { if (parm->msg_lev >= GLP_MSG_ERR)
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182 xprintf("glp_interior: unable to solve empty problem\n");
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183 ret = GLP_EFAIL;
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184 goto done;
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185 }
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186 #endif
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alpar@9
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187 /* scale the resultant LP */
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188 { ENV *env = get_env_ptr();
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189 int term_out = env->term_out;
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190 env->term_out = GLP_OFF;
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191 glp_scale_prob(prob, GLP_SF_EQ);
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192 env->term_out = term_out;
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193 }
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194 /* warn about dense columns */
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195 if (parm->msg_lev >= GLP_MSG_ON && prob->m >= 200)
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alpar@9
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196 { int len, cnt = 0;
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197 for (j = 1; j <= prob->n; j++)
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198 { len = glp_get_mat_col(prob, j, NULL, NULL);
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199 if ((double)len >= 0.20 * (double)prob->m) cnt++;
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200 }
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201 if (cnt == 1)
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202 xprintf("WARNING: PROBLEM HAS ONE DENSE COLUMN\n");
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203 else if (cnt > 0)
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204 xprintf("WARNING: PROBLEM HAS %d DENSE COLUMNS\n", cnt);
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205 }
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alpar@9
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206 /* solve the transformed LP */
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207 ret = ipm_solve(prob, parm);
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alpar@9
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208 /* postprocess solution from the transformed LP */
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209 npp_postprocess(npp, prob);
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alpar@9
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210 /* and store solution to the original LP */
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211 npp_unload_sol(npp, P);
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212 done: /* free working program objects */
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213 if (npp != NULL) npp_delete_wksp(npp);
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214 if (prob != NULL) glp_delete_prob(prob);
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alpar@9
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215 /* return to the application program */
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216 return ret;
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217 }
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218
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219 /***********************************************************************
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220 * NAME
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221 *
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222 * glp_init_iptcp - initialize interior-point solver control parameters
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223 *
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224 * SYNOPSIS
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alpar@9
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225 *
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226 * void glp_init_iptcp(glp_iptcp *parm);
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227 *
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228 * DESCRIPTION
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229 *
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alpar@9
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230 * The routine glp_init_iptcp initializes control parameters, which are
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231 * used by the interior-point solver, with default values.
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232 *
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233 * Default values of the control parameters are stored in the glp_iptcp
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234 * structure, which the parameter parm points to. */
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235
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236 void glp_init_iptcp(glp_iptcp *parm)
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237 { parm->msg_lev = GLP_MSG_ALL;
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238 parm->ord_alg = GLP_ORD_AMD;
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239 return;
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240 }
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241
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alpar@9
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242 /***********************************************************************
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alpar@9
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243 * NAME
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alpar@9
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244 *
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245 * glp_ipt_status - retrieve status of interior-point solution
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alpar@9
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246 *
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alpar@9
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247 * SYNOPSIS
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alpar@9
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248 *
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alpar@9
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249 * int glp_ipt_status(glp_prob *lp);
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alpar@9
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250 *
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alpar@9
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251 * RETURNS
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alpar@9
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252 *
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alpar@9
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253 * The routine glp_ipt_status reports the status of solution found by
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254 * the interior-point solver as follows:
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alpar@9
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255 *
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256 * GLP_UNDEF - interior-point solution is undefined;
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alpar@9
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257 * GLP_OPT - interior-point solution is optimal;
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alpar@9
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258 * GLP_INFEAS - interior-point solution is infeasible;
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259 * GLP_NOFEAS - no feasible solution exists. */
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260
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261 int glp_ipt_status(glp_prob *lp)
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262 { int ipt_stat = lp->ipt_stat;
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263 return ipt_stat;
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264 }
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265
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alpar@9
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266 /***********************************************************************
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alpar@9
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267 * NAME
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alpar@9
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268 *
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alpar@9
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269 * glp_ipt_obj_val - retrieve objective value (interior point)
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alpar@9
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270 *
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alpar@9
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271 * SYNOPSIS
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alpar@9
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272 *
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alpar@9
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273 * double glp_ipt_obj_val(glp_prob *lp);
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alpar@9
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274 *
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alpar@9
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275 * RETURNS
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alpar@9
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276 *
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alpar@9
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277 * The routine glp_ipt_obj_val returns value of the objective function
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alpar@9
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278 * for interior-point solution. */
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279
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280 double glp_ipt_obj_val(glp_prob *lp)
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alpar@9
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281 { /*struct LPXCPS *cps = lp->cps;*/
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alpar@9
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282 double z;
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alpar@9
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283 z = lp->ipt_obj;
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alpar@9
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284 /*if (cps->round && fabs(z) < 1e-9) z = 0.0;*/
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285 return z;
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alpar@9
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286 }
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alpar@9
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287
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alpar@9
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288 /***********************************************************************
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alpar@9
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289 * NAME
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alpar@9
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290 *
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alpar@9
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291 * glp_ipt_row_prim - retrieve row primal value (interior point)
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alpar@9
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292 *
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alpar@9
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293 * SYNOPSIS
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alpar@9
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294 *
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alpar@9
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295 * double glp_ipt_row_prim(glp_prob *lp, int i);
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alpar@9
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296 *
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alpar@9
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297 * RETURNS
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alpar@9
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298 *
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alpar@9
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299 * The routine glp_ipt_row_prim returns primal value of the auxiliary
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alpar@9
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300 * variable associated with i-th row. */
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alpar@9
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301
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alpar@9
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302 double glp_ipt_row_prim(glp_prob *lp, int i)
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alpar@9
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303 { /*struct LPXCPS *cps = lp->cps;*/
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alpar@9
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304 double pval;
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alpar@9
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305 if (!(1 <= i && i <= lp->m))
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alpar@9
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306 xerror("glp_ipt_row_prim: i = %d; row number out of range\n",
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alpar@9
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307 i);
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alpar@9
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308 pval = lp->row[i]->pval;
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alpar@9
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309 /*if (cps->round && fabs(pval) < 1e-9) pval = 0.0;*/
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alpar@9
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310 return pval;
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alpar@9
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311 }
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alpar@9
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312
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alpar@9
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313 /***********************************************************************
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alpar@9
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314 * NAME
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alpar@9
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315 *
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alpar@9
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316 * glp_ipt_row_dual - retrieve row dual value (interior point)
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alpar@9
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317 *
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alpar@9
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318 * SYNOPSIS
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alpar@9
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319 *
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alpar@9
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320 * double glp_ipt_row_dual(glp_prob *lp, int i);
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alpar@9
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321 *
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alpar@9
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322 * RETURNS
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alpar@9
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323 *
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alpar@9
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324 * The routine glp_ipt_row_dual returns dual value (i.e. reduced cost)
|
alpar@9
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325 * of the auxiliary variable associated with i-th row. */
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alpar@9
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326
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alpar@9
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327 double glp_ipt_row_dual(glp_prob *lp, int i)
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alpar@9
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328 { /*struct LPXCPS *cps = lp->cps;*/
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alpar@9
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329 double dval;
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alpar@9
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330 if (!(1 <= i && i <= lp->m))
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alpar@9
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331 xerror("glp_ipt_row_dual: i = %d; row number out of range\n",
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alpar@9
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332 i);
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alpar@9
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333 dval = lp->row[i]->dval;
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alpar@9
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334 /*if (cps->round && fabs(dval) < 1e-9) dval = 0.0;*/
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335 return dval;
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336 }
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337
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338 /***********************************************************************
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alpar@9
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339 * NAME
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340 *
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341 * glp_ipt_col_prim - retrieve column primal value (interior point)
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342 *
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343 * SYNOPSIS
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344 *
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345 * double glp_ipt_col_prim(glp_prob *lp, int j);
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346 *
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347 * RETURNS
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348 *
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349 * The routine glp_ipt_col_prim returns primal value of the structural
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350 * variable associated with j-th column. */
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351
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352 double glp_ipt_col_prim(glp_prob *lp, int j)
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353 { /*struct LPXCPS *cps = lp->cps;*/
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354 double pval;
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355 if (!(1 <= j && j <= lp->n))
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356 xerror("glp_ipt_col_prim: j = %d; column number out of range\n"
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357 , j);
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358 pval = lp->col[j]->pval;
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alpar@9
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359 /*if (cps->round && fabs(pval) < 1e-9) pval = 0.0;*/
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360 return pval;
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361 }
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362
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alpar@9
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363 /***********************************************************************
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alpar@9
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364 * NAME
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alpar@9
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365 *
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366 * glp_ipt_col_dual - retrieve column dual value (interior point)
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alpar@9
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367 *
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368 * SYNOPSIS
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369 *
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370 * #include "glplpx.h"
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371 * double glp_ipt_col_dual(glp_prob *lp, int j);
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alpar@9
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372 *
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373 * RETURNS
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374 *
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375 * The routine glp_ipt_col_dual returns dual value (i.e. reduced cost)
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376 * of the structural variable associated with j-th column. */
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377
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alpar@9
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378 double glp_ipt_col_dual(glp_prob *lp, int j)
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alpar@9
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379 { /*struct LPXCPS *cps = lp->cps;*/
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380 double dval;
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381 if (!(1 <= j && j <= lp->n))
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382 xerror("glp_ipt_col_dual: j = %d; column number out of range\n"
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383 , j);
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384 dval = lp->col[j]->dval;
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alpar@9
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385 /*if (cps->round && fabs(dval) < 1e-9) dval = 0.0;*/
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386 return dval;
|
alpar@9
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387 }
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388
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389 /* eof */
|