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.Core;
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23 | using HeuristicLab.Encodings.PermutationEncoding;
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24 | using HeuristicLab.Parameters;
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25 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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26 | using HeuristicLab.Data;
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27 | using System.Collections.Generic;
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28 |
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29 | namespace HeuristicLab.Problems.VehicleRouting.Encodings.Zhu {
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30 | [Item("ZhuHeuristicCrossover2", "The Zhu Heuristic Crossover (Version 2). It is implemented as described in Zhu, K.Q. (2000). A New Genetic Algorithm For VRPTW. Proceedings of the International Conference on Artificial Intelligence.")]
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31 | [StorableClass]
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32 | public sealed class ZhuHeuristicCrossover2 : ZhuCrossover {
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33 | [StorableConstructor]
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34 | private ZhuHeuristicCrossover2(bool deserializing) : base(deserializing) { }
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35 |
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36 | public ZhuHeuristicCrossover2()
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37 | : base() {
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38 | }
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39 |
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40 | protected override ZhuEncoding Crossover(IRandom random, ZhuEncoding parent1, ZhuEncoding parent2) {
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41 | List<int> p1 = new List<int>(parent1);
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42 | List<int> p2 = new List<int>(parent2);
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43 |
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44 | ZhuEncoding child = parent2.Clone() as ZhuEncoding;
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45 |
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46 | int breakPoint = random.Next(child.Length);
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47 | int i = breakPoint;
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48 | int predecessor = breakPoint - 1;
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49 | if (predecessor < 0)
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50 | predecessor = predecessor + child.Length;
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51 |
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52 | int parent1Index = i;
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53 | int parent2Index = i;
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54 |
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55 | while (i != predecessor) {
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56 | if (i == breakPoint) {
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57 | child[i] = p1[parent1Index];
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58 |
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59 | p1.Remove(child[i]);
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60 | if (parent1Index >= p1.Count)
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61 | parent1Index = 0;
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62 |
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63 | p2.Remove(child[i]);
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64 | if (parent2Index >= p2.Count)
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65 | parent2Index = 0;
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66 | }
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67 |
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68 | if (ProblemInstance.GetDistance(
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69 | child[i] + 1, p1[parent1Index] + 1)
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70 | <
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71 | ProblemInstance.GetDistance(
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72 | child[i] + 1, p2[parent2Index] + 1)) {
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73 | child[(i + 1) % child.Length] = p1[parent1Index];
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74 | } else {
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75 | child[(i + 1) % child.Length] = p2[parent2Index];
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76 | }
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77 |
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78 | p1.Remove(child[(i + 1) % child.Length]);
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79 | if (parent1Index >= p1.Count)
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80 | parent1Index = 0;
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81 |
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82 | p2.Remove(child[(i + 1) % child.Length]);
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83 | if (parent2Index >= p2.Count)
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84 | parent2Index = 0;
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85 |
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86 | i = (i + 1) % child.Length;
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87 | }
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88 |
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89 | return child;
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90 | }
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91 | }
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92 | }
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