1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 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.Data;
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25 | using HeuristicLab.Operators;
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26 | using HeuristicLab.Optimization.Operators;
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27 | using HeuristicLab.Parameters;
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28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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29 |
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30 | namespace HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm {
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31 | /// <summary>
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32 | /// An operator which represents the main loop of an offspring selection genetic algorithm.
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33 | /// </summary>
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34 | [Item("OffspringSelectionGeneticAlgorithmMainLoop", "An operator which represents the main loop of an offspring selection genetic algorithm.")]
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35 | [StorableType("2288F854-9419-4CFF-A9AE-8FEC69ED8BDF")]
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36 | public sealed class OffspringSelectionGeneticAlgorithmMainLoop : AlgorithmOperator {
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37 | #region Parameter properties
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38 | public ValueLookupParameter<IRandom> RandomParameter {
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39 | get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
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40 | }
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41 | public ValueLookupParameter<BoolValue> MaximizationParameter {
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42 | get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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43 | }
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44 | public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
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45 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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46 | }
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47 | public ValueLookupParameter<IOperator> SelectorParameter {
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48 | get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
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49 | }
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50 | public ValueLookupParameter<IOperator> CrossoverParameter {
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51 | get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
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52 | }
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53 | public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
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54 | get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
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55 | }
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56 | public ValueLookupParameter<IOperator> MutatorParameter {
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57 | get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
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58 | }
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59 | public ValueLookupParameter<IOperator> EvaluatorParameter {
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60 | get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
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61 | }
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62 | public ValueLookupParameter<IntValue> ElitesParameter {
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63 | get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
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64 | }
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65 | public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
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66 | get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
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67 | }
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68 | public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
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69 | get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
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70 | }
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71 | public ValueLookupParameter<VariableCollection> ResultsParameter {
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72 | get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
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73 | }
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74 | public ValueLookupParameter<IOperator> AnalyzerParameter {
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75 | get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
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76 | }
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77 | public ValueLookupParameter<DoubleValue> SuccessRatioParameter {
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78 | get { return (ValueLookupParameter<DoubleValue>)Parameters["SuccessRatio"]; }
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79 | }
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80 | public LookupParameter<DoubleValue> ComparisonFactorParameter {
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81 | get { return (LookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
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82 | }
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83 | public ValueLookupParameter<DoubleValue> ComparisonFactorStartParameter {
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84 | get { return (ValueLookupParameter<DoubleValue>)Parameters["ComparisonFactorStart"]; }
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85 | }
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86 | public ValueLookupParameter<IOperator> ComparisonFactorModifierParameter {
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87 | get { return (ValueLookupParameter<IOperator>)Parameters["ComparisonFactorModifier"]; }
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88 | }
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89 | public ValueLookupParameter<DoubleValue> MaximumSelectionPressureParameter {
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90 | get { return (ValueLookupParameter<DoubleValue>)Parameters["MaximumSelectionPressure"]; }
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91 | }
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92 | public ValueLookupParameter<BoolValue> OffspringSelectionBeforeMutationParameter {
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93 | get { return (ValueLookupParameter<BoolValue>)Parameters["OffspringSelectionBeforeMutation"]; }
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94 | }
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95 | public LookupParameter<IntValue> EvaluatedSolutionsParameter {
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96 | get { return (LookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
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97 | }
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98 | public IValueLookupParameter<BoolValue> FillPopulationWithParentsParameter {
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99 | get { return (IValueLookupParameter<BoolValue>)Parameters["FillPopulationWithParents"]; }
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100 | }
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101 | #endregion
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102 |
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103 | [StorableConstructor]
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104 | private OffspringSelectionGeneticAlgorithmMainLoop(bool deserializing) : base(deserializing) { }
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105 | private OffspringSelectionGeneticAlgorithmMainLoop(OffspringSelectionGeneticAlgorithmMainLoop original, Cloner cloner)
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106 | : base(original, cloner) {
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107 | }
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108 | public override IDeepCloneable Clone(Cloner cloner) {
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109 | return new OffspringSelectionGeneticAlgorithmMainLoop(this, cloner);
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110 | }
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111 | public OffspringSelectionGeneticAlgorithmMainLoop()
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112 | : base() {
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113 | Initialize();
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114 | }
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115 |
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116 | [StorableHook(HookType.AfterDeserialization)]
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117 | private void AfterDeserialization() {
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118 | // BackwardsCompatibility3.3
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119 | #region Backwards compatible code, remove with 3.4
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120 | if (!Parameters.ContainsKey("ReevaluateElites")) {
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121 | Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
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122 | }
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123 | if (!Parameters.ContainsKey("FillPopulationWithParents"))
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124 | Parameters.Add(new ValueLookupParameter<BoolValue>("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
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125 | #endregion
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126 | }
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127 |
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128 | private void Initialize() {
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129 | #region Create parameters
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130 | Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
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131 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
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132 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
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133 | Parameters.Add(new ValueLookupParameter<DoubleValue>("BestKnownQuality", "The best known quality value found so far."));
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134 | Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
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135 | Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
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136 | Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
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137 | Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
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138 | Parameters.Add(new ValueLookupParameter<IOperator>("Evaluator", "The operator used to evaluate solutions. This operator is executed in parallel, if an engine is used which supports parallelization."));
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139 | Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
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140 | Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
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141 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
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142 | Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
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143 | Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
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144 | Parameters.Add(new ValueLookupParameter<DoubleValue>("SuccessRatio", "The ratio of successful to total children that should be achieved."));
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145 | Parameters.Add(new LookupParameter<DoubleValue>("ComparisonFactor", "The comparison factor is used to determine whether the offspring should be compared to the better parent, the worse parent or a quality value linearly interpolated between them. It is in the range [0;1]."));
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146 | Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactorStart", "The initial value for the comparison factor."));
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147 | Parameters.Add(new ValueLookupParameter<IOperator>("ComparisonFactorModifier", "The operator used to modify the comparison factor."));
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148 | Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumSelectionPressure", "The maximum selection pressure that terminates the algorithm."));
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149 | Parameters.Add(new ValueLookupParameter<BoolValue>("OffspringSelectionBeforeMutation", "True if the offspring selection step should be applied before mutation, false if it should be applied after mutation."));
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150 | Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
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151 | Parameters.Add(new ValueLookupParameter<BoolValue>("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
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152 | #endregion
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153 |
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154 | #region Create operators
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155 | VariableCreator variableCreator = new VariableCreator();
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156 | Assigner comparisonFactorInitializer = new Assigner();
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157 | Placeholder analyzer1 = new Placeholder();
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158 | ResultsCollector resultsCollector1 = new ResultsCollector();
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159 | OffspringSelectionGeneticAlgorithmMainOperator mainOperator = new OffspringSelectionGeneticAlgorithmMainOperator();
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160 | IntCounter generationsCounter = new IntCounter();
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161 | Comparator maxGenerationsComparator = new Comparator();
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162 | Comparator maxSelectionPressureComparator = new Comparator();
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163 | Comparator maxEvaluatedSolutionsComparator = new Comparator();
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164 | Placeholder comparisonFactorModifier = new Placeholder();
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165 | Placeholder analyzer2 = new Placeholder();
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166 | ConditionalBranch conditionalBranch1 = new ConditionalBranch();
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167 | ConditionalBranch conditionalBranch2 = new ConditionalBranch();
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168 | ConditionalBranch conditionalBranch3 = new ConditionalBranch();
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169 |
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170 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class OffspringSelectionGeneticAlgorithm expects this to be called Generations
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171 | variableCreator.CollectedValues.Add(new ValueParameter<DoubleValue>("SelectionPressure", new DoubleValue(0)));
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172 | variableCreator.CollectedValues.Add(new ValueParameter<DoubleValue>("CurrentSuccessRatio", new DoubleValue(0)));
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173 |
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174 | comparisonFactorInitializer.Name = "Initialize ComparisonFactor (placeholder)";
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175 | comparisonFactorInitializer.LeftSideParameter.ActualName = ComparisonFactorParameter.Name;
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176 | comparisonFactorInitializer.RightSideParameter.ActualName = ComparisonFactorStartParameter.Name;
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177 |
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178 | analyzer1.Name = "Analyzer (placeholder)";
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179 | analyzer1.OperatorParameter.ActualName = AnalyzerParameter.Name;
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180 |
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181 | resultsCollector1.CopyValue = new BoolValue(false);
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182 | resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
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183 | resultsCollector1.CollectedValues.Add(new LookupParameter<DoubleValue>("Current Comparison Factor", null, ComparisonFactorParameter.Name));
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184 | resultsCollector1.CollectedValues.Add(new LookupParameter<DoubleValue>("Current Selection Pressure", "Displays the rising selection pressure during a generation.", "SelectionPressure"));
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185 | resultsCollector1.CollectedValues.Add(new LookupParameter<DoubleValue>("Current Success Ratio", "Indicates how many successful children were already found during a generation (relative to the population size).", "CurrentSuccessRatio"));
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186 | resultsCollector1.ResultsParameter.ActualName = ResultsParameter.Name;
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187 |
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188 | mainOperator.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
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189 | mainOperator.CrossoverParameter.ActualName = CrossoverParameter.Name;
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190 | mainOperator.CurrentSuccessRatioParameter.ActualName = "CurrentSuccessRatio";
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191 | mainOperator.ElitesParameter.ActualName = ElitesParameter.Name;
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192 | mainOperator.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name;
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193 | mainOperator.EvaluatedSolutionsParameter.ActualName = EvaluatedSolutionsParameter.Name;
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194 | mainOperator.EvaluatorParameter.ActualName = EvaluatorParameter.Name;
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195 | mainOperator.MaximizationParameter.ActualName = MaximizationParameter.Name;
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196 | mainOperator.MaximumSelectionPressureParameter.ActualName = MaximumSelectionPressureParameter.Name;
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197 | mainOperator.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
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198 | mainOperator.MutatorParameter.ActualName = MutatorParameter.Name;
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199 | mainOperator.OffspringSelectionBeforeMutationParameter.ActualName = OffspringSelectionBeforeMutationParameter.Name;
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200 | mainOperator.QualityParameter.ActualName = QualityParameter.Name;
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201 | mainOperator.RandomParameter.ActualName = RandomParameter.Name;
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202 | mainOperator.SelectionPressureParameter.ActualName = "SelectionPressure";
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203 | mainOperator.SelectorParameter.ActualName = SelectorParameter.Name;
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204 | mainOperator.SuccessRatioParameter.ActualName = SuccessRatioParameter.Name;
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205 | mainOperator.FillPopulationWithParentsParameter.ActualName = FillPopulationWithParentsParameter.Name;
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206 |
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207 | generationsCounter.Increment = new IntValue(1);
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208 | generationsCounter.ValueParameter.ActualName = "Generations";
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209 |
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210 | maxGenerationsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
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211 | maxGenerationsComparator.LeftSideParameter.ActualName = "Generations";
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212 | maxGenerationsComparator.ResultParameter.ActualName = "TerminateMaximumGenerations";
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213 | maxGenerationsComparator.RightSideParameter.ActualName = MaximumGenerationsParameter.Name;
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214 |
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215 | maxSelectionPressureComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
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216 | maxSelectionPressureComparator.LeftSideParameter.ActualName = "SelectionPressure";
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217 | maxSelectionPressureComparator.ResultParameter.ActualName = "TerminateSelectionPressure";
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218 | maxSelectionPressureComparator.RightSideParameter.ActualName = MaximumSelectionPressureParameter.Name;
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219 |
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220 | maxEvaluatedSolutionsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
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221 | maxEvaluatedSolutionsComparator.LeftSideParameter.ActualName = EvaluatedSolutionsParameter.Name;
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222 | maxEvaluatedSolutionsComparator.ResultParameter.ActualName = "TerminateEvaluatedSolutions";
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223 | maxEvaluatedSolutionsComparator.RightSideParameter.ActualName = "MaximumEvaluatedSolutions";
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224 |
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225 | comparisonFactorModifier.Name = "Update ComparisonFactor (placeholder)";
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226 | comparisonFactorModifier.OperatorParameter.ActualName = ComparisonFactorModifierParameter.Name;
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227 |
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228 | analyzer2.Name = "Analyzer (placeholder)";
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229 | analyzer2.OperatorParameter.ActualName = AnalyzerParameter.Name;
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230 |
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231 | conditionalBranch1.Name = "MaximumSelectionPressure reached?";
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232 | conditionalBranch1.ConditionParameter.ActualName = "TerminateSelectionPressure";
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233 |
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234 | conditionalBranch2.Name = "MaximumGenerations reached?";
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235 | conditionalBranch2.ConditionParameter.ActualName = "TerminateMaximumGenerations";
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236 |
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237 | conditionalBranch3.Name = "MaximumEvaluatedSolutions reached?";
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238 | conditionalBranch3.ConditionParameter.ActualName = "TerminateEvaluatedSolutions";
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239 | #endregion
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240 |
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241 | #region Create operator graph
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242 | OperatorGraph.InitialOperator = variableCreator;
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243 | variableCreator.Successor = comparisonFactorInitializer;
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244 | comparisonFactorInitializer.Successor = analyzer1;
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245 | analyzer1.Successor = resultsCollector1;
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246 | resultsCollector1.Successor = mainOperator;
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247 | mainOperator.Successor = generationsCounter;
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248 | generationsCounter.Successor = maxGenerationsComparator;
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249 | maxGenerationsComparator.Successor = maxSelectionPressureComparator;
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250 | maxSelectionPressureComparator.Successor = maxEvaluatedSolutionsComparator;
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251 | maxEvaluatedSolutionsComparator.Successor = comparisonFactorModifier;
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252 | comparisonFactorModifier.Successor = analyzer2;
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253 | analyzer2.Successor = conditionalBranch1;
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254 | conditionalBranch1.FalseBranch = conditionalBranch2;
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255 | conditionalBranch1.TrueBranch = null;
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256 | conditionalBranch1.Successor = null;
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257 | conditionalBranch2.FalseBranch = conditionalBranch3;
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258 | conditionalBranch2.TrueBranch = null;
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259 | conditionalBranch2.Successor = null;
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260 | conditionalBranch3.FalseBranch = mainOperator;
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261 | conditionalBranch3.TrueBranch = null;
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262 | conditionalBranch3.Successor = null;
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263 | #endregion
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264 | }
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265 | }
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266 | }
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