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 System;
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23 | using HeuristicLab.Common;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Data;
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26 | using HeuristicLab.Parameters;
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27 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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28 |
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29 | namespace HeuristicLab.Encodings.RealVectorEncoding {
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30 | /// <summary>
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31 | /// The uniform all positions arithmetic crossover constructs an offspring by calculating x = alpha * p1 + (1-alpha) * p2 for every position x in the vector.
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32 | /// </summary>
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33 | /// <remarks>
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34 | /// By setting alpha = 0.5 it is the same as the <see cref="AverageCrossover"/>, but only on two parents.
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35 | /// It is implemented as described in Michalewicz, Z. 1999. Genetic Algorithms + Data Structures = Evolution Programs. Third, Revised and Extended Edition, Spring-Verlag Berlin Heidelberg.
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36 | /// </remarks>
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37 | [Item("UniformAllPositionsArithmeticCrossover", "The uniform all positions arithmetic crossover constructs an offspring by calculating x = alpha * p1 + (1-alpha) * p2 for every position x in the vector. Note that for alpha = 0.5 it is the same as the AverageCrossover. It is implemented as described in Michalewicz, Z. 1999. Genetic Algorithms + Data Structures = Evolution Programs. Third, Revised and Extended Edition, Spring-Verlag Berlin Heidelberg.")]
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38 | [StorableClass]
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39 | public class UniformAllPositionsArithmeticCrossover : RealVectorCrossover {
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40 | /// <summary>
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41 | /// The alpha parameter needs to be in the interval [0;1] and specifies how close the resulting offspring should be either to parent1 (alpha -> 0) or parent2 (alpha -> 1).
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42 | /// </summary>
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43 | public ValueLookupParameter<DoubleValue> AlphaParameter {
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44 | get { return (ValueLookupParameter<DoubleValue>)Parameters["Alpha"]; }
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45 | }
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46 |
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47 | /// <summary>
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48 | /// Initializes a new instance with one parameter (<c>Alpha</c>).
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49 | /// </summary>
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50 | public UniformAllPositionsArithmeticCrossover()
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51 | : base() {
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52 | Parameters.Add(new ValueLookupParameter<DoubleValue>("Alpha", "The alpha value in the range [0;1]", new DoubleValue(0.33)));
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53 | }
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54 |
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55 | /// <summary>
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56 | /// Performs the arithmetic crossover on all positions by calculating x = alpha * p1 + (1 - alpha) * p2.
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57 | /// </summary>
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58 | /// <exception cref="ArgumentException">Thrown when the parent vectors are of different length or alpha is outside the range [0;1].</exception>
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59 | /// <param name="random">The random number generator.</param>
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60 | /// <param name="parent1">The first parent vector.</param>
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61 | /// <param name="parent2">The second parent vector.</param>
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62 | /// <param name="alpha">The alpha parameter (<see cref="AlphaParameter"/>).</param>
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63 | /// <returns>The vector resulting from the crossover.</returns>
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64 | public static RealVector Apply(IRandom random, RealVector parent1, RealVector parent2, DoubleValue alpha) {
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65 | int length = parent1.Length;
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66 | if (length != parent2.Length) throw new ArgumentException("UniformAllPositionsArithmeticCrossover: The parent vectors are of different length.", "parent1");
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67 | if (alpha.Value < 0 || alpha.Value > 1) throw new ArgumentException("UniformAllPositionsArithmeticCrossover: Parameter alpha must be in the range [0;1]", "alpha");
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68 | RealVector result = new RealVector(length);
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69 | for (int i = 0; i < length; i++) {
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70 | result[i] = alpha.Value * parent1[i] + (1 - alpha.Value) * parent2[i];
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71 | }
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72 | return result;
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73 | }
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74 |
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75 | /// <summary>
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76 | /// Checks that there are exactly 2 parents, that the alpha parameter is not null and fowards the call to <see cref="Apply(IRandom, RealVector, DoubleArrrayData, DoubleValue)"/>.
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77 | /// </summary>
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78 | /// <exception cref="ArgumentException">Thrown when there are not exactly two parents.</exception>
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79 | /// <exception cref="InvalidOperationException">Thrown when the alpha parmeter could not be found.</exception>
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80 | /// <param name="random">The random number generator.</param>
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81 | /// <param name="parents">The collection of parents (must be of size 2).</param>
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82 | /// <returns>The vector resulting from the crossover.</returns>
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83 | protected override RealVector Cross(IRandom random, ItemArray<RealVector> parents) {
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84 | if (parents.Length != 2) throw new ArgumentException("UniformAllPositionsArithmeticCrossover: There must be exactly two parents.", "parents");
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85 | if (AlphaParameter.ActualValue == null) throw new InvalidOperationException("UniformAllPositionsArithmeticCrossover: Parameter " + AlphaParameter.ActualName + " could not be found.");
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86 | return Apply(random, parents[0], parents[1], AlphaParameter.ActualValue);
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87 | }
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88 | }
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89 | }
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