[2830] | 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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[4722] | 22 | using HeuristicLab.Common;
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[2830] | 23 | using HeuristicLab.Core;
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| 24 | using HeuristicLab.Data;
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| 25 | using HeuristicLab.Operators;
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[3021] | 26 | using HeuristicLab.Optimization.Operators;
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[2830] | 27 | using HeuristicLab.Parameters;
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[3000] | 28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[2830] | 29 | using HeuristicLab.Selection;
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| 30 |
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[3196] | 31 | namespace HeuristicLab.Algorithms.GeneticAlgorithm {
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[2830] | 32 | /// <summary>
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[3198] | 33 | /// An operator which represents the main loop of a genetic algorithm.
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[2830] | 34 | /// </summary>
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[3198] | 35 | [Item("GeneticAlgorithmMainLoop", "An operator which represents the main loop of a genetic algorithm.")]
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[3017] | 36 | [StorableClass]
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[3198] | 37 | public sealed class GeneticAlgorithmMainLoop : AlgorithmOperator {
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[2830] | 38 | #region Parameter properties
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| 39 | public ValueLookupParameter<IRandom> RandomParameter {
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| 40 | get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
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| 41 | }
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[3048] | 42 | public ValueLookupParameter<BoolValue> MaximizationParameter {
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| 43 | get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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[2830] | 44 | }
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[3659] | 45 | public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
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| 46 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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[2830] | 47 | }
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[2882] | 48 | public ValueLookupParameter<IOperator> SelectorParameter {
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| 49 | get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
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[2830] | 50 | }
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[2882] | 51 | public ValueLookupParameter<IOperator> CrossoverParameter {
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| 52 | get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
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| 53 | }
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[3095] | 54 | public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
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| 55 | get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
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[2830] | 56 | }
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[2882] | 57 | public ValueLookupParameter<IOperator> MutatorParameter {
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| 58 | get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
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[2830] | 59 | }
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[2882] | 60 | public ValueLookupParameter<IOperator> EvaluatorParameter {
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| 61 | get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
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[2830] | 62 | }
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[3048] | 63 | public ValueLookupParameter<IntValue> ElitesParameter {
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| 64 | get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
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[2830] | 65 | }
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[3048] | 66 | public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
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| 67 | get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
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[2830] | 68 | }
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[2882] | 69 | public ValueLookupParameter<VariableCollection> ResultsParameter {
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| 70 | get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
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| 71 | }
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[3616] | 72 | public ValueLookupParameter<IOperator> AnalyzerParameter {
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| 73 | get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
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[3107] | 74 | }
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[5346] | 75 | public ValueLookupParameter<IntValue> EvaluatedSolutionsParameter {
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| 76 | get { return (ValueLookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
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| 77 | }
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| 78 | public ValueLookupParameter<IntValue> PopulationSizeParameter {
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| 79 | get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
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| 80 | }
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[2830] | 81 | private ScopeParameter CurrentScopeParameter {
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| 82 | get { return (ScopeParameter)Parameters["CurrentScope"]; }
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| 83 | }
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| 84 |
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| 85 | public IScope CurrentScope {
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| 86 | get { return CurrentScopeParameter.ActualValue; }
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| 87 | }
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| 88 | #endregion
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| 89 |
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[3080] | 90 | [StorableConstructor]
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[4722] | 91 | private GeneticAlgorithmMainLoop(bool deserializing) : base(deserializing) { }
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| 92 | private GeneticAlgorithmMainLoop(GeneticAlgorithmMainLoop original, Cloner cloner)
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| 93 | : base(original, cloner) {
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| 94 | }
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| 95 | public override IDeepCloneable Clone(Cloner cloner) {
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| 96 | return new GeneticAlgorithmMainLoop(this, cloner);
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| 97 | }
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[3198] | 98 | public GeneticAlgorithmMainLoop()
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[2830] | 99 | : base() {
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[3080] | 100 | Initialize();
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| 101 | }
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| 102 |
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| 103 | private void Initialize() {
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[2830] | 104 | #region Create parameters
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| 105 | Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
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[3048] | 106 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
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[3659] | 107 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
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[2882] | 108 | Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
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| 109 | Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
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[3095] | 110 | Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
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[2882] | 111 | Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
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[5208] | 112 | 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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[3048] | 113 | Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
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| 114 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
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[2882] | 115 | Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
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[3616] | 116 | Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
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[5346] | 117 | Parameters.Add(new ValueLookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
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| 118 | Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population."));
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[3198] | 119 | Parameters.Add(new ScopeParameter("CurrentScope", "The current scope which represents a population of solutions on which the genetic algorithm should be applied."));
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[2830] | 120 | #endregion
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| 121 |
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[3080] | 122 | #region Create operators
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[2908] | 123 | VariableCreator variableCreator = new VariableCreator();
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[3616] | 124 | ResultsCollector resultsCollector1 = new ResultsCollector();
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| 125 | Placeholder analyzer1 = new Placeholder();
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[2882] | 126 | Placeholder selector = new Placeholder();
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[3193] | 127 | SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
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[2830] | 128 | ChildrenCreator childrenCreator = new ChildrenCreator();
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[5208] | 129 | UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
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[2830] | 130 | Placeholder crossover = new Placeholder();
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| 131 | StochasticBranch stochasticBranch = new StochasticBranch();
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| 132 | Placeholder mutator = new Placeholder();
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[5208] | 133 | SubScopesRemover subScopesRemover = new SubScopesRemover();
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| 134 | UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
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[2830] | 135 | Placeholder evaluator = new Placeholder();
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[5352] | 136 | SubScopesCounter subScopesCounter = new SubScopesCounter();
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[3193] | 137 | SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
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[3096] | 138 | BestSelector bestSelector = new BestSelector();
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[2830] | 139 | RightReducer rightReducer = new RightReducer();
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| 140 | MergingReducer mergingReducer = new MergingReducer();
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[5352] | 141 | IntCounter intCounter = new IntCounter();
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[2830] | 142 | Comparator comparator = new Comparator();
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[3616] | 143 | ResultsCollector resultsCollector2 = new ResultsCollector();
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| 144 | Placeholder analyzer2 = new Placeholder();
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[2830] | 145 | ConditionalBranch conditionalBranch = new ConditionalBranch();
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| 146 |
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[3750] | 147 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class GeneticAlgorithm expects this to be called Generations
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[2908] | 148 |
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[3616] | 149 | resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
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[5346] | 150 | resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>(EvaluatedSolutionsParameter.Name));
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[3616] | 151 | resultsCollector1.ResultsParameter.ActualName = "Results";
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[3080] | 152 |
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[3616] | 153 | analyzer1.Name = "Analyzer";
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| 154 | analyzer1.OperatorParameter.ActualName = "Analyzer";
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[3095] | 155 |
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[2882] | 156 | selector.Name = "Selector";
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| 157 | selector.OperatorParameter.ActualName = "Selector";
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[2830] | 158 |
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[3048] | 159 | childrenCreator.ParentsPerChild = new IntValue(2);
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[2830] | 160 |
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[2882] | 161 | crossover.Name = "Crossover";
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| 162 | crossover.OperatorParameter.ActualName = "Crossover";
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[2830] | 163 |
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| 164 | stochasticBranch.ProbabilityParameter.ActualName = "MutationProbability";
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| 165 | stochasticBranch.RandomParameter.ActualName = "Random";
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| 166 |
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[2882] | 167 | mutator.Name = "Mutator";
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| 168 | mutator.OperatorParameter.ActualName = "Mutator";
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[2830] | 169 |
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[5208] | 170 | subScopesRemover.RemoveAllSubScopes = true;
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| 171 |
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| 172 | uniformSubScopesProcessor2.Parallel.Value = true;
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| 173 |
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[2882] | 174 | evaluator.Name = "Evaluator";
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| 175 | evaluator.OperatorParameter.ActualName = "Evaluator";
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[2830] | 176 |
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[5352] | 177 | subScopesCounter.Name = "Increment EvaluatedSolutions";
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| 178 | subScopesCounter.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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[5346] | 179 |
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[3096] | 180 | bestSelector.CopySelected = new BoolValue(false);
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| 181 | bestSelector.MaximizationParameter.ActualName = "Maximization";
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| 182 | bestSelector.NumberOfSelectedSubScopesParameter.ActualName = "Elites";
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| 183 | bestSelector.QualityParameter.ActualName = "Quality";
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[2830] | 184 |
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[5352] | 185 | intCounter.Increment = new IntValue(1);
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| 186 | intCounter.ValueParameter.ActualName = "Generations";
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[2830] | 187 |
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[3048] | 188 | comparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
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[2830] | 189 | comparator.LeftSideParameter.ActualName = "Generations";
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| 190 | comparator.ResultParameter.ActualName = "Terminate";
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| 191 | comparator.RightSideParameter.ActualName = "MaximumGenerations";
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| 192 |
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[3616] | 193 | resultsCollector2.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
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[5346] | 194 | resultsCollector2.CollectedValues.Add(new LookupParameter<IntValue>(EvaluatedSolutionsParameter.Name));
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[3616] | 195 | resultsCollector2.ResultsParameter.ActualName = "Results";
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[2891] | 196 |
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[3616] | 197 | analyzer2.Name = "Analyzer";
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| 198 | analyzer2.OperatorParameter.ActualName = "Analyzer";
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[3095] | 199 |
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[2830] | 200 | conditionalBranch.ConditionParameter.ActualName = "Terminate";
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[3080] | 201 | #endregion
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| 202 |
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| 203 | #region Create operator graph
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| 204 | OperatorGraph.InitialOperator = variableCreator;
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[3616] | 205 | variableCreator.Successor = resultsCollector1;
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| 206 | resultsCollector1.Successor = analyzer1;
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| 207 | analyzer1.Successor = selector;
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[3193] | 208 | selector.Successor = subScopesProcessor1;
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| 209 | subScopesProcessor1.Operators.Add(new EmptyOperator());
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| 210 | subScopesProcessor1.Operators.Add(childrenCreator);
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| 211 | subScopesProcessor1.Successor = subScopesProcessor2;
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[5208] | 212 | childrenCreator.Successor = uniformSubScopesProcessor1;
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| 213 | uniformSubScopesProcessor1.Operator = crossover;
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| 214 | uniformSubScopesProcessor1.Successor = uniformSubScopesProcessor2;
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[3080] | 215 | crossover.Successor = stochasticBranch;
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| 216 | stochasticBranch.FirstBranch = mutator;
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| 217 | stochasticBranch.SecondBranch = null;
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[5208] | 218 | stochasticBranch.Successor = subScopesRemover;
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[3080] | 219 | mutator.Successor = null;
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| 220 | subScopesRemover.Successor = null;
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[5208] | 221 | uniformSubScopesProcessor2.Operator = evaluator;
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[5352] | 222 | uniformSubScopesProcessor2.Successor = subScopesCounter;
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[5208] | 223 | evaluator.Successor = null;
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[5352] | 224 | subScopesCounter.Successor = null;
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[3193] | 225 | subScopesProcessor2.Operators.Add(bestSelector);
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| 226 | subScopesProcessor2.Operators.Add(new EmptyOperator());
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| 227 | subScopesProcessor2.Successor = mergingReducer;
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[3096] | 228 | bestSelector.Successor = rightReducer;
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[3080] | 229 | rightReducer.Successor = null;
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[5352] | 230 | mergingReducer.Successor = intCounter;
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| 231 | intCounter.Successor = comparator;
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[3616] | 232 | comparator.Successor = resultsCollector2;
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| 233 | resultsCollector2.Successor = analyzer2;
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| 234 | analyzer2.Successor = conditionalBranch;
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[3096] | 235 | conditionalBranch.FalseBranch = selector;
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[2830] | 236 | conditionalBranch.TrueBranch = null;
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| 237 | conditionalBranch.Successor = null;
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| 238 | #endregion
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| 239 | }
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[3715] | 240 |
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| 241 | public override IOperation Apply() {
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| 242 | if (CrossoverParameter.ActualValue == null)
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| 243 | return null;
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| 244 | return base.Apply();
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| 245 | }
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[2830] | 246 | }
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| 247 | }
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