1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2012 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 System.Linq;
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24 | using HeuristicLab.Analysis;
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25 | using HeuristicLab.Common;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Data;
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28 | using HeuristicLab.Operators;
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29 | using HeuristicLab.Optimization;
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30 | using HeuristicLab.Optimization.Operators;
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31 | using HeuristicLab.Parameters;
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32 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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33 | using HeuristicLab.PluginInfrastructure;
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34 | using HeuristicLab.Random;
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35 |
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36 | namespace HeuristicLab.Algorithms.GeneticAlgorithm {
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37 | /// <summary>
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38 | /// A genetic algorithm.
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39 | /// </summary>
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40 | [Item("Genetic Algorithm", "A genetic algorithm.")]
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41 | [Creatable("Algorithms")]
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42 | [StorableClass]
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43 | public sealed class GeneticAlgorithm : HeuristicOptimizationEngineAlgorithm, IStorableContent {
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44 | public string Filename { get; set; }
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45 |
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46 | #region Problem Properties
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47 | public override Type ProblemType {
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48 | get { return typeof(ISingleObjectiveHeuristicOptimizationProblem); }
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49 | }
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50 | public new ISingleObjectiveHeuristicOptimizationProblem Problem {
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51 | get { return (ISingleObjectiveHeuristicOptimizationProblem)base.Problem; }
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52 | set { base.Problem = value; }
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53 | }
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54 | #endregion
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55 |
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56 | #region Parameter Properties
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57 | private ValueParameter<IntValue> SeedParameter {
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58 | get { return (ValueParameter<IntValue>)Parameters["Seed"]; }
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59 | }
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60 | private ValueParameter<BoolValue> SetSeedRandomlyParameter {
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61 | get { return (ValueParameter<BoolValue>)Parameters["SetSeedRandomly"]; }
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62 | }
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63 | private ValueParameter<IntValue> PopulationSizeParameter {
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64 | get { return (ValueParameter<IntValue>)Parameters["PopulationSize"]; }
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65 | }
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66 | public ConstrainedValueParameter<ISelector> SelectorParameter {
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67 | get { return (ConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
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68 | }
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69 | public ConstrainedValueParameter<ICrossover> CrossoverParameter {
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70 | get { return (ConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
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71 | }
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72 | private ValueParameter<PercentValue> MutationProbabilityParameter {
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73 | get { return (ValueParameter<PercentValue>)Parameters["MutationProbability"]; }
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74 | }
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75 | public OptionalConstrainedValueParameter<IManipulator> MutatorParameter {
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76 | get { return (OptionalConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
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77 | }
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78 | private ValueParameter<IntValue> ElitesParameter {
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79 | get { return (ValueParameter<IntValue>)Parameters["Elites"]; }
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80 | }
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81 | private ValueParameter<MultiAnalyzer> AnalyzerParameter {
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82 | get { return (ValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
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83 | }
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84 | private ValueParameter<IntValue> MaximumGenerationsParameter {
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85 | get { return (ValueParameter<IntValue>)Parameters["MaximumGenerations"]; }
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86 | }
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87 | #endregion
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88 |
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89 | #region Properties
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90 | public IntValue Seed {
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91 | get { return SeedParameter.Value; }
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92 | set { SeedParameter.Value = value; }
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93 | }
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94 | public BoolValue SetSeedRandomly {
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95 | get { return SetSeedRandomlyParameter.Value; }
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96 | set { SetSeedRandomlyParameter.Value = value; }
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97 | }
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98 | public IntValue PopulationSize {
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99 | get { return PopulationSizeParameter.Value; }
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100 | set { PopulationSizeParameter.Value = value; }
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101 | }
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102 | public ISelector Selector {
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103 | get { return SelectorParameter.Value; }
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104 | set { SelectorParameter.Value = value; }
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105 | }
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106 | public ICrossover Crossover {
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107 | get { return CrossoverParameter.Value; }
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108 | set { CrossoverParameter.Value = value; }
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109 | }
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110 | public PercentValue MutationProbability {
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111 | get { return MutationProbabilityParameter.Value; }
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112 | set { MutationProbabilityParameter.Value = value; }
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113 | }
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114 | public IManipulator Mutator {
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115 | get { return MutatorParameter.Value; }
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116 | set { MutatorParameter.Value = value; }
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117 | }
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118 | public IntValue Elites {
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119 | get { return ElitesParameter.Value; }
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120 | set { ElitesParameter.Value = value; }
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121 | }
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122 | public MultiAnalyzer Analyzer {
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123 | get { return AnalyzerParameter.Value; }
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124 | set { AnalyzerParameter.Value = value; }
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125 | }
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126 | public IntValue MaximumGenerations {
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127 | get { return MaximumGenerationsParameter.Value; }
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128 | set { MaximumGenerationsParameter.Value = value; }
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129 | }
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130 | private RandomCreator RandomCreator {
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131 | get { return (RandomCreator)OperatorGraph.InitialOperator; }
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132 | }
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133 | private SolutionsCreator SolutionsCreator {
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134 | get { return (SolutionsCreator)RandomCreator.Successor; }
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135 | }
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136 | private GeneticAlgorithmMainLoop GeneticAlgorithmMainLoop {
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137 | get { return FindMainLoop(SolutionsCreator.Successor); }
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138 | }
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139 | [Storable]
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140 | private BestAverageWorstQualityAnalyzer qualityAnalyzer;
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141 | #endregion
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142 |
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143 | public GeneticAlgorithm()
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144 | : base() {
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145 | Parameters.Add(new ValueParameter<IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
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146 | Parameters.Add(new ValueParameter<BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
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147 | Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "The size of the population of solutions.", new IntValue(100)));
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148 | Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
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149 | Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
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150 | Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
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151 | Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
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152 | Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
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153 | Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze each generation.", new MultiAnalyzer()));
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154 | Parameters.Add(new ValueParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed.", new IntValue(1000)));
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155 |
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156 | RandomCreator randomCreator = new RandomCreator();
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157 | SolutionsCreator solutionsCreator = new SolutionsCreator();
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158 | SubScopesCounter subScopesCounter = new SubScopesCounter();
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159 | ResultsCollector resultsCollector = new ResultsCollector();
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160 | GeneticAlgorithmMainLoop mainLoop = new GeneticAlgorithmMainLoop();
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161 | OperatorGraph.InitialOperator = randomCreator;
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162 |
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163 | randomCreator.RandomParameter.ActualName = "Random";
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164 | randomCreator.SeedParameter.ActualName = SeedParameter.Name;
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165 | randomCreator.SeedParameter.Value = null;
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166 | randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
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167 | randomCreator.SetSeedRandomlyParameter.Value = null;
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168 | randomCreator.Successor = solutionsCreator;
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169 |
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170 | solutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
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171 | solutionsCreator.Successor = subScopesCounter;
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172 |
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173 | subScopesCounter.Name = "Initialize EvaluatedSolutions";
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174 | subScopesCounter.ValueParameter.ActualName = "EvaluatedSolutions";
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175 | subScopesCounter.Successor = resultsCollector;
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176 |
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177 | resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
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178 | resultsCollector.ResultsParameter.ActualName = "Results";
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179 | resultsCollector.Successor = mainLoop;
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180 |
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181 | mainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
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182 | mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
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183 | mainLoop.ElitesParameter.ActualName = ElitesParameter.Name;
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184 | mainLoop.MaximumGenerationsParameter.ActualName = MaximumGenerationsParameter.Name;
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185 | mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
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186 | mainLoop.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
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187 | mainLoop.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
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188 | mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
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189 | mainLoop.EvaluatedSolutionsParameter.ActualName = "EvaluatedSolutions";
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190 | mainLoop.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
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191 | mainLoop.ResultsParameter.ActualName = "Results";
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192 |
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193 | foreach (ISelector selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(x => !(x is IMultiObjectiveSelector)).OrderBy(x => x.Name))
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194 | SelectorParameter.ValidValues.Add(selector);
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195 | ISelector proportionalSelector = SelectorParameter.ValidValues.FirstOrDefault(x => x.GetType().Name.Equals("ProportionalSelector"));
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196 | if (proportionalSelector != null) SelectorParameter.Value = proportionalSelector;
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197 | ParameterizeSelectors();
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198 |
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199 | qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
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200 | ParameterizeAnalyzers();
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201 | UpdateAnalyzers();
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202 |
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203 | Initialize();
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204 | }
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205 | [StorableConstructor]
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206 | private GeneticAlgorithm(bool deserializing) : base(deserializing) { }
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207 | [StorableHook(HookType.AfterDeserialization)]
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208 | private void AfterDeserialization() {
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209 | Initialize();
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210 | }
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211 |
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212 | private GeneticAlgorithm(GeneticAlgorithm original, Cloner cloner)
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213 | : base(original, cloner) {
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214 | qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
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215 | Initialize();
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216 | }
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217 | public override IDeepCloneable Clone(Cloner cloner) {
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218 | return new GeneticAlgorithm(this, cloner);
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219 | }
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220 |
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221 | public override void Prepare() {
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222 | if (Problem != null) base.Prepare();
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223 | }
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224 |
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225 | #region Events
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226 | protected override void OnProblemChanged() {
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227 | ParameterizeStochasticOperator(Problem.SolutionCreator);
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228 | ParameterizeStochasticOperator(Problem.Evaluator);
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229 | foreach (IOperator op in Problem.Operators.OfType<IOperator>()) ParameterizeStochasticOperator(op);
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230 | ParameterizeSolutionsCreator();
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231 | ParameterizeGeneticAlgorithmMainLoop();
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232 | ParameterizeSelectors();
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233 | ParameterizeAnalyzers();
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234 | ParameterizeIterationBasedOperators();
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235 | UpdateCrossovers();
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236 | UpdateMutators();
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237 | UpdateAnalyzers();
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238 | Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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239 | base.OnProblemChanged();
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240 | }
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241 |
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242 | protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
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243 | ParameterizeStochasticOperator(Problem.SolutionCreator);
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244 | ParameterizeSolutionsCreator();
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245 | base.Problem_SolutionCreatorChanged(sender, e);
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246 | }
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247 | protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
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248 | ParameterizeStochasticOperator(Problem.Evaluator);
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249 | ParameterizeSolutionsCreator();
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250 | ParameterizeGeneticAlgorithmMainLoop();
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251 | ParameterizeSelectors();
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252 | ParameterizeAnalyzers();
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253 | Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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254 | base.Problem_EvaluatorChanged(sender, e);
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255 | }
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256 | protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
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257 | foreach (IOperator op in Problem.Operators) ParameterizeStochasticOperator(op);
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258 | ParameterizeIterationBasedOperators();
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259 | UpdateCrossovers();
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260 | UpdateMutators();
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261 | UpdateAnalyzers();
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262 | base.Problem_OperatorsChanged(sender, e);
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263 | }
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264 | private void ElitesParameter_ValueChanged(object sender, EventArgs e) {
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265 | Elites.ValueChanged += new EventHandler(Elites_ValueChanged);
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266 | ParameterizeSelectors();
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267 | }
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268 | private void Elites_ValueChanged(object sender, EventArgs e) {
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269 | ParameterizeSelectors();
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270 | }
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271 |
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272 | private void PopulationSizeParameter_ValueChanged(object sender, EventArgs e) {
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273 | PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
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274 | ParameterizeSelectors();
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275 | }
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276 | private void PopulationSize_ValueChanged(object sender, EventArgs e) {
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277 | ParameterizeSelectors();
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278 | }
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279 | private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
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280 | ParameterizeGeneticAlgorithmMainLoop();
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281 | ParameterizeSelectors();
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282 | ParameterizeAnalyzers();
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283 | }
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284 | #endregion
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285 |
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286 | #region Helpers
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287 | private void Initialize() {
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288 | PopulationSizeParameter.ValueChanged += new EventHandler(PopulationSizeParameter_ValueChanged);
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289 | PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
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290 | ElitesParameter.ValueChanged += new EventHandler(ElitesParameter_ValueChanged);
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291 | Elites.ValueChanged += new EventHandler(Elites_ValueChanged);
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292 | if (Problem != null) {
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293 | Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
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294 | }
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295 | }
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296 |
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297 | private void ParameterizeSolutionsCreator() {
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298 | SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
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299 | SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
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300 | }
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301 | private void ParameterizeGeneticAlgorithmMainLoop() {
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302 | GeneticAlgorithmMainLoop.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
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303 | GeneticAlgorithmMainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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304 | GeneticAlgorithmMainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
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305 | }
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306 | private void ParameterizeStochasticOperator(IOperator op) {
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307 | IStochasticOperator stochasticOp = op as IStochasticOperator;
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308 | if (stochasticOp != null) {
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309 | stochasticOp.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
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310 | stochasticOp.RandomParameter.Hidden = true;
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311 | }
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312 | }
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313 | private void ParameterizeSelectors() {
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314 | foreach (ISelector selector in SelectorParameter.ValidValues) {
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315 | selector.CopySelected = new BoolValue(true);
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316 | selector.NumberOfSelectedSubScopesParameter.Value = new IntValue(2 * (PopulationSizeParameter.Value.Value - ElitesParameter.Value.Value));
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317 | selector.NumberOfSelectedSubScopesParameter.Hidden = true;
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318 | ParameterizeStochasticOperator(selector);
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319 | }
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320 | if (Problem != null) {
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321 | foreach (ISingleObjectiveSelector selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
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322 | selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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323 | selector.MaximizationParameter.Hidden = true;
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324 | selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
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325 | selector.QualityParameter.Hidden = true;
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326 | }
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327 | }
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328 | }
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329 | private void ParameterizeAnalyzers() {
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330 | qualityAnalyzer.ResultsParameter.ActualName = "Results";
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331 | qualityAnalyzer.ResultsParameter.Hidden = true;
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332 | if (Problem != null) {
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333 | qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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334 | qualityAnalyzer.MaximizationParameter.Hidden = true;
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335 | qualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
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336 | qualityAnalyzer.QualityParameter.Depth = 1;
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337 | qualityAnalyzer.QualityParameter.Hidden = true;
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338 | qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
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339 | qualityAnalyzer.BestKnownQualityParameter.Hidden = true;
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340 | }
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341 | }
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342 | private void ParameterizeIterationBasedOperators() {
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343 | if (Problem != null) {
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344 | foreach (IIterationBasedOperator op in Problem.Operators.OfType<IIterationBasedOperator>()) {
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345 | op.IterationsParameter.ActualName = "Generations";
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346 | op.IterationsParameter.Hidden = true;
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347 | op.MaximumIterationsParameter.ActualName = "MaximumGenerations";
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348 | op.MaximumIterationsParameter.Hidden = true;
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349 | }
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350 | }
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351 | }
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352 | private void UpdateCrossovers() {
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353 | ICrossover oldCrossover = CrossoverParameter.Value;
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354 | CrossoverParameter.ValidValues.Clear();
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355 | ICrossover defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
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356 |
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357 | foreach (ICrossover crossover in Problem.Operators.OfType<ICrossover>().OrderBy(x => x.Name))
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358 | CrossoverParameter.ValidValues.Add(crossover);
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359 |
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360 | if (oldCrossover != null) {
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361 | ICrossover crossover = CrossoverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldCrossover.GetType());
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362 | if (crossover != null) CrossoverParameter.Value = crossover;
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363 | else oldCrossover = null;
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364 | }
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365 | if (oldCrossover == null && defaultCrossover != null)
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366 | CrossoverParameter.Value = defaultCrossover;
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367 | }
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368 | private void UpdateMutators() {
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369 | IManipulator oldMutator = MutatorParameter.Value;
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370 | MutatorParameter.ValidValues.Clear();
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371 | foreach (IManipulator mutator in Problem.Operators.OfType<IManipulator>().OrderBy(x => x.Name))
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372 | MutatorParameter.ValidValues.Add(mutator);
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373 | if (oldMutator != null) {
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374 | IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
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375 | if (mutator != null) MutatorParameter.Value = mutator;
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376 | }
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377 | }
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378 | private void UpdateAnalyzers() {
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379 | Analyzer.Operators.Clear();
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380 | if (Problem != null) {
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381 | foreach (IAnalyzer analyzer in Problem.Operators.OfType<IAnalyzer>()) {
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382 | foreach (IScopeTreeLookupParameter param in analyzer.Parameters.OfType<IScopeTreeLookupParameter>())
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383 | param.Depth = 1;
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384 | Analyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
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385 | }
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386 | }
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387 | Analyzer.Operators.Add(qualityAnalyzer, qualityAnalyzer.EnabledByDefault);
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388 | }
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389 | private GeneticAlgorithmMainLoop FindMainLoop(IOperator start) {
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390 | IOperator mainLoop = start;
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391 | while (mainLoop != null && !(mainLoop is GeneticAlgorithmMainLoop))
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392 | mainLoop = ((SingleSuccessorOperator)mainLoop).Successor;
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393 | if (mainLoop == null) return null;
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394 | else return (GeneticAlgorithmMainLoop)mainLoop;
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395 | }
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396 | #endregion
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397 | }
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398 | }
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