| 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 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 | using HeuristicLab.Selection;
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| 30 |
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| 31 | namespace HeuristicLab.Algorithms.RAPGA {
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| 32 | /// <summary>
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| 33 | /// An operator which represents the main loop of a relevant alleles preserving genetic algorithm.
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| 34 | /// </summary>
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| 35 | [Item("RAPGAMainLoop", "An operator which represents the main loop of a relevant alleles preserving genetic algorithm.")]
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| 36 | [StorableClass]
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| 37 | public sealed class RAPGAMainLoop : AlgorithmOperator {
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| 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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| 42 | public ValueLookupParameter<BoolValue> MaximizationParameter {
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| 43 | get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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| 44 | }
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| 45 | public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
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| 46 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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| 47 | }
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| 48 | public ValueLookupParameter<IOperator> SelectorParameter {
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| 49 | get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
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| 50 | }
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| 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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| 54 | public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
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| 55 | get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
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| 56 | }
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| 57 | public ValueLookupParameter<IOperator> MutatorParameter {
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| 58 | get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
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| 59 | }
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| 60 | public ValueLookupParameter<IOperator> EvaluatorParameter {
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| 61 | get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
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| 62 | }
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| 63 | public ValueLookupParameter<IntValue> ElitesParameter {
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| 64 | get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
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| 65 | }
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| 66 | public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
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| 67 | get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
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| 68 | }
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| 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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| 72 | public ValueLookupParameter<IOperator> AnalyzerParameter {
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| 73 | get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
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| 74 | }
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| 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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| 81 | public IValueLookupParameter<IntValue> MinimumPopulationSizeParameter {
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| 82 | get { return (IValueLookupParameter<IntValue>)Parameters["MinimumPopulationSize"]; }
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| 83 | }
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| 84 | public IValueLookupParameter<IntValue> MaximumPopulationSizeParameter {
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| 85 | get { return (IValueLookupParameter<IntValue>)Parameters["MaximumPopulationSize"]; }
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| 86 | }
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| 87 | public IValueLookupParameter<DoubleValue> ComparisonFactorParameter {
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| 88 | get { return (IValueLookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
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| 89 | }
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| 90 | public IValueLookupParameter<IntValue> EffortParameter {
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| 91 | get { return (IValueLookupParameter<IntValue>)Parameters["Effort"]; }
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| 92 | }
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| 93 | private ScopeParameter CurrentScopeParameter {
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| 94 | get { return (ScopeParameter)Parameters["CurrentScope"]; }
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| 95 | }
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| 96 |
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| 97 | public IScope CurrentScope {
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| 98 | get { return CurrentScopeParameter.ActualValue; }
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| 99 | }
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| 100 | #endregion
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| 101 |
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| 102 | [StorableConstructor]
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| 103 | private RAPGAMainLoop(bool deserializing) : base(deserializing) { }
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| 104 | private RAPGAMainLoop(RAPGAMainLoop original, Cloner cloner) : base(original, cloner) { }
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| 105 | public RAPGAMainLoop()
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| 106 | : base() {
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| 107 | Initialize();
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| 108 | }
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| 109 | public override IDeepCloneable Clone(Cloner cloner) {
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| 110 | return new RAPGAMainLoop(this, cloner);
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| 111 | }
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| 112 |
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| 113 | private void Initialize() {
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| 114 | #region Create parameters
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| 115 | Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
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| 116 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
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| 117 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
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| 118 | Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
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| 119 | Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
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| 120 | Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
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| 121 | Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
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| 122 | 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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| 123 | Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
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| 124 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
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| 125 | Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
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| 126 | Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
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| 127 | Parameters.Add(new ValueLookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
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| 128 | Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population."));
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| 129 | Parameters.Add(new ValueLookupParameter<IntValue>("MinimumPopulationSize", "The minimum size of the population of solutions."));
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| 130 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumPopulationSize", "The maximum size of the population of solutions."));
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| 131 | Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactor", "The comparison factor."));
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| 132 | Parameters.Add(new ValueLookupParameter<IntValue>("Effort", "The maximum number of offspring created in each generation."));
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| 133 | 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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| 134 | #endregion
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| 135 |
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| 136 | #region Create operators
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| 137 | VariableCreator variableCreator = new VariableCreator();
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| 138 | Assigner assigner1 = new Assigner();
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| 139 | ResultsCollector resultsCollector1 = new ResultsCollector();
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| 140 | Placeholder analyzer1 = new Placeholder();
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| 141 | Placeholder selector = new Placeholder();
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| 142 | SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
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| 143 | ChildrenCreator childrenCreator = new ChildrenCreator();
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| 144 | UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
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| 145 | Placeholder crossover = new Placeholder();
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| 146 | StochasticBranch stochasticBranch = new StochasticBranch();
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| 147 | Placeholder mutator = new Placeholder();
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| 148 | UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
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| 149 | Placeholder evaluator = new Placeholder();
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| 150 | WeightedParentsQualityComparator comparator1 = new WeightedParentsQualityComparator();
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| 151 | ConditionalSelector conditionalSelector = new ConditionalSelector();
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| 152 | RightReducer rightReducer1 = new RightReducer();
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| 153 | SubScopesCounter subScopesCounter1 = new SubScopesCounter();
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| 154 | IntCounter intCounter1 = new IntCounter();
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| 155 | UniformSubScopesProcessor uniformSubScopesProcessor3 = new UniformSubScopesProcessor();
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| 156 | SubScopesRemover subScopesRemover = new SubScopesRemover();
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| 157 | Comparator comparator2 = new Comparator();
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| 158 | ConditionalBranch conditionalBranch1 = new ConditionalBranch();
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| 159 | BestSelector bestSelector1 = new BestSelector();
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| 160 | BestSelector bestSelector2 = new BestSelector();
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| 161 | RightReducer rightReducer2 = new RightReducer();
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| 162 | SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
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| 163 | BestSelector bestSelector3 = new BestSelector();
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| 164 | RightReducer rightReducer3 = new RightReducer();
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| 165 | MergingReducer mergingReducer = new MergingReducer();
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| 166 | IntCounter intCounter2 = new IntCounter();
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| 167 | Comparator comparator3 = new Comparator();
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| 168 | Placeholder analyzer2 = new Placeholder();
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| 169 | ConditionalBranch conditionalBranch2 = new ConditionalBranch();
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| 170 | Assigner assigner2 = new Assigner();
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| 171 | SubScopesCounter subScopesCounter2 = new SubScopesCounter();
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| 172 | ResultsCollector resultsCollector2 = new ResultsCollector();
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| 173 | Comparator comparator4 = new Comparator();
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| 174 | ConditionalBranch conditionalBranch3 = new ConditionalBranch();
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| 175 |
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| 176 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class GeneticAlgorithm expects this to be called Generations
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| 177 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("CurrentPopulationSize", new IntValue(0)));
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| 178 |
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| 179 | assigner1.Name = "Initialize CurrentPopulationSize";
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| 180 | assigner1.LeftSideParameter.ActualName = "CurrentPopulationSize";
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| 181 | assigner1.RightSideParameter.ActualName = EvaluatedSolutionsParameter.ActualName;
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| 182 |
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| 183 | resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
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| 184 | resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("CurrentPopulationSize"));
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| 185 | resultsCollector1.ResultsParameter.ActualName = "Results";
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| 186 |
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| 187 | analyzer1.Name = "Analyzer";
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| 188 | analyzer1.OperatorParameter.ActualName = "Analyzer";
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| 189 |
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| 190 | selector.Name = "Selector";
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| 191 | selector.OperatorParameter.ActualName = "Selector";
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| 192 |
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| 193 | childrenCreator.ParentsPerChild = new IntValue(2);
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| 194 |
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| 195 | crossover.Name = "Crossover";
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| 196 | crossover.OperatorParameter.ActualName = "Crossover";
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| 197 |
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| 198 | stochasticBranch.ProbabilityParameter.ActualName = "MutationProbability";
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| 199 | stochasticBranch.RandomParameter.ActualName = "Random";
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| 200 |
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| 201 | mutator.Name = "Mutator";
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| 202 | mutator.OperatorParameter.ActualName = "Mutator";
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| 203 |
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| 204 | uniformSubScopesProcessor2.Parallel.Value = true;
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| 205 |
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| 206 | evaluator.Name = "Evaluator";
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| 207 | evaluator.OperatorParameter.ActualName = "Evaluator";
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| 208 |
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| 209 | comparator1.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
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| 210 | comparator1.LeftSideParameter.ActualName = QualityParameter.Name;
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| 211 | comparator1.MaximizationParameter.ActualName = MaximizationParameter.Name;
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| 212 | comparator1.RightSideParameter.ActualName = QualityParameter.Name;
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| 213 | comparator1.ResultParameter.ActualName = "SuccessfulOffspring";
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| 214 |
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| 215 | conditionalSelector.ConditionParameter.ActualName = "SuccessfulOffspring";
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| 216 | conditionalSelector.ConditionParameter.Depth = 1;
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| 217 | conditionalSelector.CopySelected.Value = false;
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| 218 |
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| 219 | subScopesCounter1.Name = "Count Successful Offspring";
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| 220 | subScopesCounter1.ValueParameter.ActualName = "NumberOfSuccessfulOffspring";
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| 221 |
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| 222 | intCounter1.IncrementParameter.ActualName = "NumberOfSuccessfulOffspring";
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| 223 | intCounter1.IncrementParameter.Value = null;
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| 224 | intCounter1.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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| 225 |
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| 226 | uniformSubScopesProcessor3.Parallel.Value = true;
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| 227 |
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| 228 | subScopesRemover.RemoveAllSubScopes = true;
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| 229 |
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| 230 | comparator2.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
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| 231 | comparator2.LeftSideParameter.ActualName = "NumberOfSuccessfulOffspring";
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| 232 | comparator2.RightSideParameter.ActualName = MaximumPopulationSizeParameter.Name;
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| 233 | comparator2.ResultParameter.ActualName = "SelectMaximum";
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| 234 |
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| 235 | conditionalBranch1.ConditionParameter.ActualName = "SelectMaximum";
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| 236 |
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| 237 | bestSelector1.CopySelected = new BoolValue(true);
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| 238 | bestSelector1.MaximizationParameter.ActualName = MaximizationParameter.Name;
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| 239 | bestSelector1.NumberOfSelectedSubScopesParameter.ActualName = MaximumPopulationSizeParameter.Name;
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| 240 | bestSelector1.QualityParameter.ActualName = QualityParameter.Name;
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| 241 |
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| 242 | bestSelector2.CopySelected = new BoolValue(true);
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| 243 | bestSelector2.MaximizationParameter.ActualName = MaximizationParameter.Name;
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| 244 | bestSelector2.NumberOfSelectedSubScopesParameter.ActualName = "NumberOfSuccessfulOffspring";
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| 245 | bestSelector2.QualityParameter.ActualName = QualityParameter.Name;
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| 246 |
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| 247 | bestSelector3.CopySelected = new BoolValue(false);
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| 248 | bestSelector3.MaximizationParameter.ActualName = MaximizationParameter.Name;
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| 249 | bestSelector3.NumberOfSelectedSubScopesParameter.ActualName = "Elites";
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| 250 | bestSelector3.QualityParameter.ActualName = QualityParameter.Name;
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| 251 |
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| 252 | intCounter2.Increment = new IntValue(1);
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| 253 | intCounter2.ValueParameter.ActualName = "Generations";
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| 254 |
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| 255 | comparator3.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
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| 256 | comparator3.LeftSideParameter.ActualName = "Generations";
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| 257 | comparator3.ResultParameter.ActualName = "Terminate";
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| 258 | comparator3.RightSideParameter.ActualName = MaximumGenerationsParameter.Name;
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| 259 |
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| 260 | analyzer2.Name = "Analyzer";
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| 261 | analyzer2.OperatorParameter.ActualName = "Analyzer";
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| 262 |
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| 263 | conditionalBranch2.ConditionParameter.ActualName = "Terminate";
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| 264 |
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| 265 | assigner2.Name = "Reset CurrentPopulationSize";
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| 266 | assigner2.LeftSideParameter.ActualName = "CurrentPopulationSize";
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| 267 | assigner2.RightSideParameter.Value = new IntValue(0);
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| 268 |
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| 269 | subScopesCounter2.Name = "Increment EvaluatedSolutions";
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| 270 | subScopesCounter2.ValueParameter.ActualName = "CurrentPopulationSize";
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| 271 |
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| 272 | resultsCollector2.CollectedValues.Add(new LookupParameter<IntValue>("CurrentPopulationSize"));
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| 273 | resultsCollector2.ResultsParameter.ActualName = "Results";
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| 274 |
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| 275 | comparator4.Comparison = new Comparison(ComparisonType.Less);
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| 276 | comparator4.LeftSideParameter.ActualName = "CurrentPopulationSize";
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| 277 | comparator4.RightSideParameter.ActualName = MinimumPopulationSizeParameter.Name;
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| 278 | comparator4.ResultParameter.ActualName = "Terminate";
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| 279 |
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| 280 | conditionalBranch3.ConditionParameter.ActualName = "Terminate";
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| 281 | #endregion
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| 282 |
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| 283 | #region Create operator graph
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| 284 | OperatorGraph.InitialOperator = variableCreator;
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| 285 | variableCreator.Successor = assigner1;
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| 286 | assigner1.Successor = resultsCollector1;
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| 287 | resultsCollector1.Successor = analyzer1;
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| 288 | analyzer1.Successor = selector;
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| 289 | selector.Successor = subScopesProcessor1;
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| 290 | subScopesProcessor1.Operators.Add(new EmptyOperator());
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| 291 | subScopesProcessor1.Operators.Add(childrenCreator);
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| 292 | subScopesProcessor1.Successor = subScopesProcessor2;
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| 293 | childrenCreator.Successor = uniformSubScopesProcessor1;
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| 294 | uniformSubScopesProcessor1.Operator = crossover;
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| 295 | uniformSubScopesProcessor1.Successor = uniformSubScopesProcessor2;
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| 296 | crossover.Successor = stochasticBranch;
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| 297 | stochasticBranch.FirstBranch = mutator;
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| 298 | stochasticBranch.SecondBranch = null;
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| 299 | stochasticBranch.Successor = null;
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| 300 | mutator.Successor = null;
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| 301 | subScopesRemover.Successor = null;
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| 302 | uniformSubScopesProcessor2.Operator = evaluator;
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| 303 | uniformSubScopesProcessor2.Successor = conditionalSelector;
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| 304 | evaluator.Successor = comparator1;
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| 305 | conditionalSelector.Successor = rightReducer1;
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| 306 | rightReducer1.Successor = subScopesCounter1;
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| 307 | subScopesCounter1.Successor = intCounter1;
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| 308 | intCounter1.Successor = uniformSubScopesProcessor3;
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| 309 | uniformSubScopesProcessor3.Operator = subScopesRemover;
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| 310 | uniformSubScopesProcessor3.Successor = comparator2;
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| 311 | comparator2.Successor = conditionalBranch1;
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| 312 | conditionalBranch1.TrueBranch = bestSelector1;
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| 313 | conditionalBranch1.FalseBranch = bestSelector2;
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| 314 | bestSelector1.Successor = rightReducer2;
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| 315 | bestSelector2.Successor = rightReducer2;
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| 316 | subScopesProcessor2.Operators.Add(bestSelector3);
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| 317 | subScopesProcessor2.Operators.Add(new EmptyOperator());
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| 318 | subScopesProcessor2.Successor = mergingReducer;
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| 319 | bestSelector3.Successor = rightReducer3;
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| 320 | rightReducer3.Successor = null;
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| 321 | mergingReducer.Successor = intCounter2;
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| 322 | intCounter2.Successor = comparator3;
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| 323 | comparator3.Successor = analyzer2;
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| 324 | analyzer2.Successor = conditionalBranch2;
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| 325 | conditionalBranch2.FalseBranch = assigner2;
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| 326 | conditionalBranch2.TrueBranch = null;
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| 327 | conditionalBranch2.Successor = null;
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| 328 | assigner2.Successor = subScopesCounter2;
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| 329 | subScopesCounter2.Successor = resultsCollector2;
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| 330 | resultsCollector2.Successor = comparator4;
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| 331 | comparator4.Successor = conditionalBranch3;
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| 332 | conditionalBranch3.FalseBranch = selector;
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| 333 | conditionalBranch3.TrueBranch = null;
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| 334 | conditionalBranch3.Successor = null;
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| 335 | #endregion
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| 336 | }
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| 337 |
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| 338 | public override IOperation Apply() {
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| 339 | if (CrossoverParameter.ActualName == null)
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| 340 | return null;
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| 341 | return base.Apply();
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| 342 | }
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| 343 | }
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| 344 | }
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