1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using HeuristicLab.Analysis;
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23 | using HeuristicLab.Common;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Encodings.PermutationEncoding;
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26 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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27 |
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28 | namespace HeuristicLab.Problems.TravelingSalesman {
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29 | /// <summary>
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30 | /// An operator for analyzing the diversity of solutions of Traveling Salesman Problems given in path representation.
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31 | /// </summary>
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32 | [Item("TSPPopulationDiversityAnalyzer", "An operator for analyzing the diversity of solutions of Traveling Salesman Problems given in path representation.")]
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33 | [StorableClass]
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34 | public sealed class TSPPopulationDiversityAnalyzer : PopulationDiversityAnalyzer<Permutation> {
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35 | [StorableConstructor]
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36 | private TSPPopulationDiversityAnalyzer(bool deserializing) : base(deserializing) { }
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37 | private TSPPopulationDiversityAnalyzer(TSPPopulationDiversityAnalyzer original, Cloner cloner) : base(original, cloner) { }
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38 | public TSPPopulationDiversityAnalyzer() : base() { }
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39 |
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40 | public override IDeepCloneable Clone(Cloner cloner) {
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41 | return new TSPPopulationDiversityAnalyzer(this, cloner);
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42 | }
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43 |
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44 | protected override double[,] CalculateSimilarities(Permutation[] solutions) {
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45 | int count = solutions.Length;
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46 | double[,] similarities = new double[count, count];
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47 | int[][] edges = new int[count][];
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48 |
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49 | for (int i = 0; i < count; i++)
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50 | edges[i] = CalculateEdgesVector(solutions[i]);
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51 |
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52 | for (int i = 0; i < count; i++) {
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53 | similarities[i, i] = 1;
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54 | for (int j = i + 1; j < count; j++) {
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55 | similarities[i, j] = CalculateSimilarity(edges[i], edges[j]);
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56 | similarities[j, i] = similarities[i, j];
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57 | }
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58 | }
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59 | return similarities;
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60 | }
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61 |
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62 | private int[] CalculateEdgesVector(Permutation permutation) {
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63 | // transform path representation into adjacency representation
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64 | int[] edgesVector = new int[permutation.Length];
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65 | for (int i = 0; i < permutation.Length - 1; i++)
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66 | edgesVector[permutation[i]] = permutation[i + 1];
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67 | edgesVector[permutation[permutation.Length - 1]] = permutation[0];
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68 | return edgesVector;
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69 | }
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70 |
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71 | private double CalculateSimilarity(int[] edgesA, int[] edgesB) {
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72 | // calculate relative number of identical edges
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73 | int identicalEdges = 0;
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74 | for (int i = 0; i < edgesA.Length; i++) {
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75 | if ((edgesA[i] == edgesB[i]) || (edgesA[edgesB[i]] == i))
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76 | identicalEdges++;
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77 | }
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78 | return ((double)identicalEdges) / edgesA.Length;
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79 | }
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80 | }
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81 | }
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