| 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2016 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.ALPS {
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| 32 | [Item("AlpsGeneticAlgorithmMainOperator", "An operator that represents the core of an ALPS genetic algorithm.")]
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| 33 | [StorableClass]
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| 34 | public sealed class AlpsGeneticAlgorithmMainOperator : AlgorithmOperator {
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| 35 | #region Parameter properties
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| 36 | public IValueLookupParameter<IRandom> RandomParameter {
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| 37 | get { return (IValueLookupParameter<IRandom>)Parameters["Random"]; }
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| 38 | }
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| 39 |
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| 40 | public IValueLookupParameter<IOperator> EvaluatorParameter {
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| 41 | get { return (IValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
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| 42 | }
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| 43 | public IValueLookupParameter<IntValue> EvaluatedSolutionsParameter {
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| 44 | get { return (IValueLookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
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| 45 | }
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| 46 | public IScopeTreeLookupParameter<DoubleValue> QualityParameter {
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| 47 | get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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| 48 | }
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| 49 | public IValueLookupParameter<BoolValue> MaximizationParameter {
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| 50 | get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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| 51 | }
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| 52 |
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| 53 | public IValueLookupParameter<IntValue> PopulationSizeParameter {
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| 54 | get { return (IValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
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| 55 | }
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| 56 | public IValueLookupParameter<IOperator> SelectorParameter {
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| 57 | get { return (IValueLookupParameter<IOperator>)Parameters["Selector"]; }
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| 58 | }
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| 59 | public IValueLookupParameter<IOperator> CrossoverParameter {
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| 60 | get { return (IValueLookupParameter<IOperator>)Parameters["Crossover"]; }
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| 61 | }
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| 62 | public IValueLookupParameter<IOperator> MutatorParameter {
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| 63 | get { return (IValueLookupParameter<IOperator>)Parameters["Mutator"]; }
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| 64 | }
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| 65 | public IValueLookupParameter<PercentValue> MutationProbabilityParameter {
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| 66 | get { return (IValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
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| 67 | }
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| 68 | public IValueLookupParameter<IntValue> ElitesParameter {
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| 69 | get { return (IValueLookupParameter<IntValue>)Parameters["Elites"]; }
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| 70 | }
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| 71 | public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
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| 72 | get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
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| 73 | }
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| 74 | public IValueLookupParameter<BoolValue> PlusSelectionParameter {
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| 75 | get { return (IValueLookupParameter<BoolValue>)Parameters["PlusSelection"]; }
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| 76 | }
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| 77 |
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| 78 | public IScopeTreeLookupParameter<DoubleValue> AgeParameter {
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| 79 | get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters["Age"]; }
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| 80 | }
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| 81 | public IValueLookupParameter<DoubleValue> AgeInheritanceParameter {
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| 82 | get { return (IValueLookupParameter<DoubleValue>)Parameters["AgeInheritance"]; }
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| 83 | }
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| 84 | public IValueLookupParameter<DoubleValue> AgeIncrementParameter {
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| 85 | get { return (IValueLookupParameter<DoubleValue>)Parameters["AgeIncrement"]; }
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| 86 | }
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| 87 | #endregion
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| 88 |
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| 89 | [StorableConstructor]
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| 90 | private AlpsGeneticAlgorithmMainOperator(bool deserializing) : base(deserializing) { }
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| 91 | private AlpsGeneticAlgorithmMainOperator(AlpsGeneticAlgorithmMainOperator original, Cloner cloner)
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| 92 | : base(original, cloner) {
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| 93 | }
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| 94 | public override IDeepCloneable Clone(Cloner cloner) {
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| 95 | return new AlpsGeneticAlgorithmMainOperator(this, cloner);
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| 96 | }
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| 97 | public AlpsGeneticAlgorithmMainOperator()
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| 98 | : base() {
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| 99 | Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
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| 100 |
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| 101 | 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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| 102 | Parameters.Add(new ValueLookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
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| 103 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
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| 104 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
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| 105 |
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| 106 | Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population of solutions in each layer."));
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| 107 | Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
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| 108 | Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
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| 109 | Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
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| 110 | Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
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| 111 | Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
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| 112 | 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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| 113 | Parameters.Add(new ValueLookupParameter<BoolValue>("PlusSelection", "Include the parents in the selection of the invividuals for the next generation."));
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| 114 |
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| 115 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Age", "The age of individuals."));
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| 116 | Parameters.Add(new ValueLookupParameter<DoubleValue>("AgeInheritance", "A weight that determines the age of a child after crossover based on the older (1.0) and younger (0.0) parent."));
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| 117 | Parameters.Add(new ValueLookupParameter<DoubleValue>("AgeIncrement", "The value the age the individuals is incremented if they survives a generation."));
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| 118 |
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| 119 |
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| 120 | var numberOfSelectedParentsCalculator = new ExpressionCalculator() { Name = "NumberOfSelectedParents = 2 * (PopulationSize - (PlusSelection ? 0 : Elites))" };
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| 121 | var selector = new Placeholder() { Name = "Selector (Placeholder)" };
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| 122 | var subScopesProcessor1 = new SubScopesProcessor();
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| 123 | var childrenCreator = new ChildrenCreator();
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| 124 | var uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
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| 125 | var crossover = new Placeholder() { Name = "Crossover (Placeholder)" };
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| 126 | var stochasticBranch = new StochasticBranch() { Name = "MutationProbability" };
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| 127 | var mutator = new Placeholder() { Name = "Mutator (Placeholder)" };
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| 128 | var ageCalculator = new WeightingReducer() { Name = "Calculate Age" };
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| 129 | var subScopesRemover = new SubScopesRemover();
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| 130 | var uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
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| 131 | var evaluator = new Placeholder() { Name = "Evaluator (Placeholder)" };
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| 132 | var subScopesCounter = new SubScopesCounter() { Name = "Increment EvaluatedSolutions" };
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| 133 | var replacementBranch = new ConditionalBranch() { Name = "PlusSelection?" };
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| 134 | var replacementMergingReducer = new MergingReducer();
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| 135 | var replacementBestSelector = new BestSelector();
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| 136 | var replacementRightReducer = new RightReducer();
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| 137 | var subScopesProcessor2 = new SubScopesProcessor();
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| 138 | var bestSelector = new BestSelector();
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| 139 | var rightReducer = new RightReducer();
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| 140 | var mergingReducer = new MergingReducer();
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| 141 | var reevaluateElitesBranch = new ConditionalBranch() { Name = "Reevaluate elites ?" };
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| 142 | var incrementAgeProcessor = new UniformSubScopesProcessor();
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| 143 | var ageIncrementor = new DoubleCounter() { Name = "Increment Age" };
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| 144 |
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| 145 | OperatorGraph.InitialOperator = numberOfSelectedParentsCalculator;
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| 146 |
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| 147 | numberOfSelectedParentsCalculator.CollectedValues.Add(new LookupParameter<IntValue>(PopulationSizeParameter.Name));
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| 148 | numberOfSelectedParentsCalculator.CollectedValues.Add(new LookupParameter<IntValue>(ElitesParameter.Name));
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| 149 | numberOfSelectedParentsCalculator.CollectedValues.Add(new LookupParameter<BoolValue>(PlusSelectionParameter.Name));
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| 150 | numberOfSelectedParentsCalculator.ExpressionResultParameter.ActualName = "NumberOfSelectedSubScopes";
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| 151 | numberOfSelectedParentsCalculator.ExpressionParameter.Value = new StringValue("PopulationSize 0 Elites PlusSelection if - 2 * toint");
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| 152 | numberOfSelectedParentsCalculator.Successor = selector;
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| 153 |
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| 154 | selector.OperatorParameter.ActualName = SelectorParameter.Name;
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| 155 | selector.Successor = subScopesProcessor1;
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| 156 |
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| 157 | subScopesProcessor1.Operators.Add(new EmptyOperator());
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| 158 | subScopesProcessor1.Operators.Add(childrenCreator);
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| 159 | subScopesProcessor1.Successor = replacementBranch;
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| 160 |
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| 161 | childrenCreator.ParentsPerChild = new IntValue(2);
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| 162 | childrenCreator.Successor = uniformSubScopesProcessor1;
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| 163 |
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| 164 | uniformSubScopesProcessor1.Operator = crossover;
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| 165 | uniformSubScopesProcessor1.Successor = uniformSubScopesProcessor2;
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| 166 |
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| 167 | crossover.OperatorParameter.ActualName = CrossoverParameter.Name;
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| 168 | crossover.Successor = stochasticBranch;
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| 169 |
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| 170 | stochasticBranch.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
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| 171 | stochasticBranch.RandomParameter.ActualName = RandomParameter.Name;
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| 172 | stochasticBranch.FirstBranch = mutator;
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| 173 | stochasticBranch.SecondBranch = null;
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| 174 | stochasticBranch.Successor = ageCalculator;
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| 175 |
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| 176 | mutator.OperatorParameter.ActualName = MutatorParameter.Name;
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| 177 | mutator.Successor = null;
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| 178 |
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| 179 | ageCalculator.ParameterToReduce.ActualName = AgeParameter.Name;
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| 180 | ageCalculator.TargetParameter.ActualName = AgeParameter.Name;
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| 181 | ageCalculator.WeightParameter.ActualName = AgeInheritanceParameter.Name;
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| 182 | ageCalculator.Successor = subScopesRemover;
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| 183 |
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| 184 | subScopesRemover.RemoveAllSubScopes = true;
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| 185 | subScopesRemover.Successor = null;
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| 186 |
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| 187 | uniformSubScopesProcessor2.Parallel.Value = true;
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| 188 | uniformSubScopesProcessor2.Operator = evaluator;
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| 189 | uniformSubScopesProcessor2.Successor = subScopesCounter;
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| 190 |
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| 191 | evaluator.OperatorParameter.ActualName = EvaluatorParameter.Name;
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| 192 | evaluator.Successor = null;
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| 193 |
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| 194 | subScopesCounter.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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| 195 | subScopesCounter.AccumulateParameter.Value = new BoolValue(true);
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| 196 | subScopesCounter.Successor = null;
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| 197 |
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| 198 | replacementBranch.ConditionParameter.ActualName = PlusSelectionParameter.Name;
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| 199 | replacementBranch.TrueBranch = replacementMergingReducer;
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| 200 | replacementBranch.FalseBranch = subScopesProcessor2;
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| 201 | replacementBranch.Successor = incrementAgeProcessor;
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| 202 |
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| 203 | replacementMergingReducer.Successor = replacementBestSelector;
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| 204 |
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| 205 | replacementBestSelector.NumberOfSelectedSubScopesParameter.ActualName = PopulationSizeParameter.Name;
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| 206 | replacementBestSelector.CopySelected = new BoolValue(false);
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| 207 | replacementBestSelector.Successor = replacementRightReducer;
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| 208 |
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| 209 | replacementRightReducer.Successor = reevaluateElitesBranch;
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| 210 |
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| 211 | subScopesProcessor2.Operators.Add(bestSelector);
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| 212 | subScopesProcessor2.Operators.Add(new EmptyOperator());
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| 213 | subScopesProcessor2.Successor = mergingReducer;
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| 214 |
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| 215 | bestSelector.CopySelected = new BoolValue(false);
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| 216 | bestSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
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| 217 | bestSelector.NumberOfSelectedSubScopesParameter.ActualName = ElitesParameter.Name;
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| 218 | bestSelector.QualityParameter.ActualName = QualityParameter.Name;
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| 219 | bestSelector.Successor = rightReducer;
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| 220 |
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| 221 | rightReducer.Successor = reevaluateElitesBranch;
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| 222 |
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| 223 | mergingReducer.Successor = null;
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| 224 |
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| 225 | reevaluateElitesBranch.ConditionParameter.ActualName = ReevaluateElitesParameter.Name;
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| 226 | reevaluateElitesBranch.TrueBranch = uniformSubScopesProcessor2;
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| 227 | reevaluateElitesBranch.FalseBranch = null;
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| 228 | reevaluateElitesBranch.Successor = null;
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| 229 |
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| 230 |
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| 231 | incrementAgeProcessor.Operator = ageIncrementor;
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| 232 | incrementAgeProcessor.Successor = null;
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| 233 |
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| 234 | ageIncrementor.ValueParameter.ActualName = AgeParameter.Name;
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| 235 | ageIncrementor.IncrementParameter.Value = null;
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| 236 | ageIncrementor.IncrementParameter.ActualName = AgeIncrementParameter.Name;
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| 237 | ageIncrementor.Successor = null;
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| 238 | }
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| 239 | }
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| 240 | } |
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