1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2018 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.Common;
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23 | using HeuristicLab.Core;
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24 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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25 |
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26 | namespace HeuristicLab.Problems.VehicleRouting.Encodings.Zhu {
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27 | [Item("ZhuHeuristicCrossover1", "The Zhu Heuristic Crossover (Version 1). 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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28 | [StorableClass]
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29 | public sealed class ZhuHeuristicCrossover1 : ZhuCrossover {
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30 | [StorableConstructor]
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31 | private ZhuHeuristicCrossover1(bool deserializing) : base(deserializing) { }
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32 |
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33 | public ZhuHeuristicCrossover1()
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34 | : base() {
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35 | }
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36 |
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37 | public override IDeepCloneable Clone(Cloner cloner) {
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38 | return new ZhuHeuristicCrossover1(this, cloner);
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39 | }
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40 |
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41 | private ZhuHeuristicCrossover1(ZhuHeuristicCrossover1 original, Cloner cloner)
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42 | : base(original, cloner) {
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43 | }
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44 |
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45 | private void Swap(ZhuEncoding individual, int city1, int city2) {
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46 | int index1 = individual.IndexOf(city1);
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47 | int index2 = individual.IndexOf(city2);
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48 |
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49 | int temp = individual[index1];
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50 | individual[index1] = individual[index2];
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51 | individual[index2] = temp;
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52 | }
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53 |
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54 | protected override ZhuEncoding Crossover(IRandom random, ZhuEncoding parent1, ZhuEncoding parent2) {
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55 | parent1 = parent1.Clone() as ZhuEncoding;
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56 | parent2 = parent2.Clone() as ZhuEncoding;
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57 |
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58 | ZhuEncoding child = parent2.Clone() as ZhuEncoding;
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59 |
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60 | if (parent1.Length != parent2.Length)
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61 | return child;
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62 |
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63 | int breakPoint = random.Next(child.Length);
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64 | int i = breakPoint;
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65 | int predecessor = breakPoint - 1;
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66 | if (predecessor < 0)
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67 | predecessor = predecessor + child.Length;
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68 |
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69 | while (i != predecessor) {
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70 | if (i == breakPoint) {
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71 | child[i] = parent1[i];
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72 | Swap(parent2, parent2[i], parent1[i]);
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73 | }
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74 |
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75 | if (ProblemInstance.GetDistance(
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76 | child[i] + 1, parent1[(i + 1) % child.Length] + 1, child)
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77 | <
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78 | ProblemInstance.GetDistance(
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79 | child[i] + 1, parent2[(i + 1) % child.Length] + 1, child)) {
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80 | child[(i + 1) % child.Length] = parent1[(i + 1) % child.Length];
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81 | Swap(parent2, parent2[(i + 1) % child.Length], parent1[(i + 1) % child.Length]);
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82 | } else {
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83 | child[(i + 1) % child.Length] = parent2[(i + 1) % child.Length];
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84 | Swap(parent1, parent1[(i + 1) % child.Length], parent2[(i + 1) % child.Length]);
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85 | }
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86 |
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87 | i = (i + 1) % child.Length;
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88 | }
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89 |
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90 | return child;
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91 | }
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92 | }
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93 | }
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