[11051] | 1 | using System;
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| 2 | using System.Linq;
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| 3 | using System.Threading;
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[13285] | 4 | using HeuristicLab.Algorithms.ALPS;
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[11051] | 5 | using HeuristicLab.Algorithms.EvolutionStrategy;
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| 6 | using HeuristicLab.Algorithms.GeneticAlgorithm;
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| 7 | using HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm;
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| 8 | using HeuristicLab.Data;
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| 9 | using HeuristicLab.Optimization;
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| 10 | using HeuristicLab.Selection;
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| 11 | using Microsoft.VisualStudio.TestTools.UnitTesting;
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| 12 |
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| 13 | namespace HeuristicLab.Tests {
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| 14 | public static class SamplesUtils {
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[11907] | 15 | public const string SamplesDirectory = @"Samples\";
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| 16 | public const string SampleFileExtension = ".hl";
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[11051] | 17 |
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| 18 | public static void RunAlgorithm(IAlgorithm a) {
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| 19 | var trigger = new EventWaitHandle(false, EventResetMode.ManualReset);
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| 20 | Exception ex = null;
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| 21 | a.Stopped += (src, e) => { trigger.Set(); };
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| 22 | a.ExceptionOccurred += (src, e) => { ex = e.Value; trigger.Set(); };
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| 23 | a.Prepare();
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| 24 | a.Start();
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| 25 | trigger.WaitOne();
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| 26 |
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| 27 | Assert.AreEqual(ex, null);
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| 28 | }
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| 29 |
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| 30 | public static double GetDoubleResult(IAlgorithm a, string resultName) {
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| 31 | return ((DoubleValue)a.Results[resultName].Value).Value;
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| 32 | }
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| 33 |
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| 34 | public static int GetIntResult(IAlgorithm a, string resultName) {
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| 35 | return ((IntValue)a.Results[resultName].Value).Value;
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| 36 | }
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| 37 |
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| 38 | public static void ConfigureEvolutionStrategyParameters<R, M, SC, SR, SM>(EvolutionStrategy es, int popSize, int children, int parentsPerChild, int maxGens, bool plusSelection)
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| 39 | where R : ICrossover
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| 40 | where M : IManipulator
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| 41 | where SC : IStrategyParameterCreator
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| 42 | where SR : IStrategyParameterCrossover
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| 43 | where SM : IStrategyParameterManipulator {
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| 44 | es.PopulationSize.Value = popSize;
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| 45 | es.Children.Value = children;
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| 46 | es.ParentsPerChild.Value = parentsPerChild;
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| 47 | es.MaximumGenerations.Value = maxGens;
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| 48 | es.PlusSelection.Value = false;
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| 49 |
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| 50 | es.Seed.Value = 0;
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| 51 | es.SetSeedRandomly.Value = true;
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| 52 |
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| 53 | es.Recombinator = es.RecombinatorParameter.ValidValues
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| 54 | .OfType<R>()
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| 55 | .Single();
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| 56 |
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| 57 | es.Mutator = es.MutatorParameter.ValidValues
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| 58 | .OfType<M>()
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| 59 | .Single();
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| 60 |
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| 61 | es.StrategyParameterCreator = es.StrategyParameterCreatorParameter.ValidValues
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| 62 | .OfType<SC>()
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| 63 | .Single();
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| 64 | es.StrategyParameterCrossover = es.StrategyParameterCrossoverParameter.ValidValues
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| 65 | .OfType<SR>()
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| 66 | .Single();
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| 67 | es.StrategyParameterManipulator = es.StrategyParameterManipulatorParameter.ValidValues
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| 68 | .OfType<SM>()
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| 69 | .Single();
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| 70 | es.Engine = new ParallelEngine.ParallelEngine();
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| 71 | }
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| 72 |
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| 73 | public static void ConfigureGeneticAlgorithmParameters<S, C, M>(GeneticAlgorithm ga, int popSize, int elites, int maxGens, double mutationRate, int tournGroupSize = 0)
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| 74 | where S : ISelector
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| 75 | where C : ICrossover
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| 76 | where M : IManipulator {
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| 77 | ga.Elites.Value = elites;
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| 78 | ga.MaximumGenerations.Value = maxGens;
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| 79 | ga.MutationProbability.Value = mutationRate;
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| 80 | ga.PopulationSize.Value = popSize;
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| 81 | ga.Seed.Value = 0;
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| 82 | ga.SetSeedRandomly.Value = true;
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| 83 | ga.Selector = ga.SelectorParameter.ValidValues
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| 84 | .OfType<S>()
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| 85 | .First();
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| 86 |
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| 87 | ga.Crossover = ga.CrossoverParameter.ValidValues
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| 88 | .OfType<C>()
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| 89 | .First();
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| 90 |
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| 91 | ga.Mutator = ga.MutatorParameter.ValidValues
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| 92 | .OfType<M>()
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| 93 | .First();
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| 94 |
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| 95 | var tSelector = ga.Selector as TournamentSelector;
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| 96 | if (tSelector != null) {
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| 97 | tSelector.GroupSizeParameter.Value.Value = tournGroupSize;
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| 98 | }
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| 99 | ga.Engine = new ParallelEngine.ParallelEngine();
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| 100 | }
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| 101 |
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| 102 | public static void ConfigureOsGeneticAlgorithmParameters<S, C, M>(OffspringSelectionGeneticAlgorithm ga, int popSize, int elites, int maxGens, double mutationRate = 0.05, double maxSelPres = 100, int tournGroupSize = 0)
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| 103 | where S : ISelector
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| 104 | where C : ICrossover
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| 105 | where M : IManipulator {
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| 106 | ga.Elites.Value = elites;
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| 107 | ga.MaximumGenerations.Value = maxGens;
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| 108 | ga.MutationProbability.Value = mutationRate;
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| 109 | ga.PopulationSize.Value = popSize;
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| 110 | ga.MaximumSelectionPressure.Value = maxSelPres;
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| 111 | ga.Seed.Value = 0;
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| 112 | ga.SetSeedRandomly.Value = true;
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| 113 | ga.ComparisonFactorLowerBound.Value = 1;
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| 114 | ga.ComparisonFactorUpperBound.Value = 1;
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| 115 |
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| 116 | ga.Selector = ga.SelectorParameter.ValidValues
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| 117 | .OfType<S>()
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| 118 | .First();
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| 119 |
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| 120 | ga.Crossover = ga.CrossoverParameter.ValidValues
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| 121 | .OfType<C>()
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| 122 | .First();
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| 123 |
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| 124 | ga.Mutator = ga.MutatorParameter.ValidValues
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| 125 | .OfType<M>()
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| 126 | .First();
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| 127 |
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| 128 | var tSelector = ga.Selector as TournamentSelector;
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| 129 | if (tSelector != null) {
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| 130 | tSelector.GroupSizeParameter.Value.Value = tournGroupSize;
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| 131 | }
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| 132 | ga.Engine = new ParallelEngine.ParallelEngine();
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| 133 | }
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| 134 |
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| 135 | public static void ConfigureIslandGeneticAlgorithmParameters<S, C, M, Mi, MiS, MiR>(IslandGeneticAlgorithm ga, int popSize, int elites, int maxGens, double mutationRate, int numberOfIslands, int migrationInterval, double migrationRate)
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| 136 | where S : ISelector
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| 137 | where C : ICrossover
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| 138 | where M : IManipulator
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| 139 | where Mi : IMigrator
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| 140 | where MiS : ISelector
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| 141 | where MiR : IReplacer {
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| 142 | ga.Elites.Value = elites;
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| 143 | ga.MaximumGenerations.Value = maxGens;
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| 144 | ga.MutationProbability.Value = mutationRate;
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| 145 | ga.PopulationSize.Value = popSize;
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| 146 | ga.NumberOfIslands.Value = numberOfIslands;
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| 147 | ga.MigrationInterval.Value = migrationInterval;
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| 148 | ga.MigrationRate.Value = migrationRate;
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| 149 | ga.Seed.Value = 0;
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| 150 | ga.SetSeedRandomly.Value = true;
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| 151 | ga.Selector = ga.SelectorParameter.ValidValues
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| 152 | .OfType<S>()
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| 153 | .Single();
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| 154 |
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| 155 | ga.Crossover = ga.CrossoverParameter.ValidValues
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| 156 | .OfType<C>()
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| 157 | .Single();
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| 158 |
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| 159 | ga.Mutator = ga.MutatorParameter.ValidValues
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| 160 | .OfType<M>()
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| 161 | .Single();
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| 162 | ga.Migrator = ga.MigratorParameter.ValidValues
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| 163 | .OfType<Mi>()
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| 164 | .Single();
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| 165 | ga.EmigrantsSelector = ga.EmigrantsSelectorParameter.ValidValues
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| 166 | .OfType<MiS>()
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| 167 | .Single();
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| 168 | ga.ImmigrationReplacer = ga.ImmigrationReplacerParameter.ValidValues
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| 169 | .OfType<MiR>()
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| 170 | .Single();
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| 171 | ga.Engine = new ParallelEngine.ParallelEngine();
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| 172 | }
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[13285] | 173 |
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| 174 | public static void ConfigureAlpsGeneticAlgorithmParameters<S, C, M>(AlpsGeneticAlgorithm ga, int numberOfLayers, int popSize, double mutationRate, int elites, bool plusSelection, AgingScheme agingScheme, int ageGap, double ageInheritance, int maxGens)
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| 175 | where S : ISelector
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| 176 | where C : ICrossover
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| 177 | where M : IManipulator {
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| 178 | ga.Seed.Value = 0;
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| 179 | ga.SetSeedRandomly.Value = true;
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| 180 |
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| 181 | ga.NumberOfLayers.Value = numberOfLayers;
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| 182 | ga.PopulationSize.Value = popSize;
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| 183 |
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| 184 | ga.Selector = ga.SelectorParameter.ValidValues.OfType<S>().Single();
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| 185 | ga.Crossover = ga.CrossoverParameter.ValidValues.OfType<C>().Single();
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| 186 | ga.Mutator = ga.MutatorParameter.ValidValues.OfType<M>().Single();
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| 187 | ga.MutationProbability.Value = mutationRate;
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| 188 | ga.Elites.Value = elites;
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| 189 | ga.PlusSelection = plusSelection;
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| 190 |
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| 191 | ga.AgingScheme = new EnumValue<AgingScheme>(agingScheme);
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| 192 | ga.AgeGap.Value = ageGap;
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| 193 | ga.AgeInheritance.Value = ageInheritance;
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| 194 |
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| 195 | ga.MaximumGenerations = maxGens;
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| 196 |
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| 197 | ga.Engine = new ParallelEngine.ParallelEngine();
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| 198 | }
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[11051] | 199 | }
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| 200 | } |
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