1 | #region License Information |
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2 | /* HeuristicLab |
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3 | * Copyright (C) 2002-2019 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 System; |
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23 | using HeuristicLab.Common; |
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24 | using HeuristicLab.Core; |
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25 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; |
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26 | |
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27 | namespace HeuristicLab.Encodings.RealVectorEncoding { |
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28 | /// <summary> |
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29 | /// The average crossover (intermediate recombination) calculates the average or centroid of a number of parent vectors. |
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30 | /// </summary> |
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31 | /// <remarks> |
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32 | /// It is implemented as described by Beyer, H.-G. and Schwefel, H.-P. 2002. Evolution Strategies - A Comprehensive Introduction Natural Computing, 1, pp. 3-52. |
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33 | /// </remarks> |
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34 | [Item("AverageCrossover", "The average crossover (intermediate recombination) produces a new offspring by calculating in each position the average of a number of parents. It is implemented as described by Beyer, H.-G. and Schwefel, H.-P. 2002. Evolution Strategies - A Comprehensive Introduction Natural Computing, 1, pp. 3-52.")] |
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35 | [StorableClass] |
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36 | public class AverageCrossover : RealVectorCrossover { |
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37 | [StorableConstructor] |
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38 | protected AverageCrossover(bool deserializing) : base(deserializing) { } |
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39 | protected AverageCrossover(AverageCrossover original, Cloner cloner) : base(original, cloner) { } |
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40 | public AverageCrossover() : base() { } |
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41 | |
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42 | public override IDeepCloneable Clone(Cloner cloner) { |
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43 | return new AverageCrossover(this, cloner); |
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44 | } |
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45 | |
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46 | /// <summary> |
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47 | /// Performs the average crossover (intermediate recombination) on a list of parents. |
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48 | /// </summary> |
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49 | /// <exception cref="ArgumentException">Thrown when there is just one parent or when the parent vectors are of different length.</exception> |
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50 | /// <remarks> |
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51 | /// There can be more than two parents. |
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52 | /// </remarks> |
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53 | /// <param name="random">The random number generator.</param> |
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54 | /// <param name="parents">The list of parents.</param> |
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55 | /// <returns>The child vector (average) of the parents.</returns> |
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56 | public static RealVector Apply(IRandom random, ItemArray<RealVector> parents) { |
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57 | int length = parents[0].Length, parentsCount = parents.Length; |
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58 | if (parents.Length < 2) throw new ArgumentException("AverageCrossover: The number of parents is less than 2.", "parents"); |
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59 | RealVector result = new RealVector(length); |
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60 | try { |
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61 | double avg; |
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62 | for (int i = 0; i < length; i++) { |
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63 | avg = 0; |
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64 | for (int j = 0; j < parentsCount; j++) |
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65 | avg += parents[j][i]; |
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66 | result[i] = avg / (double)parentsCount; |
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67 | } |
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68 | } |
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69 | catch (IndexOutOfRangeException) { |
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70 | throw new ArgumentException("AverageCrossover: The parents' vectors are of different length.", "parents"); |
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71 | } |
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72 | |
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73 | return result; |
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74 | } |
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75 | |
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76 | /// <summary> |
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77 | /// Forwards the call to <see cref="Apply(IRandom, ItemArray<RealVector>)"/>. |
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78 | /// </summary> |
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79 | /// <param name="random">The random number generator.</param> |
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80 | /// <param name="parents">The list of parents.</param> |
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81 | /// <returns>The child vector (average) of the parents.</returns> |
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82 | protected override RealVector Cross(IRandom random, ItemArray<RealVector> parents) { |
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83 | return Apply(random, parents); |
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84 | } |
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85 | } |
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86 | } |
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