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