| 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2013 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;
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| 27 | using HeuristicLab.Optimization.Operators;
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| 28 | using HeuristicLab.Parameters;
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| 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 30 | using HeuristicLab.Selection;
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| 31 |
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| 32 | namespace HeuristicLab.Algorithms.RAPGA {
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| 33 | /// <summary>
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| 34 | /// An operator which represents the main loop of a relevant alleles preserving genetic algorithm.
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| 35 | /// </summary>
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| 36 | [Item("RAPGAMainLoop", "An operator which represents the main loop of a relevant alleles preserving genetic algorithm.")]
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| 37 | [StorableClass]
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| 38 | public sealed class RAPGAMainLoop : AlgorithmOperator {
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| 39 | #region Parameter properties
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| 40 | public ValueLookupParameter<IRandom> RandomParameter {
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| 41 | get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
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| 42 | }
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| 43 | public ValueLookupParameter<BoolValue> MaximizationParameter {
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| 44 | get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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| 45 | }
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| 46 | public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
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| 47 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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| 48 | }
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| 49 | public ValueLookupParameter<IOperator> SelectorParameter {
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| 50 | get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
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| 51 | }
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| 52 | public ValueLookupParameter<IOperator> CrossoverParameter {
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| 53 | get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
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| 54 | }
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| 55 | public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
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| 56 | get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
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| 57 | }
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| 58 | public ValueLookupParameter<IOperator> MutatorParameter {
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| 59 | get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
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| 60 | }
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| 61 | public ValueLookupParameter<IOperator> EvaluatorParameter {
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| 62 | get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
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| 63 | }
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| 64 | public ValueLookupParameter<IntValue> ElitesParameter {
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| 65 | get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
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| 66 | }
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| 67 | public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
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| 68 | get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
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| 69 | }
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| 70 | public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
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| 71 | get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
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| 72 | }
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| 73 | public ValueLookupParameter<VariableCollection> ResultsParameter {
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| 74 | get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
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| 75 | }
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| 76 | public ValueLookupParameter<IOperator> AnalyzerParameter {
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| 77 | get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
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| 78 | }
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| 79 | public ValueLookupParameter<IntValue> EvaluatedSolutionsParameter {
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| 80 | get { return (ValueLookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
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| 81 | }
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| 82 | public ValueLookupParameter<IntValue> PopulationSizeParameter {
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| 83 | get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
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| 84 | }
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| 85 | public IValueLookupParameter<IntValue> MinimumPopulationSizeParameter {
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| 86 | get { return (IValueLookupParameter<IntValue>)Parameters["MinimumPopulationSize"]; }
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| 87 | }
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| 88 | public IValueLookupParameter<IntValue> MaximumPopulationSizeParameter {
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| 89 | get { return (IValueLookupParameter<IntValue>)Parameters["MaximumPopulationSize"]; }
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| 90 | }
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| 91 | public IValueLookupParameter<DoubleValue> ComparisonFactorParameter {
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| 92 | get { return (IValueLookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
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| 93 | }
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| 94 | public IValueLookupParameter<IntValue> EffortParameter {
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| 95 | get { return (IValueLookupParameter<IntValue>)Parameters["Effort"]; }
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| 96 | }
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| 97 | public IValueLookupParameter<IntValue> BatchSizeParameter {
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| 98 | get { return (IValueLookupParameter<IntValue>)Parameters["BatchSize"]; }
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| 99 | }
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| 100 | public IValueLookupParameter<ISolutionSimilarityCalculator> SimilarityCalculatorParameter {
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| 101 | get { return (IValueLookupParameter<ISolutionSimilarityCalculator>)Parameters["SimilarityCalculator"]; }
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| 102 | }
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| 103 | private ScopeParameter CurrentScopeParameter {
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| 104 | get { return (ScopeParameter)Parameters["CurrentScope"]; }
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| 105 | }
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| 106 |
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| 107 | public IScope CurrentScope {
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| 108 | get { return CurrentScopeParameter.ActualValue; }
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| 109 | }
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| 110 | #endregion
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| 111 |
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| 112 | [StorableConstructor]
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| 113 | private RAPGAMainLoop(bool deserializing) : base(deserializing) { }
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| 114 | private RAPGAMainLoop(RAPGAMainLoop original, Cloner cloner) : base(original, cloner) { }
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| 115 | public RAPGAMainLoop()
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| 116 | : base() {
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| 117 | Initialize();
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| 118 | }
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| 119 | public override IDeepCloneable Clone(Cloner cloner) {
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| 120 | return new RAPGAMainLoop(this, cloner);
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| 121 | }
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| 122 |
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| 123 | private void Initialize() {
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| 124 | #region Create parameters
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| 125 | Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
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| 126 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
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| 127 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
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| 128 | Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
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| 129 | Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
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| 130 | Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
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| 131 | Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
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| 132 | 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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| 133 | Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
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| 134 | Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
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| 135 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
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| 136 | Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
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| 137 | Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
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| 138 | Parameters.Add(new ValueLookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
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| 139 | Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population."));
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| 140 | Parameters.Add(new ValueLookupParameter<IntValue>("MinimumPopulationSize", "The minimum size of the population of solutions."));
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| 141 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumPopulationSize", "The maximum size of the population of solutions."));
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| 142 | Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactor", "The comparison factor."));
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| 143 | Parameters.Add(new ValueLookupParameter<IntValue>("Effort", "The maximum number of offspring created in each generation."));
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| 144 | Parameters.Add(new ValueLookupParameter<IntValue>("BatchSize", "The number of children that should be created during one iteration of the offspring creation process."));
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| 145 | Parameters.Add(new ValueLookupParameter<ISolutionSimilarityCalculator>("SimilarityCalculator", "The operator used to calculate the similarity between two solutions."));
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| 146 | 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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| 147 | #endregion
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| 148 |
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| 149 | #region Create operators
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| 150 | VariableCreator variableCreator = new VariableCreator();
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| 151 | Assigner assigner1 = new Assigner();
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| 152 | ResultsCollector resultsCollector = new ResultsCollector();
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| 153 | Placeholder analyzer1 = new Placeholder();
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| 154 | Placeholder selector = new Placeholder();
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| 155 | SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
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| 156 | ChildrenCreator childrenCreator = new ChildrenCreator();
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| 157 | UniformSubScopesProcessor uniformSubScopesProcessor = new UniformSubScopesProcessor();
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| 158 | Placeholder crossover = new Placeholder();
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| 159 | StochasticBranch stochasticBranch = new StochasticBranch();
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| 160 | Placeholder mutator = new Placeholder();
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| 161 | Placeholder evaluator = new Placeholder();
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| 162 | WeightedParentsQualityComparator weightedParentsQualityComparator = new WeightedParentsQualityComparator();
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| 163 | SubScopesRemover subScopesRemover = new SubScopesRemover();
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| 164 | IntCounter intCounter1 = new IntCounter();
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| 165 | IntCounter intCounter2 = new IntCounter();
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| 166 | ConditionalSelector conditionalSelector = new ConditionalSelector();
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| 167 | RightReducer rightReducer1 = new RightReducer();
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| 168 | DuplicatesSelector duplicateSelector = new DuplicatesSelector();
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| 169 | LeftReducer leftReducer1 = new LeftReducer();
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| 170 | ProgressiveOffspringPreserver progressiveOffspringSelector = new ProgressiveOffspringPreserver();
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| 171 | SubScopesCounter subScopesCounter2 = new SubScopesCounter();
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| 172 | ExpressionCalculator calculator1 = new ExpressionCalculator();
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| 173 | ConditionalBranch conditionalBranch1 = new ConditionalBranch();
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| 174 | Comparator comparator1 = new Comparator();
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| 175 | ConditionalBranch conditionalBranch2 = new ConditionalBranch();
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| 176 | LeftReducer leftReducer2 = new LeftReducer();
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| 177 | SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
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| 178 | BestSelector bestSelector = new BestSelector();
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| 179 | RightReducer rightReducer2 = new RightReducer();
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| 180 | ScopeCleaner scopeCleaner = new ScopeCleaner();
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| 181 | ScopeRestorer scopeRestorer = new ScopeRestorer();
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| 182 | MergingReducer mergingReducer = new MergingReducer();
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| 183 | IntCounter intCounter3 = new IntCounter();
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| 184 | SubScopesCounter subScopesCounter3 = new SubScopesCounter();
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| 185 | ExpressionCalculator calculator2 = new ExpressionCalculator();
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| 186 | Comparator comparator2 = new Comparator();
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| 187 | ConditionalBranch conditionalBranch3 = new ConditionalBranch();
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| 188 | Placeholder analyzer2 = new Placeholder();
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| 189 | Comparator comparator3 = new Comparator();
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| 190 | ConditionalBranch conditionalBranch4 = new ConditionalBranch();
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| 191 | Comparator comparator4 = new Comparator();
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| 192 | ConditionalBranch conditionalBranch5 = new ConditionalBranch();
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| 193 | Assigner assigner3 = new Assigner();
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| 194 | Assigner assigner4 = new Assigner();
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| 195 | Assigner assigner5 = new Assigner();
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| 196 | ConditionalBranch reevaluateElitesBranch = new ConditionalBranch();
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| 197 | UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
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| 198 | Placeholder evaluator2 = new Placeholder();
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| 199 | SubScopesCounter subScopesCounter4 = new SubScopesCounter();
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| 200 |
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| 201 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class RAPGA expects this to be called Generations
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| 202 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("CurrentPopulationSize", new IntValue(0)));
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| 203 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("NumberOfCreatedOffspring", new IntValue(0)));
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| 204 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("NumberOfSuccessfulOffspring", new IntValue(0)));
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| 205 | variableCreator.CollectedValues.Add(new ValueParameter<ScopeList>("OffspringList", new ScopeList()));
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| 206 |
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| 207 | assigner1.Name = "Initialize CurrentPopulationSize";
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| 208 | assigner1.LeftSideParameter.ActualName = "CurrentPopulationSize";
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| 209 | assigner1.RightSideParameter.ActualName = PopulationSizeParameter.Name;
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| 210 |
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| 211 | resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
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| 212 | resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("CurrentPopulationSize"));
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| 213 | resultsCollector.ResultsParameter.ActualName = "Results";
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| 214 |
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| 215 | analyzer1.Name = "Analyzer";
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| 216 | analyzer1.OperatorParameter.ActualName = "Analyzer";
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| 217 |
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| 218 | selector.Name = "Selector";
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| 219 | selector.OperatorParameter.ActualName = "Selector";
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| 220 |
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| 221 | childrenCreator.ParentsPerChild = new IntValue(2);
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| 222 |
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| 223 | uniformSubScopesProcessor.Parallel.Value = true;
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| 224 |
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| 225 | crossover.Name = "Crossover";
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| 226 | crossover.OperatorParameter.ActualName = "Crossover";
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| 227 |
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| 228 | stochasticBranch.ProbabilityParameter.ActualName = "MutationProbability";
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| 229 | stochasticBranch.RandomParameter.ActualName = "Random";
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| 230 |
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| 231 | mutator.Name = "Mutator";
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| 232 | mutator.OperatorParameter.ActualName = "Mutator";
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| 233 |
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| 234 | evaluator.Name = "Evaluator";
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| 235 | evaluator.OperatorParameter.ActualName = "Evaluator";
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| 236 |
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| 237 | weightedParentsQualityComparator.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
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| 238 | weightedParentsQualityComparator.LeftSideParameter.ActualName = QualityParameter.Name;
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| 239 | weightedParentsQualityComparator.MaximizationParameter.ActualName = MaximizationParameter.Name;
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| 240 | weightedParentsQualityComparator.RightSideParameter.ActualName = QualityParameter.Name;
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| 241 | weightedParentsQualityComparator.ResultParameter.ActualName = "SuccessfulOffspring";
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| 242 |
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| 243 | subScopesRemover.RemoveAllSubScopes = true;
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| 244 |
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| 245 | intCounter1.Name = "Increment NumberOfCreatedOffspring";
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| 246 | intCounter1.ValueParameter.ActualName = "NumberOfCreatedOffspring";
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| 247 | intCounter1.Increment = null;
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| 248 | intCounter1.IncrementParameter.ActualName = BatchSizeParameter.Name;
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| 249 |
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| 250 | intCounter2.Name = "Increment EvaluatedSolutions";
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| 251 | intCounter2.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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| 252 | intCounter2.Increment = null;
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| 253 | intCounter2.IncrementParameter.ActualName = BatchSizeParameter.Name;
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| 254 |
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| 255 | conditionalSelector.ConditionParameter.ActualName = "SuccessfulOffspring";
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| 256 | conditionalSelector.ConditionParameter.Depth = 1;
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| 257 | conditionalSelector.CopySelected.Value = false;
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| 258 |
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| 259 | duplicateSelector.CopySelected.Value = false;
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| 260 |
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| 261 | progressiveOffspringSelector.OffspringListParameter.ActualName = "OffspringList";
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| 262 | progressiveOffspringSelector.ElitesParameter.ActualName = ElitesParameter.Name;
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| 263 | progressiveOffspringSelector.MaximumPopulationSizeParameter.ActualName = MaximumPopulationSizeParameter.Name;
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| 264 |
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| 265 | subScopesCounter2.Name = "Count Successful Offspring";
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| 266 | subScopesCounter2.ValueParameter.ActualName = "NumberOfSuccessfulOffspring";
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| 267 |
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| 268 | calculator1.Name = "NumberOfSuccessfulOffspring == MaximumPopulationSize - Elites";
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| 269 | calculator1.CollectedValues.Add(new ValueLookupParameter<IntValue>("NumberOfSuccessfulOffspring"));
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| 270 | calculator1.CollectedValues.Add(new ValueLookupParameter<IntValue>("MaximumPopulationSize"));
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| 271 | calculator1.CollectedValues.Add(new ValueLookupParameter<IntValue>("Elites"));
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| 272 | calculator1.ExpressionParameter.Value = new StringValue("NumberOfSuccessfulOffspring MaximumPopulationSize Elites - ==");
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| 273 | calculator1.ExpressionResultParameter.ActualName = "Break";
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| 274 |
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| 275 | conditionalBranch1.Name = "Break?";
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| 276 | conditionalBranch1.ConditionParameter.ActualName = "Break";
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| 277 |
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| 278 | comparator1.Name = "NumberOfCreatedOffspring >= Effort";
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| 279 | comparator1.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
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| 280 | comparator1.LeftSideParameter.ActualName = "NumberOfCreatedOffspring";
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| 281 | comparator1.RightSideParameter.ActualName = EffortParameter.Name;
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| 282 | comparator1.ResultParameter.ActualName = "Break";
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| 283 |
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| 284 | conditionalBranch2.Name = "Break?";
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| 285 | conditionalBranch2.ConditionParameter.ActualName = "Break";
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| 286 |
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| 287 | bestSelector.CopySelected = new BoolValue(false);
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| 288 | bestSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
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| 289 | bestSelector.NumberOfSelectedSubScopesParameter.ActualName = "Elites";
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| 290 | bestSelector.QualityParameter.ActualName = QualityParameter.Name;
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| 291 |
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| 292 | intCounter3.Name = "Increment Generations";
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| 293 | intCounter3.Increment = new IntValue(1);
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| 294 | intCounter3.ValueParameter.ActualName = "Generations";
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| 295 |
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| 296 | subScopesCounter3.Name = "Update CurrentPopulationSize";
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| 297 | subScopesCounter3.ValueParameter.ActualName = "CurrentPopulationSize";
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| 298 | subScopesCounter3.AccumulateParameter.Value = new BoolValue(false);
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| 299 |
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| 300 | calculator2.Name = "Evaluate ActualSelectionPressure";
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| 301 | calculator2.CollectedValues.Add(new ValueLookupParameter<IntValue>("NumberOfCreatedOffspring"));
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| 302 | calculator2.CollectedValues.Add(new ValueLookupParameter<IntValue>("Elites"));
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| 303 | calculator2.CollectedValues.Add(new ValueLookupParameter<IntValue>("CurrentPopulationSize"));
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| 304 | calculator2.ExpressionParameter.Value = new StringValue("NumberOfCreatedOffspring Elites + CurrentPopulationSize /");
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| 305 | calculator2.ExpressionResultParameter.ActualName = "ActualSelectionPressure";
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| 306 |
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| 307 | comparator2.Name = "CurrentPopulationSize < 1";
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| 308 | comparator2.Comparison = new Comparison(ComparisonType.Less);
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| 309 | comparator2.LeftSideParameter.ActualName = "CurrentPopulationSize";
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| 310 | comparator2.RightSideParameter.Value = new IntValue(1);
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| 311 | comparator2.ResultParameter.ActualName = "Terminate";
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| 312 |
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| 313 | conditionalBranch3.Name = "Terminate?";
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| 314 | conditionalBranch3.ConditionParameter.ActualName = "Terminate";
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| 315 |
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| 316 | analyzer2.Name = "Analyzer";
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| 317 | analyzer2.OperatorParameter.ActualName = "Analyzer";
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| 318 |
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| 319 | comparator3.Name = "Generations >= MaximumGenerations";
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| 320 | comparator3.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
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| 321 | comparator3.LeftSideParameter.ActualName = "Generations";
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| 322 | comparator3.ResultParameter.ActualName = "Terminate";
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| 323 | comparator3.RightSideParameter.ActualName = MaximumGenerationsParameter.Name;
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| 324 |
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| 325 | conditionalBranch4.Name = "Terminate?";
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| 326 | conditionalBranch4.ConditionParameter.ActualName = "Terminate";
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| 327 |
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| 328 | comparator4.Name = "CurrentPopulationSize < MinimumPopulationSize";
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| 329 | comparator4.Comparison = new Comparison(ComparisonType.Less);
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| 330 | comparator4.LeftSideParameter.ActualName = "CurrentPopulationSize";
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| 331 | comparator4.RightSideParameter.ActualName = MinimumPopulationSizeParameter.Name;
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| 332 | comparator4.ResultParameter.ActualName = "Terminate";
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| 333 |
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| 334 | conditionalBranch5.Name = "Terminate?";
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| 335 | conditionalBranch5.ConditionParameter.ActualName = "Terminate";
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| 336 |
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| 337 | assigner3.Name = "Reset NumberOfCreatedOffspring";
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| 338 | assigner3.LeftSideParameter.ActualName = "NumberOfCreatedOffspring";
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| 339 | assigner3.RightSideParameter.Value = new IntValue(0);
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| 340 |
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| 341 | assigner4.Name = "Reset NumberOfSuccessfulOffspring";
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| 342 | assigner4.LeftSideParameter.ActualName = "NumberOfSuccessfulOffspring";
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| 343 | assigner4.RightSideParameter.Value = new IntValue(0);
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| 344 |
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| 345 | assigner5.Name = "Reset OffspringList";
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| 346 | assigner5.LeftSideParameter.ActualName = "OffspringList";
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| 347 | assigner5.RightSideParameter.Value = new ScopeList();
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| 348 |
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| 349 | reevaluateElitesBranch.ConditionParameter.ActualName = "ReevaluateElites";
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| 350 | reevaluateElitesBranch.Name = "Reevaluate elites ?";
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| 351 |
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| 352 | uniformSubScopesProcessor2.Parallel.Value = true;
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| 353 |
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| 354 | evaluator2.Name = "Evaluator (placeholder)";
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| 355 | evaluator2.OperatorParameter.ActualName = EvaluatorParameter.Name;
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| 356 |
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| 357 | subScopesCounter4.Name = "Increment EvaluatedSolutions";
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| 358 | subScopesCounter4.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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| 359 | #endregion
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| 360 |
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| 361 | #region Create operator graph
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| 362 | OperatorGraph.InitialOperator = variableCreator;
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| 363 | variableCreator.Successor = assigner1;
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| 364 | assigner1.Successor = resultsCollector;
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| 365 | resultsCollector.Successor = analyzer1;
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| 366 | analyzer1.Successor = selector;
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| 367 | selector.Successor = subScopesProcessor1;
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| 368 | subScopesProcessor1.Operators.Add(new EmptyOperator());
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| 369 | subScopesProcessor1.Operators.Add(childrenCreator);
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| 370 | subScopesProcessor1.Successor = calculator1;
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| 371 | childrenCreator.Successor = uniformSubScopesProcessor;
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| 372 | uniformSubScopesProcessor.Operator = crossover;
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| 373 | uniformSubScopesProcessor.Successor = intCounter1;
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| 374 | crossover.Successor = stochasticBranch;
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| 375 | stochasticBranch.FirstBranch = mutator;
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| 376 | stochasticBranch.SecondBranch = null;
|
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| 377 | mutator.Successor = null;
|
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| 378 | stochasticBranch.Successor = evaluator;
|
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| 379 | evaluator.Successor = weightedParentsQualityComparator;
|
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| 380 | weightedParentsQualityComparator.Successor = subScopesRemover;
|
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| 381 | intCounter1.Successor = intCounter2;
|
|---|
| 382 | intCounter2.Successor = conditionalSelector;
|
|---|
| 383 | conditionalSelector.Successor = rightReducer1;
|
|---|
| 384 | rightReducer1.Successor = duplicateSelector;
|
|---|
| 385 | duplicateSelector.Successor = leftReducer1;
|
|---|
| 386 | leftReducer1.Successor = progressiveOffspringSelector;
|
|---|
| 387 | progressiveOffspringSelector.Successor = subScopesCounter2;
|
|---|
| 388 | calculator1.Successor = conditionalBranch1;
|
|---|
| 389 | conditionalBranch1.FalseBranch = comparator1;
|
|---|
| 390 | conditionalBranch1.TrueBranch = subScopesProcessor2;
|
|---|
| 391 | comparator1.Successor = conditionalBranch2;
|
|---|
| 392 | conditionalBranch2.FalseBranch = leftReducer2;
|
|---|
| 393 | conditionalBranch2.TrueBranch = subScopesProcessor2;
|
|---|
| 394 | leftReducer2.Successor = selector;
|
|---|
| 395 | subScopesProcessor2.Operators.Add(bestSelector);
|
|---|
| 396 | subScopesProcessor2.Operators.Add(scopeCleaner);
|
|---|
| 397 | subScopesProcessor2.Successor = mergingReducer;
|
|---|
| 398 | bestSelector.Successor = rightReducer2;
|
|---|
| 399 | rightReducer2.Successor = reevaluateElitesBranch;
|
|---|
| 400 | reevaluateElitesBranch.TrueBranch = uniformSubScopesProcessor2;
|
|---|
| 401 | uniformSubScopesProcessor2.Operator = evaluator2;
|
|---|
| 402 | uniformSubScopesProcessor2.Successor = subScopesCounter4;
|
|---|
| 403 | evaluator2.Successor = null;
|
|---|
| 404 | subScopesCounter4.Successor = null;
|
|---|
| 405 | reevaluateElitesBranch.FalseBranch = null;
|
|---|
| 406 | reevaluateElitesBranch.Successor = null;
|
|---|
| 407 | scopeCleaner.Successor = scopeRestorer;
|
|---|
| 408 | mergingReducer.Successor = intCounter3;
|
|---|
| 409 | intCounter3.Successor = subScopesCounter3;
|
|---|
| 410 | subScopesCounter3.Successor = calculator2;
|
|---|
| 411 | calculator2.Successor = comparator2;
|
|---|
| 412 | comparator2.Successor = conditionalBranch3;
|
|---|
| 413 | conditionalBranch3.FalseBranch = analyzer2;
|
|---|
| 414 | conditionalBranch3.TrueBranch = null;
|
|---|
| 415 | analyzer2.Successor = comparator3;
|
|---|
| 416 | comparator3.Successor = conditionalBranch4;
|
|---|
| 417 | conditionalBranch4.FalseBranch = comparator4;
|
|---|
| 418 | conditionalBranch4.TrueBranch = null;
|
|---|
| 419 | conditionalBranch4.Successor = null;
|
|---|
| 420 | comparator4.Successor = conditionalBranch5;
|
|---|
| 421 | conditionalBranch5.FalseBranch = assigner3;
|
|---|
| 422 | conditionalBranch5.TrueBranch = null;
|
|---|
| 423 | conditionalBranch5.Successor = null;
|
|---|
| 424 | assigner3.Successor = assigner4;
|
|---|
| 425 | assigner4.Successor = assigner5;
|
|---|
| 426 | assigner5.Successor = selector;
|
|---|
| 427 |
|
|---|
| 428 | #endregion
|
|---|
| 429 | }
|
|---|
| 430 |
|
|---|
| 431 | public override IOperation Apply() {
|
|---|
| 432 | if (CrossoverParameter.ActualName == null)
|
|---|
| 433 | return null;
|
|---|
| 434 | return base.Apply();
|
|---|
| 435 | }
|
|---|
| 436 | }
|
|---|
| 437 | }
|
|---|
