1 | /* |
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2 | * TSPSG: TSP Solver and Generator |
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3 | * Copyright (C) 2007-2010 Lёppa <contacts[at]oleksii[dot]name> |
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4 | * |
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5 | * $Id: tspsolver.cpp 93 2010-02-23 22:17:48Z laleppa $ |
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6 | * $URL: https://tspsg.svn.sourceforge.net/svnroot/tspsg/trunk/src/tspsolver.cpp $ |
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7 | * |
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8 | * This file is part of TSPSG. |
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9 | * |
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10 | * TSPSG is free software: you can redistribute it and/or modify |
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11 | * it under the terms of the GNU General Public License as published by |
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12 | * the Free Software Foundation, either version 3 of the License, or |
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13 | * (at your option) any later version. |
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14 | * |
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15 | * TSPSG is distributed in the hope that it will be useful, |
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16 | * but WITHOUT ANY WARRANTY; without even the implied warranty of |
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17 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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18 | * GNU General Public License for more details. |
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19 | * |
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20 | * You should have received a copy of the GNU General Public License |
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21 | * along with TSPSG. If not, see <http://www.gnu.org/licenses/>. |
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22 | */ |
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23 | |
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24 | #include "tspsolver.h" |
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25 | |
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26 | //! Class constructor |
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27 | CTSPSolver::CTSPSolver() |
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28 | : nCities(0), root(NULL) |
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29 | { |
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30 | } |
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31 | |
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32 | /*! |
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33 | * \brief Returns the sorted optimal path, starting from City 1. |
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34 | * \return A string, containing sorted optimal path. |
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35 | */ |
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36 | QString CTSPSolver::getSortedPath() const |
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37 | { |
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38 | if (!root || route.isEmpty() || (route.size() != nCities)) |
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39 | return QString(); |
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40 | |
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41 | int i = 0; // We start from City 1 |
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42 | QString path = tr("City %1").arg(1) + " -> "; |
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43 | while ((i = route[i]) != 0) { |
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44 | path += tr("City %1").arg(i + 1) + " -> "; |
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45 | } |
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46 | // And finish in City 1, too |
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47 | path += tr("City %1").arg(1); |
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48 | |
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49 | return path; |
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50 | } |
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51 | |
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52 | /*! |
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53 | * \brief Returns CTSPSolver's version ID. |
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54 | * \return A string: <b>\$Id: tspsolver.cpp 93 2010-02-23 22:17:48Z laleppa $</b>. |
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55 | */ |
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56 | QString CTSPSolver::getVersionId() |
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57 | { |
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58 | return QString("$Id: tspsolver.cpp 93 2010-02-23 22:17:48Z laleppa $"); |
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59 | } |
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60 | |
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61 | /*! |
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62 | * \brief Returns whether or not the solution is definitely optimal. |
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63 | * \return \c true if solution is definitely optimal, otherwise \c false. |
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64 | * |
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65 | * The solution may need some further interations to determine whether it is optimal. |
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66 | * In such cases this function returns \c false. |
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67 | */ |
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68 | bool CTSPSolver::isOptimal() const |
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69 | { |
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70 | return !mayNotBeOptimal; |
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71 | } |
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72 | |
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73 | /*! |
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74 | * \brief Solves the given task. |
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75 | * \param numCities Number of cities in the task. |
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76 | * \param task The matrix of city-to-city travel costs. |
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77 | * \param parent The parent widget for displaying messages and dialogs. |
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78 | * \return Pointer to the root of the solution tree. |
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79 | * |
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80 | * \todo TODO: Comment the algorithm. |
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81 | */ |
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82 | SStep *CTSPSolver::solve(int numCities, TMatrix task, QWidget *parent) |
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83 | { |
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84 | if (numCities <= 1) |
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85 | return NULL; |
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86 | cleanup(); |
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87 | nCities = numCities; |
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88 | QProgressDialog pd(parent); |
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89 | QProgressBar *pb = new QProgressBar(&pd); |
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90 | pb->setAlignment(Qt::AlignCenter); |
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91 | pb->setFormat(tr("%v of %m parts found")); |
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92 | pd.setBar(pb); |
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93 | pd.setMaximum(nCities); |
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94 | pd.setMinimumDuration(1000); |
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95 | pd.setLabelText(tr("Calculating optimal route...")); |
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96 | pd.setWindowTitle(tr("Solution Progress")); |
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97 | pd.setWindowModality(Qt::ApplicationModal); |
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98 | pd.setValue(0); |
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99 | |
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100 | SStep *step = new SStep(); |
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101 | step->matrix = task; |
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102 | step->price = align(step->matrix); |
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103 | root = step; |
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104 | |
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105 | SStep *left, *right; |
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106 | int nRow, nCol; |
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107 | bool firstStep = true; |
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108 | double check = INFINITY; |
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109 | while (this->route.size() < nCities) { |
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110 | // forbidden.clear(); |
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111 | step->alts = findCandidate(step->matrix,nRow,nCol); |
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112 | while (hasSubCycles(nRow,nCol)) { |
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113 | // forbidden[nRow] = nCol; |
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114 | step->matrix[nRow][nCol] = INFINITY; |
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115 | step->price += align(step->matrix); |
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116 | step->alts = findCandidate(step->matrix,nRow,nCol); |
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117 | } |
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118 | if ((nRow == -1) || (nCol == -1) || pd.wasCanceled()) { |
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119 | cleanup(); |
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120 | break; |
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121 | } |
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122 | |
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123 | // Route with (nRow,nCol) path |
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124 | right = new SStep(); |
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125 | right->pNode = step; |
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126 | right->matrix = step->matrix; |
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127 | for (int k = 0; k < nCities; k++) { |
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128 | if (k != nCol) |
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129 | right->matrix[nRow][k] = INFINITY; |
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130 | if (k != nRow) |
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131 | right->matrix[k][nCol] = INFINITY; |
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132 | } |
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133 | right->price = step->price + align(right->matrix); |
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134 | // Forbid selected route to exclude its reuse in next steps. |
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135 | right->matrix[nCol][nRow] = INFINITY; |
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136 | right->matrix[nRow][nCol] = INFINITY; |
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137 | |
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138 | // Route without (nRow,nCol) path |
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139 | left = new SStep(); |
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140 | left->pNode = step; |
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141 | left->matrix = step->matrix; |
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142 | left->matrix[nRow][nCol] = INFINITY; |
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143 | left->price = step->price + align(left->matrix); |
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144 | |
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145 | step->candidate.nRow = nRow; |
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146 | step->candidate.nCol = nCol; |
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147 | step->plNode = left; |
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148 | step->prNode = right; |
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149 | |
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150 | if (right->price <= left->price) { |
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151 | // Route with (nRow,nCol) path is cheaper |
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152 | step = right; |
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153 | this->route[nRow] = nCol; |
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154 | pd.setValue(this->route.size()); |
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155 | if (firstStep) { |
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156 | check = left->price; |
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157 | firstStep = false; |
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158 | } |
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159 | } else { |
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160 | // Route without (nRow,nCol) path is cheaper |
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161 | step = left; |
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162 | qApp->processEvents(); |
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163 | if (firstStep) { |
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164 | check = right->price; |
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165 | firstStep = false; |
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166 | } |
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167 | } |
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168 | } |
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169 | |
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170 | if (!root && !pd.wasCanceled()) { |
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171 | pd.reset(); |
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172 | QMessageBox(QMessageBox::Warning,tr("Solution Result"),tr("Unable to find solution.\nMaybe, this task has no solutions."),QMessageBox::Ok,parent).exec(); |
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173 | } |
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174 | |
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175 | qApp->processEvents(); |
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176 | |
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177 | if (root) { |
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178 | route = this->route; |
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179 | mayNotBeOptimal = (check < step->price); |
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180 | } |
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181 | return root; |
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182 | } |
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183 | |
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184 | CTSPSolver::~CTSPSolver() |
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185 | { |
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186 | if (root != NULL) |
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187 | deleteTree(root); |
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188 | } |
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189 | |
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190 | /* Privates **********************************************************/ |
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191 | |
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192 | double CTSPSolver::align(TMatrix &matrix) |
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193 | { |
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194 | double r = 0; |
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195 | double min; |
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196 | for (int k = 0; k < nCities; k++) { |
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197 | min = findMinInRow(k,matrix); |
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198 | if (min > 0) { |
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199 | r += min; |
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200 | subRow(matrix,k,min); |
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201 | } |
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202 | } |
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203 | for (int k = 0; k < nCities; k++) { |
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204 | min = findMinInCol(k,matrix); |
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205 | if (min > 0) { |
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206 | r += min; |
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207 | subCol(matrix,k,min); |
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208 | } |
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209 | } |
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210 | return r; |
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211 | } |
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212 | |
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213 | void CTSPSolver::cleanup() |
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214 | { |
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215 | QApplication::setOverrideCursor(QCursor(Qt::WaitCursor)); |
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216 | route.clear(); |
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217 | mayNotBeOptimal = false; |
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218 | if (root != NULL) |
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219 | deleteTree(root); |
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220 | QApplication::restoreOverrideCursor(); |
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221 | } |
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222 | |
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223 | void CTSPSolver::deleteTree(SStep *&root) |
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224 | { |
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225 | if (root == NULL) |
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226 | return; |
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227 | SStep *step = root; |
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228 | SStep *parent; |
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229 | forever { |
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230 | if (step->plNode != NULL) { |
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231 | // We have left child node - going inside it |
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232 | step = step->plNode; |
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233 | step->pNode->plNode = NULL; |
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234 | continue; |
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235 | } else if (step->prNode != NULL) { |
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236 | // We have right child node - going inside it |
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237 | step = step->prNode; |
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238 | step->pNode->prNode = NULL; |
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239 | continue; |
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240 | } else { |
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241 | // We have no child nodes. Deleting current one. |
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242 | parent = step->pNode; |
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243 | delete step; |
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244 | if (parent != NULL) { |
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245 | // Going back to the parent node. |
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246 | step = parent; |
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247 | } else { |
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248 | // We came back to the root node. Finishing. |
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249 | root = NULL; |
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250 | break; |
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251 | } |
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252 | } |
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253 | } |
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254 | } |
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255 | |
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256 | QList<SCandidate> CTSPSolver::findCandidate(const TMatrix &matrix, int &nRow, int &nCol) const |
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257 | { |
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258 | nRow = -1; |
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259 | nCol = -1; |
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260 | QList<SCandidate> alts; |
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261 | SCandidate cand; |
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262 | double h = -1; |
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263 | double sum; |
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264 | for (int r = 0; r < nCities; r++) |
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265 | for (int c = 0; c < nCities; c++) |
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266 | // if ((matrix.at(r).at(c) == 0) && !forbidden.values(r).contains(c)) { |
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267 | if (matrix.at(r).at(c) == 0) { |
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268 | sum = findMinInRow(r,matrix,c) + findMinInCol(c,matrix,r); |
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269 | if (sum > h) { |
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270 | h = sum; |
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271 | nRow = r; |
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272 | nCol = c; |
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273 | alts.clear(); |
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274 | } else if ((sum == h) && !hasSubCycles(r,c)) { |
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275 | cand.nRow = r; |
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276 | cand.nCol = c; |
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277 | alts.append(cand); |
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278 | } |
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279 | } |
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280 | return alts; |
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281 | } |
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282 | |
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283 | double CTSPSolver::findMinInCol(int nCol, const TMatrix &matrix, int exr) const |
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284 | { |
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285 | double min = INFINITY; |
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286 | for (int k = 0; k < nCities; k++) |
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287 | if ((k != exr) && (min > matrix.at(k).at(nCol))) |
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288 | min = matrix.at(k).at(nCol); |
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289 | return min == INFINITY ? 0 : min; |
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290 | } |
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291 | |
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292 | double CTSPSolver::findMinInRow(int nRow, const TMatrix &matrix, int exc) const |
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293 | { |
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294 | double min = INFINITY; |
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295 | for (int k = 0; k < nCities; k++) |
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296 | if (((k != exc)) && (min > matrix.at(nRow).at(k))) |
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297 | min = matrix.at(nRow).at(k); |
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298 | return min == INFINITY ? 0 : min; |
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299 | } |
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300 | |
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301 | bool CTSPSolver::hasSubCycles(int nRow, int nCol) const |
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302 | { |
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303 | if ((nRow < 0) || (nCol < 0) || route.isEmpty() || !(route.size() < nCities - 1) || !route.contains(nCol)) |
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304 | return false; |
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305 | int i = nCol; |
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306 | while (true) { |
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307 | if ((i = route[i]) == nRow) |
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308 | return true; |
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309 | if (!route.contains(i)) |
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310 | return false; |
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311 | } |
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312 | return false; |
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313 | } |
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314 | |
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315 | void CTSPSolver::subCol(TMatrix &matrix, int nCol, double val) |
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316 | { |
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317 | for (int k = 0; k < nCities; k++) |
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318 | if (k != nCol) |
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319 | matrix[k][nCol] -= val; |
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320 | } |
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321 | |
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322 | void CTSPSolver::subRow(TMatrix &matrix, int nRow, double val) |
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323 | { |
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324 | for (int k = 0; k < nCities; k++) |
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325 | if (k != nRow) |
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326 | matrix[nRow][k] -= val; |
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327 | } |
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