1 | using HeuristicLab.Common;
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2 | using HeuristicLab.Core;
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3 | using HeuristicLab.Data;
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4 | using HeuristicLab.Encodings.IntegerVectorEncoding;
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5 | using HeuristicLab.Encodings.RealVectorEncoding;
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6 | using HeuristicLab.Operators;
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7 | using HeuristicLab.Optimization;
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8 | using HeuristicLab.Parameters;
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9 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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10 | using System;
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11 |
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12 | namespace HeuristicLab.Problems.MetaOptimization {
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13 | /// <summary>
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14 | ///
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15 | /// </summary>
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16 | [Item("ParameterConfigurationCrossover", "TODO")]
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17 | [StorableClass]
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18 | public class ParameterConfigurationCrossover : SingleSuccessorOperator, IParameterConfigurationOperator, IParameterConfigurationCrossover {
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19 | public override bool CanChangeName {
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20 | get { return false; }
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21 | }
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22 |
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23 | public ILookupParameter<IRandom> RandomParameter {
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24 | get { return (LookupParameter<IRandom>)Parameters["Random"]; }
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25 | }
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26 | public ILookupParameter<ItemArray<ParameterConfigurationTree>> ParentsParameter {
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27 | get { return (ScopeTreeLookupParameter<ParameterConfigurationTree>)Parameters["Parents"]; }
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28 | }
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29 | public ILookupParameter<ParameterConfigurationTree> ChildParameter {
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30 | get { return (ILookupParameter<ParameterConfigurationTree>)Parameters["Child"]; }
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31 | }
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32 |
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33 | public IValueLookupParameter<IIntValueCrossover> IntValueCrossoverParameter {
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34 | get { return (IValueLookupParameter<IIntValueCrossover>)Parameters[MetaOptimizationProblem.IntValueCrossoverParameterName]; }
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35 | }
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36 | public IValueLookupParameter<IDoubleValueCrossover> DoubleValueCrossoverParameter {
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37 | get { return (IValueLookupParameter<IDoubleValueCrossover>)Parameters[MetaOptimizationProblem.DoubleValueCrossoverParameterName]; }
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38 | }
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39 |
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40 | /// <summary>
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41 | /// Whether the problem is a maximization or minimization problem.
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42 | /// </summary>
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43 | public ValueLookupParameter<BoolValue> MaximizationParameter {
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44 | get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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45 | }
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46 |
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47 | /// <summary>
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48 | /// The quality of the parents.
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49 | /// </summary>
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50 | public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
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51 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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52 | }
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53 |
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54 | [StorableConstructor]
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55 | protected ParameterConfigurationCrossover(bool deserializing) : base(deserializing) { }
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56 | protected ParameterConfigurationCrossover(ParameterConfigurationCrossover original, Cloner cloner) : base(original, cloner) { }
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57 | public ParameterConfigurationCrossover()
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58 | : base() {
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59 | Parameters.Add(new LookupParameter<IRandom>("Random", "The pseudo random number generator which should be used for stochastic crossover operators."));
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60 | Parameters.Add(new ScopeTreeLookupParameter<ParameterConfigurationTree>("Parents", "The parent vectors which should be crossed."));
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61 | Parameters.Add(new LookupParameter<ParameterConfigurationTree>("Child", "The child vector resulting from the crossover."));
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62 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "Whether the problem is a maximization problem or not."));
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63 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The quality values of the parents."));
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64 | Parameters.Add(new ValueLookupParameter<IIntValueCrossover>(MetaOptimizationProblem.IntValueCrossoverParameterName, ""));
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65 | Parameters.Add(new ValueLookupParameter<IDoubleValueCrossover>(MetaOptimizationProblem.DoubleValueCrossoverParameterName, ""));
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66 | }
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67 | public override IDeepCloneable Clone(Cloner cloner) {
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68 | return new ParameterConfigurationCrossover(this, cloner);
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69 | }
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70 |
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71 | public override IOperation Apply() {
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72 | if (MaximizationParameter.ActualValue == null) throw new InvalidOperationException("HeuristicCrossover: Parameter " + MaximizationParameter.ActualName + " could not be found.");
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73 | if (QualityParameter.ActualValue == null || QualityParameter.ActualValue.Length != 2) throw new InvalidOperationException("ParameterConfigurationCrossover: Parameter " + QualityParameter.ActualName + " could not be found, or not in the same quantity as there are parents.");
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74 | ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;
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75 | bool maximization = MaximizationParameter.ActualValue.Value;
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76 |
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77 | ParameterConfigurationTree child1;
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78 | ParameterConfigurationTree child2;
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79 |
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80 | if (maximization && qualities[0].Value >= qualities[1].Value || !maximization && qualities[0].Value <= qualities[1].Value) {
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81 | child1 = (ParameterConfigurationTree)ParentsParameter.ActualValue[0].Clone();
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82 | child2 = (ParameterConfigurationTree)ParentsParameter.ActualValue[1];
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83 | } else {
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84 | child1 = (ParameterConfigurationTree)ParentsParameter.ActualValue[1].Clone();
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85 | child2 = (ParameterConfigurationTree)ParentsParameter.ActualValue[0];
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86 | }
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87 |
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88 | child1.Cross(RandomParameter.ActualValue, child2, Cross, IntValueCrossoverParameter.ActualValue, DoubleValueCrossoverParameter.ActualValue);
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89 | this.ChildParameter.ActualValue = child1;
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90 |
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91 | return base.Apply();
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92 | }
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93 |
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94 | public static void Apply(IRandom random, IOptimizable configuartion, IOptimizable other, IIntValueCrossover intValueCrossover, IDoubleValueCrossover doubleValueCrossover) {
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95 | configuartion.Cross(random, other, Cross, intValueCrossover, doubleValueCrossover);
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96 | }
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97 |
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98 | private static void Cross(IRandom random, IOptimizable configuartion, IOptimizable other, IIntValueCrossover intValueCrossover, IDoubleValueCrossover doubleValueCrossover) {
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99 | var vc = configuartion as IValueConfiguration;
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100 | var pc = configuartion as IParameterConfiguration;
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101 | if (vc != null) {
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102 | var value = vc.ActualValue.Value;
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103 | var range = vc.RangeConstraint;
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104 |
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105 | if (value is IntValue) {
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106 | intValueCrossover.Apply(random, (IntValue)value, (IntValue)((IValueConfiguration)other).ActualValue.Value, (IntValueRange)range);
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107 | } else if (value is PercentValue) {
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108 | doubleValueCrossover.Apply(random, (PercentValue)value, (DoubleValue)((IValueConfiguration)other).ActualValue.Value, ((PercentValueRange)range).AsDoubleValueRange());
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109 | } else if (value is DoubleValue) {
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110 | doubleValueCrossover.Apply(random, (DoubleValue)value, (DoubleValue)((IValueConfiguration)other).ActualValue.Value, (DoubleValueRange)range);
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111 | }
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112 | } else if (pc != null) {
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113 | if (random.NextDouble() > 0.5) {
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114 | pc.ActualValueConfigurationIndex = ((ParameterConfiguration)other).ActualValueConfigurationIndex;
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115 | }
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116 | pc.ActualValue = pc.ValueConfigurations[pc.ActualValueConfigurationIndex].ActualValue;
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117 | }
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118 | }
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119 |
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120 | private IntValue CrossInteger(IParameterConfiguration parameter1, IParameterConfiguration parameter2) {
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121 | IntegerVector integerChild = HeuristicLab.Encodings.IntegerVectorEncoding.DiscreteCrossover.Apply(
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122 | RandomParameter.ActualValue,
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123 | new IntegerVector(new IntArray(new int[] { ((IntValue)parameter1.ActualValue.Value).Value })),
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124 | new IntegerVector(new IntArray(new int[] { ((IntValue)parameter2.ActualValue.Value).Value })));
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125 | return new IntValue(integerChild[0]);
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126 | }
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127 |
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128 | }
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129 | }
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