#region License Information
/* HeuristicLab
* Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Optimization.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm {
///
/// An island offspring selection genetic algorithm main loop operator.
///
[Item("IslandOffspringSelectionGeneticAlgorithmMainLoop", "An island offspring selection genetic algorithm main loop operator.")]
[StorableClass]
public sealed class IslandOffspringSelectionGeneticAlgorithmMainLoop : AlgorithmOperator {
#region Parameter Properties
public ValueLookupParameter RandomParameter {
get { return (ValueLookupParameter)Parameters["Random"]; }
}
public ValueLookupParameter MaximizationParameter {
get { return (ValueLookupParameter)Parameters["Maximization"]; }
}
public ScopeTreeLookupParameter QualityParameter {
get { return (ScopeTreeLookupParameter)Parameters["Quality"]; }
}
public ValueLookupParameter BestKnownQualityParameter {
get { return (ValueLookupParameter)Parameters["BestKnownQuality"]; }
}
public ValueLookupParameter NumberOfIslandsParameter {
get { return (ValueLookupParameter)Parameters["NumberOfIslands"]; }
}
public ValueLookupParameter MigrationIntervalParameter {
get { return (ValueLookupParameter)Parameters["MigrationInterval"]; }
}
public ValueLookupParameter MigrationRateParameter {
get { return (ValueLookupParameter)Parameters["MigrationRate"]; }
}
public ValueLookupParameter MigratorParameter {
get { return (ValueLookupParameter)Parameters["Migrator"]; }
}
public ValueLookupParameter EmigrantsSelectorParameter {
get { return (ValueLookupParameter)Parameters["EmigrantsSelector"]; }
}
public ValueLookupParameter ImmigrationReplacerParameter {
get { return (ValueLookupParameter)Parameters["ImmigrationReplacer"]; }
}
public ValueLookupParameter PopulationSizeParameter {
get { return (ValueLookupParameter)Parameters["PopulationSize"]; }
}
public ValueLookupParameter MaximumGenerationsParameter {
get { return (ValueLookupParameter)Parameters["MaximumGenerations"]; }
}
public ValueLookupParameter SelectorParameter {
get { return (ValueLookupParameter)Parameters["Selector"]; }
}
public ValueLookupParameter CrossoverParameter {
get { return (ValueLookupParameter)Parameters["Crossover"]; }
}
public ValueLookupParameter MutationProbabilityParameter {
get { return (ValueLookupParameter)Parameters["MutationProbability"]; }
}
public ValueLookupParameter MutatorParameter {
get { return (ValueLookupParameter)Parameters["Mutator"]; }
}
public ValueLookupParameter EvaluatorParameter {
get { return (ValueLookupParameter)Parameters["Evaluator"]; }
}
public ValueLookupParameter ElitesParameter {
get { return (ValueLookupParameter)Parameters["Elites"]; }
}
public IValueLookupParameter ReevaluateElitesParameter {
get { return (IValueLookupParameter)Parameters["ReevaluateElites"]; }
}
public ValueLookupParameter ResultsParameter {
get { return (ValueLookupParameter)Parameters["Results"]; }
}
public ValueLookupParameter VisualizerParameter {
get { return (ValueLookupParameter)Parameters["Visualizer"]; }
}
public LookupParameter VisualizationParameter {
get { return (LookupParameter)Parameters["Visualization"]; }
}
public ValueLookupParameter SuccessRatioParameter {
get { return (ValueLookupParameter)Parameters["SuccessRatio"]; }
}
public LookupParameter ComparisonFactorParameter {
get { return (LookupParameter)Parameters["ComparisonFactor"]; }
}
public ValueLookupParameter ComparisonFactorStartParameter {
get { return (ValueLookupParameter)Parameters["ComparisonFactorStart"]; }
}
public ValueLookupParameter ComparisonFactorModifierParameter {
get { return (ValueLookupParameter)Parameters["ComparisonFactorModifier"]; }
}
public ValueLookupParameter MaximumSelectionPressureParameter {
get { return (ValueLookupParameter)Parameters["MaximumSelectionPressure"]; }
}
public ValueLookupParameter OffspringSelectionBeforeMutationParameter {
get { return (ValueLookupParameter)Parameters["OffspringSelectionBeforeMutation"]; }
}
public ValueLookupParameter AnalyzerParameter {
get { return (ValueLookupParameter)Parameters["Analyzer"]; }
}
public ValueLookupParameter IslandAnalyzerParameter {
get { return (ValueLookupParameter)Parameters["IslandAnalyzer"]; }
}
public LookupParameter EvaluatedSolutionsParameter {
get { return (LookupParameter)Parameters["EvaluatedSolutions"]; }
}
public IValueLookupParameter FillPopulationWithParentsParameter {
get { return (IValueLookupParameter)Parameters["FillPopulationWithParents"]; }
}
#endregion
[StorableConstructor]
private IslandOffspringSelectionGeneticAlgorithmMainLoop(bool deserializing) : base(deserializing) { }
private IslandOffspringSelectionGeneticAlgorithmMainLoop(IslandOffspringSelectionGeneticAlgorithmMainLoop original, Cloner cloner)
: base(original, cloner) {
}
public override IDeepCloneable Clone(Cloner cloner) {
return new IslandOffspringSelectionGeneticAlgorithmMainLoop(this, cloner);
}
public IslandOffspringSelectionGeneticAlgorithmMainLoop()
: base() {
#region Create parameters
Parameters.Add(new ValueLookupParameter("Random", "A pseudo random number generator."));
Parameters.Add(new ValueLookupParameter("Maximization", "True if the problem is a maximization problem, otherwise false."));
Parameters.Add(new ScopeTreeLookupParameter("Quality", "The value which represents the quality of a solution."));
Parameters.Add(new ValueLookupParameter("BestKnownQuality", "The best known quality value found so far."));
Parameters.Add(new ValueLookupParameter("NumberOfIslands", "The number of islands."));
Parameters.Add(new ValueLookupParameter("MigrationInterval", "The number of generations that should pass between migration phases."));
Parameters.Add(new ValueLookupParameter("MigrationRate", "The proportion of individuals that should migrate between the islands."));
Parameters.Add(new ValueLookupParameter("Migrator", "The migration strategy."));
Parameters.Add(new ValueLookupParameter("EmigrantsSelector", "Selects the individuals that will be migrated."));
Parameters.Add(new ValueLookupParameter("ImmigrationReplacer", "Replaces part of the original population with the immigrants."));
Parameters.Add(new ValueLookupParameter("PopulationSize", "The size of the population of solutions."));
Parameters.Add(new ValueLookupParameter("MaximumGenerations", "The maximum number of generations that should be processed."));
Parameters.Add(new ValueLookupParameter("Selector", "The operator used to select solutions for reproduction."));
Parameters.Add(new ValueLookupParameter("Crossover", "The operator used to cross solutions."));
Parameters.Add(new ValueLookupParameter("MutationProbability", "The probability that the mutation operator is applied on a solution."));
Parameters.Add(new ValueLookupParameter("Mutator", "The operator used to mutate solutions."));
Parameters.Add(new ValueLookupParameter("Evaluator", "The operator used to evaluate solutions. This operator is executed in parallel, if an engine is used which supports parallelization."));
Parameters.Add(new ValueLookupParameter("Elites", "The numer of elite solutions which are kept in each generation."));
Parameters.Add(new ValueLookupParameter("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
Parameters.Add(new ValueLookupParameter("Results", "The results collection to store the results."));
Parameters.Add(new ValueLookupParameter("Visualizer", "The operator used to visualize solutions."));
Parameters.Add(new LookupParameter("Visualization", "The item which represents the visualization of solutions."));
Parameters.Add(new ValueLookupParameter("SuccessRatio", "The ratio of successful to total children that should be achieved."));
Parameters.Add(new LookupParameter("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]."));
Parameters.Add(new ValueLookupParameter("ComparisonFactorStart", "The initial value for the comparison factor."));
Parameters.Add(new ValueLookupParameter("ComparisonFactorModifier", "The operator used to modify the comparison factor."));
Parameters.Add(new ValueLookupParameter("MaximumSelectionPressure", "The maximum selection pressure that terminates the algorithm."));
Parameters.Add(new ValueLookupParameter("OffspringSelectionBeforeMutation", "True if the offspring selection step should be applied before mutation, false if it should be applied after mutation."));
Parameters.Add(new ValueLookupParameter("Analyzer", "The operator used to the analyze the islands."));
Parameters.Add(new ValueLookupParameter("IslandAnalyzer", "The operator used to analyze each island."));
Parameters.Add(new LookupParameter("EvaluatedSolutions", "The number of times solutions have been evaluated."));
Parameters.Add(new ValueLookupParameter("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
#endregion
#region Create operators
VariableCreator variableCreator = new VariableCreator();
UniformSubScopesProcessor uniformSubScopesProcessor0 = new UniformSubScopesProcessor();
VariableCreator islandVariableCreator = new VariableCreator();
Placeholder islandAnalyzer1 = new Placeholder();
ResultsCollector islandResultsCollector1 = new ResultsCollector();
Assigner comparisonFactorInitializer = new Assigner();
Placeholder analyzer1 = new Placeholder();
ResultsCollector resultsCollector1 = new ResultsCollector();
UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
ConditionalBranch islandTerminatedBySelectionPressure1 = new ConditionalBranch();
OffspringSelectionGeneticAlgorithmMainOperator mainOperator = new OffspringSelectionGeneticAlgorithmMainOperator();
Placeholder islandAnalyzer2 = new Placeholder();
ResultsCollector islandResultsCollector2 = new ResultsCollector();
Comparator islandSelectionPressureComparator = new Comparator();
ConditionalBranch islandTerminatedBySelectionPressure2 = new ConditionalBranch();
IntCounter terminatedIslandsCounter = new IntCounter();
IntCounter generationsCounter = new IntCounter();
IntCounter generationsSinceLastMigrationCounter = new IntCounter();
Comparator migrationComparator = new Comparator();
ConditionalBranch migrationBranch = new ConditionalBranch();
Assigner resetTerminatedIslandsAssigner = new Assigner();
Assigner resetGenerationsSinceLastMigrationAssigner = new Assigner();
IntCounter migrationsCounter = new IntCounter();
UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
Assigner reviveIslandAssigner = new Assigner();
Placeholder emigrantsSelector = new Placeholder();
Placeholder migrator = new Placeholder();
UniformSubScopesProcessor uniformSubScopesProcessor3 = new UniformSubScopesProcessor();
Placeholder immigrationReplacer = new Placeholder();
Comparator generationsComparator = new Comparator();
Comparator terminatedIslandsComparator = new Comparator();
Comparator maxEvaluatedSolutionsComparator = new Comparator();
Placeholder comparisonFactorModifier = new Placeholder();
Placeholder analyzer2 = new Placeholder();
ConditionalBranch generationsTerminationCondition = new ConditionalBranch();
ConditionalBranch terminatedIslandsCondition = new ConditionalBranch();
ConditionalBranch evaluatedSolutionsTerminationCondition = new ConditionalBranch();
variableCreator.CollectedValues.Add(new ValueParameter("Migrations", new IntValue(0)));
variableCreator.CollectedValues.Add(new ValueParameter("Generations", new IntValue(0))); // Class IslandOffspringSelectionGeneticAlgorithm expects this to be called Generations
variableCreator.CollectedValues.Add(new ValueParameter("GenerationsSinceLastMigration", new IntValue(0)));
variableCreator.CollectedValues.Add(new ValueParameter("TerminatedIslands", new IntValue(0)));
islandVariableCreator.CollectedValues.Add(new ValueParameter(ResultsParameter.Name, new ResultCollection()));
islandVariableCreator.CollectedValues.Add(new ValueParameter("TerminateSelectionPressure", new BoolValue(false)));
islandVariableCreator.CollectedValues.Add(new ValueParameter("SelectionPressure", new DoubleValue(0)));
islandAnalyzer1.Name = "Island Analyzer (placeholder)";
islandAnalyzer1.OperatorParameter.ActualName = IslandAnalyzerParameter.Name;
islandResultsCollector1.CollectedValues.Add(new LookupParameter("Current Selection Pressure", "Displays the rising selection pressure during a generation.", "SelectionPressure"));
islandResultsCollector1.CollectedValues.Add(new LookupParameter("Current Success Ratio", "Indicates how many successful children were already found during a generation (relative to the population size).", "CurrentSuccessRatio"));
islandResultsCollector1.ResultsParameter.ActualName = ResultsParameter.Name;
comparisonFactorInitializer.Name = "Initialize Comparison Factor";
comparisonFactorInitializer.LeftSideParameter.ActualName = ComparisonFactorParameter.Name;
comparisonFactorInitializer.RightSideParameter.ActualName = ComparisonFactorStartParameter.Name;
analyzer1.Name = "Analyzer (placeholder)";
analyzer1.OperatorParameter.ActualName = AnalyzerParameter.Name;
resultsCollector1.CopyValue = new BoolValue(false);
resultsCollector1.CollectedValues.Add(new LookupParameter("Migrations"));
resultsCollector1.CollectedValues.Add(new LookupParameter("Generations"));
resultsCollector1.CollectedValues.Add(new LookupParameter("Current Comparison Factor", null, ComparisonFactorParameter.Name));
resultsCollector1.CollectedValues.Add(new ScopeTreeLookupParameter("IslandResults", "Result set for each island", ResultsParameter.Name));
resultsCollector1.ResultsParameter.ActualName = ResultsParameter.Name;
islandTerminatedBySelectionPressure1.Name = "Island Terminated ?";
islandTerminatedBySelectionPressure1.ConditionParameter.ActualName = "TerminateSelectionPressure";
mainOperator.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
mainOperator.CrossoverParameter.ActualName = CrossoverParameter.Name;
mainOperator.CurrentSuccessRatioParameter.ActualName = "CurrentSuccessRatio";
mainOperator.ElitesParameter.ActualName = ElitesParameter.Name;
mainOperator.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name;
mainOperator.EvaluatedSolutionsParameter.ActualName = EvaluatedSolutionsParameter.Name;
mainOperator.EvaluatorParameter.ActualName = EvaluatorParameter.Name;
mainOperator.MaximizationParameter.ActualName = MaximizationParameter.Name;
mainOperator.MaximumSelectionPressureParameter.ActualName = MaximumSelectionPressureParameter.Name;
mainOperator.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
mainOperator.MutatorParameter.ActualName = MutatorParameter.Name;
mainOperator.OffspringSelectionBeforeMutationParameter.ActualName = OffspringSelectionBeforeMutationParameter.Name;
mainOperator.QualityParameter.ActualName = QualityParameter.Name;
mainOperator.RandomParameter.ActualName = RandomParameter.Name;
mainOperator.SelectionPressureParameter.ActualName = "SelectionPressure";
mainOperator.SelectorParameter.ActualName = SelectorParameter.Name;
mainOperator.SuccessRatioParameter.ActualName = SuccessRatioParameter.Name;
mainOperator.FillPopulationWithParentsParameter.ActualName = FillPopulationWithParentsParameter.Name;
islandAnalyzer2.Name = "Island Analyzer (placeholder)";
islandAnalyzer2.OperatorParameter.ActualName = IslandAnalyzerParameter.Name;
islandResultsCollector2.CollectedValues.Add(new LookupParameter("Current Selection Pressure", "Displays the rising selection pressure during a generation.", "SelectionPressure"));
islandResultsCollector2.CollectedValues.Add(new LookupParameter("Current Success Ratio", "Indicates how many successful children were already found during a generation (relative to the population size).", "CurrentSuccessRatio"));
islandResultsCollector2.ResultsParameter.ActualName = "Results";
islandSelectionPressureComparator.Name = "SelectionPressure >= MaximumSelectionPressure ?";
islandSelectionPressureComparator.LeftSideParameter.ActualName = "SelectionPressure";
islandSelectionPressureComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
islandSelectionPressureComparator.RightSideParameter.ActualName = MaximumSelectionPressureParameter.Name;
islandSelectionPressureComparator.ResultParameter.ActualName = "TerminateSelectionPressure";
islandTerminatedBySelectionPressure2.Name = "Island Terminated ?";
islandTerminatedBySelectionPressure2.ConditionParameter.ActualName = "TerminateSelectionPressure";
terminatedIslandsCounter.Name = "TerminatedIslands + 1";
terminatedIslandsCounter.ValueParameter.ActualName = "TerminatedIslands";
terminatedIslandsCounter.Increment = new IntValue(1);
generationsCounter.Name = "Generations + 1";
generationsCounter.ValueParameter.ActualName = "Generations";
generationsCounter.Increment = new IntValue(1);
generationsSinceLastMigrationCounter.Name = "GenerationsSinceLastMigration + 1";
generationsSinceLastMigrationCounter.ValueParameter.ActualName = "GenerationsSinceLastMigration";
generationsSinceLastMigrationCounter.Increment = new IntValue(1);
migrationComparator.Name = "GenerationsSinceLastMigration = MigrationInterval ?";
migrationComparator.LeftSideParameter.ActualName = "GenerationsSinceLastMigration";
migrationComparator.Comparison = new Comparison(ComparisonType.Equal);
migrationComparator.RightSideParameter.ActualName = MigrationIntervalParameter.Name;
migrationComparator.ResultParameter.ActualName = "Migrate";
migrationBranch.Name = "Migrate?";
migrationBranch.ConditionParameter.ActualName = "Migrate";
resetTerminatedIslandsAssigner.Name = "Reset TerminatedIslands";
resetTerminatedIslandsAssigner.LeftSideParameter.ActualName = "TerminatedIslands";
resetTerminatedIslandsAssigner.RightSideParameter.Value = new IntValue(0);
resetGenerationsSinceLastMigrationAssigner.Name = "Reset GenerationsSinceLastMigration";
resetGenerationsSinceLastMigrationAssigner.LeftSideParameter.ActualName = "GenerationsSinceLastMigration";
resetGenerationsSinceLastMigrationAssigner.RightSideParameter.Value = new IntValue(0);
migrationsCounter.Name = "Migrations + 1";
migrationsCounter.IncrementParameter.Value = new IntValue(1);
migrationsCounter.ValueParameter.ActualName = "Migrations";
reviveIslandAssigner.Name = "Revive Island";
reviveIslandAssigner.LeftSideParameter.ActualName = "TerminateSelectionPressure";
reviveIslandAssigner.RightSideParameter.Value = new BoolValue(false);
emigrantsSelector.Name = "Emigrants Selector (placeholder)";
emigrantsSelector.OperatorParameter.ActualName = EmigrantsSelectorParameter.Name;
migrator.Name = "Migrator (placeholder)";
migrator.OperatorParameter.ActualName = MigratorParameter.Name;
immigrationReplacer.Name = "Immigration Replacer (placeholder)";
immigrationReplacer.OperatorParameter.ActualName = ImmigrationReplacerParameter.Name;
generationsComparator.Name = "Generations >= MaximumGenerations ?";
generationsComparator.LeftSideParameter.ActualName = "Generations";
generationsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
generationsComparator.RightSideParameter.ActualName = MaximumGenerationsParameter.Name;
generationsComparator.ResultParameter.ActualName = "TerminateGenerations";
terminatedIslandsComparator.Name = "All Islands terminated ?";
terminatedIslandsComparator.LeftSideParameter.ActualName = "TerminatedIslands";
terminatedIslandsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
terminatedIslandsComparator.RightSideParameter.ActualName = NumberOfIslandsParameter.Name;
terminatedIslandsComparator.ResultParameter.ActualName = "TerminateTerminatedIslands";
maxEvaluatedSolutionsComparator.Name = "EvaluatedSolutions >= MaximumEvaluatedSolutions ?";
maxEvaluatedSolutionsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
maxEvaluatedSolutionsComparator.LeftSideParameter.ActualName = EvaluatedSolutionsParameter.Name;
maxEvaluatedSolutionsComparator.ResultParameter.ActualName = "TerminateEvaluatedSolutions";
maxEvaluatedSolutionsComparator.RightSideParameter.ActualName = "MaximumEvaluatedSolutions";
comparisonFactorModifier.Name = "Update Comparison Factor (Placeholder)";
comparisonFactorModifier.OperatorParameter.ActualName = ComparisonFactorModifierParameter.Name;
analyzer2.Name = "Analyzer (placeholder)";
analyzer2.OperatorParameter.ActualName = AnalyzerParameter.Name;
generationsTerminationCondition.Name = "Terminate (MaxGenerations) ?";
generationsTerminationCondition.ConditionParameter.ActualName = "TerminateGenerations";
terminatedIslandsCondition.Name = "Terminate (TerminatedIslands) ?";
terminatedIslandsCondition.ConditionParameter.ActualName = "TerminateTerminatedIslands";
evaluatedSolutionsTerminationCondition.Name = "Terminate (EvaluatedSolutions) ?";
evaluatedSolutionsTerminationCondition.ConditionParameter.ActualName = "TerminateEvaluatedSolutions";
#endregion
#region Create operator graph
OperatorGraph.InitialOperator = variableCreator;
variableCreator.Successor = uniformSubScopesProcessor0;
uniformSubScopesProcessor0.Operator = islandVariableCreator;
uniformSubScopesProcessor0.Successor = comparisonFactorInitializer;
islandVariableCreator.Successor = islandAnalyzer1;
islandAnalyzer1.Successor = islandResultsCollector1;
islandResultsCollector1.Successor = null;
comparisonFactorInitializer.Successor = analyzer1;
analyzer1.Successor = resultsCollector1;
resultsCollector1.Successor = uniformSubScopesProcessor1;
uniformSubScopesProcessor1.Operator = islandTerminatedBySelectionPressure1;
uniformSubScopesProcessor1.Successor = generationsCounter;
islandTerminatedBySelectionPressure1.TrueBranch = null;
islandTerminatedBySelectionPressure1.FalseBranch = mainOperator;
islandTerminatedBySelectionPressure1.Successor = null;
mainOperator.Successor = islandAnalyzer2;
islandAnalyzer2.Successor = islandResultsCollector2;
islandResultsCollector2.Successor = islandSelectionPressureComparator;
islandSelectionPressureComparator.Successor = islandTerminatedBySelectionPressure2;
islandTerminatedBySelectionPressure2.TrueBranch = terminatedIslandsCounter;
islandTerminatedBySelectionPressure2.FalseBranch = null;
islandTerminatedBySelectionPressure2.Successor = null;
generationsCounter.Successor = generationsSinceLastMigrationCounter;
generationsSinceLastMigrationCounter.Successor = migrationComparator;
migrationComparator.Successor = migrationBranch;
migrationBranch.TrueBranch = resetTerminatedIslandsAssigner;
migrationBranch.FalseBranch = null;
migrationBranch.Successor = generationsComparator;
resetTerminatedIslandsAssigner.Successor = resetGenerationsSinceLastMigrationAssigner;
resetGenerationsSinceLastMigrationAssigner.Successor = migrationsCounter;
migrationsCounter.Successor = uniformSubScopesProcessor2;
uniformSubScopesProcessor2.Operator = reviveIslandAssigner;
uniformSubScopesProcessor2.Successor = migrator;
reviveIslandAssigner.Successor = emigrantsSelector;
emigrantsSelector.Successor = null;
migrator.Successor = uniformSubScopesProcessor3;
uniformSubScopesProcessor3.Operator = immigrationReplacer;
uniformSubScopesProcessor3.Successor = null;
immigrationReplacer.Successor = null;
generationsComparator.Successor = terminatedIslandsComparator;
terminatedIslandsComparator.Successor = maxEvaluatedSolutionsComparator;
maxEvaluatedSolutionsComparator.Successor = comparisonFactorModifier;
comparisonFactorModifier.Successor = analyzer2;
analyzer2.Successor = generationsTerminationCondition;
generationsTerminationCondition.TrueBranch = null;
generationsTerminationCondition.FalseBranch = terminatedIslandsCondition;
generationsTerminationCondition.Successor = null;
terminatedIslandsCondition.TrueBranch = null;
terminatedIslandsCondition.FalseBranch = evaluatedSolutionsTerminationCondition;
terminatedIslandsCondition.Successor = null;
evaluatedSolutionsTerminationCondition.TrueBranch = null;
evaluatedSolutionsTerminationCondition.FalseBranch = uniformSubScopesProcessor1;
evaluatedSolutionsTerminationCondition.Successor = null;
#endregion
}
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() {
// BackwardsCompatibility3.3
#region Backwards compatible code, remove with 3.4
if (!Parameters.ContainsKey("ReevaluateElites")) {
Parameters.Add(new ValueLookupParameter("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
}
if (!Parameters.ContainsKey("FillPopulationWithParents"))
Parameters.Add(new ValueLookupParameter("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
#endregion
}
public override IOperation Apply() {
if (CrossoverParameter.ActualValue == null)
return null;
return base.Apply();
}
}
}