[12] | 1 | /* |
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[42] | 2 | * TSPSG: TSP Solver and Generator |
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[87] | 3 | * Copyright (C) 2007-2010 Lёppa <contacts[at]oleksii[dot]name> |
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[12] | 4 | * |
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| 5 | * $Id: tspsolver.cpp 90 2010-02-17 16:54:05Z 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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[65] | 26 | //! Class constructor |
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[13] | 27 | CTSPSolver::CTSPSolver() |
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[74] | 28 | : nCities(0), root(NULL) |
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[13] | 29 | { |
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| 30 | } |
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[12] | 31 | |
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[67] | 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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[13] | 37 | { |
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[67] | 38 | if (!root || route.isEmpty() || (route.size() != nCities)) |
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| 39 | return QString(); |
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[42] | 40 | |
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[67] | 41 | int i = 0; // We start from City 1 |
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[87] | 42 | QString path = tr("City %1").arg(1) + " -> "; |
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[67] | 43 | while ((i = route[i]) != 0) { |
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[87] | 44 | path += tr("City %1").arg(i + 1) + " -> "; |
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[67] | 45 | } |
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| 46 | // And finish in City 1, too |
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[87] | 47 | path += tr("City %1").arg(1); |
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[12] | 48 | |
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[67] | 49 | return path; |
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[12] | 50 | } |
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| 51 | |
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[67] | 52 | /*! |
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| 53 | * \brief Returns CTSPSolver's version ID. |
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| 54 | * \return A string: <b>\$Id: tspsolver.cpp 90 2010-02-17 16:54:05Z laleppa $</b>. |
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| 55 | */ |
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| 56 | QString CTSPSolver::getVersionId() |
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[12] | 57 | { |
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[67] | 58 | return QString("$Id: tspsolver.cpp 90 2010-02-17 16:54:05Z laleppa $"); |
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[42] | 59 | } |
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| 60 | |
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[67] | 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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[42] | 69 | { |
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[67] | 70 | return !mayNotBeOptimal; |
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[42] | 71 | } |
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| 72 | |
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[65] | 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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[66] | 78 | * \return Pointer to the root of the solution tree. |
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[65] | 79 | * |
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| 80 | * \todo TODO: Comment the algorithm. |
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| 81 | */ |
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[74] | 82 | SStep *CTSPSolver::solve(int numCities, TMatrix task, QWidget *parent) |
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[42] | 83 | { |
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[12] | 84 | if (numCities <= 1) |
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| 85 | return NULL; |
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[42] | 86 | cleanup(); |
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[13] | 87 | nCities = numCities; |
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[42] | 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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[87] | 91 | pb->setFormat(tr("%v of %m parts found")); |
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[42] | 92 | pd.setBar(pb); |
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| 93 | pd.setMaximum(nCities); |
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| 94 | pd.setMinimumDuration(1000); |
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[87] | 95 | pd.setLabelText(tr("Calculating optimal route...")); |
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| 96 | pd.setWindowTitle(tr("Solution Progress")); |
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[42] | 97 | pd.setWindowModality(Qt::ApplicationModal); |
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| 98 | pd.setValue(0); |
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| 99 | |
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[74] | 100 | SStep *step = new SStep(); |
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[13] | 101 | step->matrix = task; |
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[60] | 102 | step->price = align(step->matrix); |
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[13] | 103 | root = step; |
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[12] | 104 | |
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[74] | 105 | SStep *left, *right; |
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[42] | 106 | int nRow, nCol; |
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[60] | 107 | bool firstStep = true; |
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[89] | 108 | double check; |
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[60] | 109 | while (this->route.size() < nCities) { |
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[50] | 110 | // forbidden.clear(); |
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[60] | 111 | step->alts = findCandidate(step->matrix,nRow,nCol); |
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[42] | 112 | while (hasSubCycles(nRow,nCol)) { |
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[50] | 113 | // forbidden[nRow] = nCol; |
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[42] | 114 | step->matrix[nRow][nCol] = INFINITY; |
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| 115 | step->price += align(step->matrix); |
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[60] | 116 | step->alts = findCandidate(step->matrix,nRow,nCol); |
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[42] | 117 | } |
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| 118 | if ((nRow == -1) || (nCol == -1) || pd.wasCanceled()) { |
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[74] | 119 | cleanup(); |
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[42] | 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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[74] | 124 | right = new SStep(); |
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[90] | 125 | right->pNode = step; |
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[42] | 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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[74] | 139 | left = new SStep(); |
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[90] | 140 | left->pNode = step; |
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[42] | 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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[60] | 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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[42] | 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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[60] | 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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[42] | 167 | } |
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| 168 | } |
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| 169 | |
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| 170 | if (!root && !pd.wasCanceled()) { |
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[50] | 171 | pd.reset(); |
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[87] | 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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[42] | 173 | } |
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| 174 | |
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[50] | 175 | qApp->processEvents(); |
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| 176 | |
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[60] | 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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[42] | 181 | return root; |
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[12] | 182 | } |
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[60] | 183 | |
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[74] | 184 | CTSPSolver::~CTSPSolver() |
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| 185 | { |
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| 186 | if (root != NULL) |
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[90] | 187 | deleteTree(root); |
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[74] | 188 | } |
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| 189 | |
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[67] | 190 | /* Privates **********************************************************/ |
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| 191 | |
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[89] | 192 | double CTSPSolver::align(TMatrix &matrix) |
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[60] | 193 | { |
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[89] | 194 | double r = 0; |
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| 195 | double min; |
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[67] | 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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[60] | 202 | } |
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[67] | 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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[60] | 212 | |
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[67] | 213 | void CTSPSolver::cleanup() |
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| 214 | { |
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[78] | 215 | QApplication::setOverrideCursor(QCursor(Qt::WaitCursor)); |
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[67] | 216 | route.clear(); |
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| 217 | mayNotBeOptimal = false; |
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[74] | 218 | if (root != NULL) |
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[90] | 219 | deleteTree(root); |
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[78] | 220 | QApplication::restoreOverrideCursor(); |
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[60] | 221 | } |
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| 222 | |
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[90] | 223 | void CTSPSolver::deleteTree(SStep *&root) |
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[63] | 224 | { |
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[90] | 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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[74] | 254 | } |
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| 255 | |
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[76] | 256 | QList<SCandidate> CTSPSolver::findCandidate(const TMatrix &matrix, int &nRow, int &nCol) const |
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[74] | 257 | { |
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[67] | 258 | nRow = -1; |
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| 259 | nCol = -1; |
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[76] | 260 | QList<SCandidate> alts; |
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| 261 | SCandidate cand; |
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[89] | 262 | double h = -1; |
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| 263 | double sum; |
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[67] | 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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[74] | 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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[67] | 279 | } |
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| 280 | return alts; |
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[63] | 281 | } |
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| 282 | |
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[89] | 283 | double CTSPSolver::findMinInCol(int nCol, const TMatrix &matrix, int exr) const |
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[60] | 284 | { |
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[89] | 285 | double min = INFINITY; |
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[67] | 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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[60] | 290 | } |
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[67] | 291 | |
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[89] | 292 | double CTSPSolver::findMinInRow(int nRow, const TMatrix &matrix, int exc) const |
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[67] | 293 | { |
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[89] | 294 | double min = INFINITY; |
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[67] | 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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[71] | 301 | bool CTSPSolver::hasSubCycles(int nRow, int nCol) const |
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[67] | 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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[89] | 315 | void CTSPSolver::subCol(TMatrix &matrix, int nCol, double val) |
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[67] | 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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[89] | 322 | void CTSPSolver::subRow(TMatrix &matrix, int nRow, double val) |
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[67] | 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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