#region License Information
/* HeuristicLab
* Copyright (C) 2002-2012 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 System;
using System.Linq;
using HeuristicLab.Analysis;
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;
using HeuristicLab.PluginInfrastructure;
using HeuristicLab.Random;
namespace HeuristicLab.Algorithms.GeneticAlgorithm {
///
/// An island genetic algorithm.
///
[Item("Island Genetic Algorithm", "An island genetic algorithm.")]
[Creatable("Algorithms")]
[StorableClass]
public sealed class IslandGeneticAlgorithm : HeuristicOptimizationEngineAlgorithm, IStorableContent {
public string Filename { get; set; }
#region Problem Properties
public override Type ProblemType {
get { return typeof(ISingleObjectiveHeuristicOptimizationProblem); }
}
public new ISingleObjectiveHeuristicOptimizationProblem Problem {
get { return (ISingleObjectiveHeuristicOptimizationProblem)base.Problem; }
set { base.Problem = value; }
}
#endregion
#region Parameter Properties
private ValueParameter SeedParameter {
get { return (ValueParameter)Parameters["Seed"]; }
}
private ValueParameter SetSeedRandomlyParameter {
get { return (ValueParameter)Parameters["SetSeedRandomly"]; }
}
private ValueParameter NumberOfIslandsParameter {
get { return (ValueParameter)Parameters["NumberOfIslands"]; }
}
private ValueParameter MigrationIntervalParameter {
get { return (ValueParameter)Parameters["MigrationInterval"]; }
}
private ValueParameter MigrationRateParameter {
get { return (ValueParameter)Parameters["MigrationRate"]; }
}
public IConstrainedValueParameter MigratorParameter {
get { return (IConstrainedValueParameter)Parameters["Migrator"]; }
}
public IConstrainedValueParameter EmigrantsSelectorParameter {
get { return (IConstrainedValueParameter)Parameters["EmigrantsSelector"]; }
}
public IConstrainedValueParameter ImmigrationReplacerParameter {
get { return (IConstrainedValueParameter)Parameters["ImmigrationReplacer"]; }
}
private ValueParameter PopulationSizeParameter {
get { return (ValueParameter)Parameters["PopulationSize"]; }
}
private ValueParameter MaximumGenerationsParameter {
get { return (ValueParameter)Parameters["MaximumGenerations"]; }
}
public IConstrainedValueParameter SelectorParameter {
get { return (IConstrainedValueParameter)Parameters["Selector"]; }
}
public IConstrainedValueParameter CrossoverParameter {
get { return (IConstrainedValueParameter)Parameters["Crossover"]; }
}
private ValueParameter MutationProbabilityParameter {
get { return (ValueParameter)Parameters["MutationProbability"]; }
}
public IConstrainedValueParameter MutatorParameter {
get { return (IConstrainedValueParameter)Parameters["Mutator"]; }
}
private ValueParameter ElitesParameter {
get { return (ValueParameter)Parameters["Elites"]; }
}
private ValueParameter AnalyzerParameter {
get { return (ValueParameter)Parameters["Analyzer"]; }
}
private ValueParameter IslandAnalyzerParameter {
get { return (ValueParameter)Parameters["IslandAnalyzer"]; }
}
#endregion
#region Properties
public IntValue Seed {
get { return SeedParameter.Value; }
set { SeedParameter.Value = value; }
}
public BoolValue SetSeedRandomly {
get { return SetSeedRandomlyParameter.Value; }
set { SetSeedRandomlyParameter.Value = value; }
}
public IntValue NumberOfIslands {
get { return NumberOfIslandsParameter.Value; }
set { NumberOfIslandsParameter.Value = value; }
}
public IntValue MigrationInterval {
get { return MigrationIntervalParameter.Value; }
set { MigrationIntervalParameter.Value = value; }
}
public PercentValue MigrationRate {
get { return MigrationRateParameter.Value; }
set { MigrationRateParameter.Value = value; }
}
public IMigrator Migrator {
get { return MigratorParameter.Value; }
set { MigratorParameter.Value = value; }
}
public ISelector EmigrantsSelector {
get { return EmigrantsSelectorParameter.Value; }
set { EmigrantsSelectorParameter.Value = value; }
}
public IReplacer ImmigrationReplacer {
get { return ImmigrationReplacerParameter.Value; }
set { ImmigrationReplacerParameter.Value = value; }
}
public IntValue PopulationSize {
get { return PopulationSizeParameter.Value; }
set { PopulationSizeParameter.Value = value; }
}
public IntValue MaximumGenerations {
get { return MaximumGenerationsParameter.Value; }
set { MaximumGenerationsParameter.Value = value; }
}
public ISelector Selector {
get { return SelectorParameter.Value; }
set { SelectorParameter.Value = value; }
}
public ICrossover Crossover {
get { return CrossoverParameter.Value; }
set { CrossoverParameter.Value = value; }
}
public PercentValue MutationProbability {
get { return MutationProbabilityParameter.Value; }
set { MutationProbabilityParameter.Value = value; }
}
public IManipulator Mutator {
get { return MutatorParameter.Value; }
set { MutatorParameter.Value = value; }
}
public IntValue Elites {
get { return ElitesParameter.Value; }
set { ElitesParameter.Value = value; }
}
public MultiAnalyzer Analyzer {
get { return AnalyzerParameter.Value; }
set { AnalyzerParameter.Value = value; }
}
public MultiAnalyzer IslandAnalyzer {
get { return IslandAnalyzerParameter.Value; }
set { IslandAnalyzerParameter.Value = value; }
}
private RandomCreator RandomCreator {
get { return (RandomCreator)OperatorGraph.InitialOperator; }
}
private UniformSubScopesProcessor IslandProcessor {
get { return ((RandomCreator.Successor as SubScopesCreator).Successor as UniformSubScopesProcessor); }
}
private SolutionsCreator SolutionsCreator {
get { return (SolutionsCreator)IslandProcessor.Operator; }
}
private IslandGeneticAlgorithmMainLoop MainLoop {
get { return FindMainLoop(IslandProcessor.Successor); }
}
[Storable]
private BestAverageWorstQualityAnalyzer islandQualityAnalyzer;
[Storable]
private BestAverageWorstQualityAnalyzer qualityAnalyzer;
#endregion
[StorableConstructor]
private IslandGeneticAlgorithm(bool deserializing) : base(deserializing) { }
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() {
Initialize();
}
private IslandGeneticAlgorithm(IslandGeneticAlgorithm original, Cloner cloner)
: base(original, cloner) {
islandQualityAnalyzer = cloner.Clone(original.islandQualityAnalyzer);
qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
Initialize();
}
public override IDeepCloneable Clone(Cloner cloner) {
return new IslandGeneticAlgorithm(this, cloner);
}
public IslandGeneticAlgorithm()
: base() {
Parameters.Add(new ValueParameter("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
Parameters.Add(new ValueParameter("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
Parameters.Add(new ValueParameter("NumberOfIslands", "The number of islands.", new IntValue(5)));
Parameters.Add(new ValueParameter("MigrationInterval", "The number of generations that should pass between migration phases.", new IntValue(20)));
Parameters.Add(new ValueParameter("MigrationRate", "The proportion of individuals that should migrate between the islands.", new PercentValue(0.15)));
Parameters.Add(new ConstrainedValueParameter("Migrator", "The migration strategy."));
Parameters.Add(new ConstrainedValueParameter("EmigrantsSelector", "Selects the individuals that will be migrated."));
Parameters.Add(new ConstrainedValueParameter("ImmigrationReplacer", "Selects the population from the unification of the original population and the immigrants."));
Parameters.Add(new ValueParameter("PopulationSize", "The size of the population of solutions.", new IntValue(100)));
Parameters.Add(new ValueParameter("MaximumGenerations", "The maximum number of generations that should be processed.", new IntValue(1000)));
Parameters.Add(new ConstrainedValueParameter("Selector", "The operator used to select solutions for reproduction."));
Parameters.Add(new ConstrainedValueParameter("Crossover", "The operator used to cross solutions."));
Parameters.Add(new ValueParameter("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
Parameters.Add(new OptionalConstrainedValueParameter("Mutator", "The operator used to mutate solutions."));
Parameters.Add(new ValueParameter("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
Parameters.Add(new ValueParameter("Analyzer", "The operator used to analyze the islands.", new MultiAnalyzer()));
Parameters.Add(new ValueParameter("IslandAnalyzer", "The operator used to analyze each island.", new MultiAnalyzer()));
RandomCreator randomCreator = new RandomCreator();
SubScopesCreator populationCreator = new SubScopesCreator();
UniformSubScopesProcessor ussp1 = new UniformSubScopesProcessor();
SolutionsCreator solutionsCreator = new SolutionsCreator();
VariableCreator variableCreator = new VariableCreator();
UniformSubScopesProcessor ussp2 = new UniformSubScopesProcessor();
SubScopesCounter subScopesCounter = new SubScopesCounter();
ResultsCollector resultsCollector = new ResultsCollector();
IslandGeneticAlgorithmMainLoop mainLoop = new IslandGeneticAlgorithmMainLoop();
OperatorGraph.InitialOperator = randomCreator;
randomCreator.RandomParameter.ActualName = "GlobalRandom";
randomCreator.SeedParameter.ActualName = SeedParameter.Name;
randomCreator.SeedParameter.Value = null;
randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
randomCreator.SetSeedRandomlyParameter.Value = null;
randomCreator.Successor = populationCreator;
populationCreator.NumberOfSubScopesParameter.ActualName = NumberOfIslandsParameter.Name;
populationCreator.Successor = ussp1;
ussp1.Operator = solutionsCreator;
ussp1.Successor = variableCreator;
solutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
//don't create solutions in parallel because the hive engine would distribute these tasks
solutionsCreator.ParallelParameter.Value = new BoolValue(false);
solutionsCreator.Successor = null;
variableCreator.Name = "Initialize EvaluatedSolutions";
variableCreator.CollectedValues.Add(new ValueParameter("EvaluatedSolutions", new IntValue()));
variableCreator.Successor = ussp2;
ussp2.Operator = subScopesCounter;
ussp2.Successor = resultsCollector;
subScopesCounter.Name = "Count EvaluatedSolutions";
subScopesCounter.ValueParameter.ActualName = "EvaluatedSolutions";
subScopesCounter.Successor = null;
resultsCollector.CollectedValues.Add(new LookupParameter("Evaluated Solutions", null, "EvaluatedSolutions"));
resultsCollector.ResultsParameter.ActualName = "Results";
resultsCollector.Successor = mainLoop;
mainLoop.EmigrantsSelectorParameter.ActualName = EmigrantsSelectorParameter.Name;
mainLoop.ImmigrationReplacerParameter.ActualName = ImmigrationReplacerParameter.Name;
mainLoop.MaximumGenerationsParameter.ActualName = MaximumGenerationsParameter.Name;
mainLoop.MigrationIntervalParameter.ActualName = MigrationIntervalParameter.Name;
mainLoop.MigrationRateParameter.ActualName = MigrationRateParameter.Name;
mainLoop.MigratorParameter.ActualName = MigratorParameter.Name;
mainLoop.NumberOfIslandsParameter.ActualName = NumberOfIslandsParameter.Name;
mainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
mainLoop.ElitesParameter.ActualName = ElitesParameter.Name;
mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
mainLoop.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
mainLoop.RandomParameter.ActualName = randomCreator.RandomParameter.ActualName;
mainLoop.ResultsParameter.ActualName = "Results";
mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
mainLoop.IslandAnalyzerParameter.ActualName = IslandAnalyzerParameter.Name;
mainLoop.EvaluatedSolutionsParameter.ActualName = "EvaluatedSolutions";
mainLoop.Successor = null;
foreach (ISelector selector in ApplicationManager.Manager.GetInstances().Where(x => !(x is IMultiObjectiveSelector)).OrderBy(x => x.Name))
SelectorParameter.ValidValues.Add(selector);
ISelector proportionalSelector = SelectorParameter.ValidValues.FirstOrDefault(x => x.GetType().Name.Equals("ProportionalSelector"));
if (proportionalSelector != null) SelectorParameter.Value = proportionalSelector;
foreach (ISelector selector in ApplicationManager.Manager.GetInstances().Where(x => !(x is IMultiObjectiveSelector)).OrderBy(x => x.Name))
EmigrantsSelectorParameter.ValidValues.Add(selector);
foreach (IReplacer replacer in ApplicationManager.Manager.GetInstances().OrderBy(x => x.Name))
ImmigrationReplacerParameter.ValidValues.Add(replacer);
ParameterizeSelectors();
foreach (IMigrator migrator in ApplicationManager.Manager.GetInstances().OrderBy(x => x.Name))
MigratorParameter.ValidValues.Add(migrator);
qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
islandQualityAnalyzer = new BestAverageWorstQualityAnalyzer();
ParameterizeAnalyzers();
UpdateAnalyzers();
Initialize();
}
public override void Prepare() {
if (Problem != null) base.Prepare();
}
#region Events
protected override void OnProblemChanged() {
ParameterizeStochasticOperator(Problem.SolutionCreator);
ParameterizeStochasticOperator(Problem.Evaluator);
foreach (IOperator op in Problem.Operators.OfType()) ParameterizeStochasticOperator(op);
ParameterizeSolutionsCreator();
ParameterizeMainLoop();
ParameterizeSelectors();
ParameterizeAnalyzers();
ParameterizeIterationBasedOperators();
UpdateCrossovers();
UpdateMutators();
UpdateAnalyzers();
Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
base.OnProblemChanged();
}
protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
ParameterizeStochasticOperator(Problem.SolutionCreator);
ParameterizeSolutionsCreator();
base.Problem_SolutionCreatorChanged(sender, e);
}
protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
ParameterizeStochasticOperator(Problem.Evaluator);
ParameterizeSolutionsCreator();
ParameterizeMainLoop();
ParameterizeSelectors();
ParameterizeAnalyzers();
Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
base.Problem_EvaluatorChanged(sender, e);
}
protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
foreach (IOperator op in Problem.Operators.OfType()) ParameterizeStochasticOperator(op);
ParameterizeIterationBasedOperators();
UpdateCrossovers();
UpdateMutators();
UpdateAnalyzers();
base.Problem_OperatorsChanged(sender, e);
}
private void ElitesParameter_ValueChanged(object sender, EventArgs e) {
Elites.ValueChanged += new EventHandler(Elites_ValueChanged);
ParameterizeSelectors();
}
private void Elites_ValueChanged(object sender, EventArgs e) {
ParameterizeSelectors();
}
private void PopulationSizeParameter_ValueChanged(object sender, EventArgs e) {
NumberOfIslands.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
ParameterizeSelectors();
}
private void PopulationSize_ValueChanged(object sender, EventArgs e) {
ParameterizeSelectors();
}
private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
ParameterizeMainLoop();
ParameterizeSelectors();
ParameterizeAnalyzers();
}
private void MigrationRateParameter_ValueChanged(object sender, EventArgs e) {
MigrationRate.ValueChanged += new EventHandler(MigrationRate_ValueChanged);
ParameterizeSelectors();
}
private void MigrationRate_ValueChanged(object sender, EventArgs e) {
ParameterizeSelectors();
}
#endregion
#region Helpers
private void Initialize() {
PopulationSizeParameter.ValueChanged += new EventHandler(PopulationSizeParameter_ValueChanged);
PopulationSize.ValueChanged += new EventHandler(PopulationSize_ValueChanged);
MigrationRateParameter.ValueChanged += new EventHandler(MigrationRateParameter_ValueChanged);
MigrationRate.ValueChanged += new EventHandler(MigrationRate_ValueChanged);
ElitesParameter.ValueChanged += new EventHandler(ElitesParameter_ValueChanged);
Elites.ValueChanged += new EventHandler(Elites_ValueChanged);
if (Problem != null) {
Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
}
}
private void ParameterizeSolutionsCreator() {
SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
}
private void ParameterizeMainLoop() {
MainLoop.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
MainLoop.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
}
private void ParameterizeStochasticOperator(IOperator op) {
IStochasticOperator stochasticOp = op as IStochasticOperator;
if (stochasticOp != null) {
stochasticOp.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
stochasticOp.RandomParameter.Hidden = true;
}
}
private void ParameterizeStochasticOperatorForIsland(IOperator op) {
IStochasticOperator stochasticOp = op as IStochasticOperator;
if (stochasticOp != null) {
stochasticOp.RandomParameter.ActualName = "LocalRandom";
stochasticOp.RandomParameter.Hidden = true;
}
}
private void ParameterizeSelectors() {
foreach (ISelector selector in SelectorParameter.ValidValues) {
selector.CopySelected = new BoolValue(true);
selector.NumberOfSelectedSubScopesParameter.Value = new IntValue(2 * (PopulationSize.Value - Elites.Value));
selector.NumberOfSelectedSubScopesParameter.Hidden = true;
ParameterizeStochasticOperatorForIsland(selector);
}
foreach (ISelector selector in EmigrantsSelectorParameter.ValidValues) {
selector.CopySelected = new BoolValue(true);
selector.NumberOfSelectedSubScopesParameter.Value = new IntValue((int)Math.Ceiling(PopulationSize.Value * MigrationRate.Value));
selector.NumberOfSelectedSubScopesParameter.Hidden = true;
ParameterizeStochasticOperator(selector);
}
foreach (IReplacer replacer in ImmigrationReplacerParameter.ValidValues) {
ParameterizeStochasticOperator(replacer);
}
if (Problem != null) {
foreach (ISingleObjectiveSelector selector in SelectorParameter.ValidValues.OfType()) {
selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
selector.MaximizationParameter.Hidden = true;
selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
selector.QualityParameter.Hidden = true;
}
foreach (ISingleObjectiveSelector selector in EmigrantsSelectorParameter.ValidValues.OfType()) {
selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
selector.MaximizationParameter.Hidden = true;
selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
selector.QualityParameter.Hidden = true;
}
foreach (ISingleObjectiveReplacer selector in ImmigrationReplacerParameter.ValidValues.OfType()) {
selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
selector.MaximizationParameter.Hidden = true;
selector.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
selector.QualityParameter.Hidden = true;
}
}
}
private void ParameterizeAnalyzers() {
islandQualityAnalyzer.ResultsParameter.ActualName = "Results";
islandQualityAnalyzer.ResultsParameter.Hidden = true;
islandQualityAnalyzer.QualityParameter.Depth = 1;
qualityAnalyzer.ResultsParameter.ActualName = "Results";
qualityAnalyzer.ResultsParameter.Hidden = true;
qualityAnalyzer.QualityParameter.Depth = 2;
if (Problem != null) {
islandQualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
islandQualityAnalyzer.MaximizationParameter.Hidden = true;
islandQualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
islandQualityAnalyzer.QualityParameter.Hidden = true;
islandQualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
islandQualityAnalyzer.BestKnownQualityParameter.Hidden = true;
qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
qualityAnalyzer.MaximizationParameter.Hidden = true;
qualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
qualityAnalyzer.QualityParameter.Hidden = true;
qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
qualityAnalyzer.BestKnownQualityParameter.Hidden = true;
}
}
private void ParameterizeIterationBasedOperators() {
if (Problem != null) {
foreach (IIterationBasedOperator op in Problem.Operators.OfType()) {
op.IterationsParameter.ActualName = "Generations";
op.IterationsParameter.Hidden = true;
op.MaximumIterationsParameter.ActualName = "MaximumGenerations";
op.MaximumIterationsParameter.Hidden = true;
}
}
}
private void UpdateCrossovers() {
ICrossover oldCrossover = CrossoverParameter.Value;
ICrossover defaultCrossover = Problem.Operators.OfType().FirstOrDefault();
CrossoverParameter.ValidValues.Clear();
foreach (ICrossover crossover in Problem.Operators.OfType().OrderBy(x => x.Name)) {
ParameterizeStochasticOperatorForIsland(crossover);
CrossoverParameter.ValidValues.Add(crossover);
}
if (oldCrossover != null) {
ICrossover crossover = CrossoverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldCrossover.GetType());
if (crossover != null) CrossoverParameter.Value = crossover;
else oldCrossover = null;
}
if (oldCrossover == null && defaultCrossover != null)
CrossoverParameter.Value = defaultCrossover;
}
private void UpdateMutators() {
IManipulator oldMutator = MutatorParameter.Value;
MutatorParameter.ValidValues.Clear();
foreach (IManipulator mutator in Problem.Operators.OfType().OrderBy(x => x.Name)) {
ParameterizeStochasticOperatorForIsland(mutator);
MutatorParameter.ValidValues.Add(mutator);
}
if (oldMutator != null) {
IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
if (mutator != null) MutatorParameter.Value = mutator;
}
}
private void UpdateAnalyzers() {
IslandAnalyzer.Operators.Clear();
Analyzer.Operators.Clear();
IslandAnalyzer.Operators.Add(islandQualityAnalyzer, islandQualityAnalyzer.EnabledByDefault);
if (Problem != null) {
foreach (IAnalyzer analyzer in Problem.Operators.OfType()) {
foreach (IScopeTreeLookupParameter param in analyzer.Parameters.OfType())
param.Depth = 2;
Analyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
}
}
Analyzer.Operators.Add(qualityAnalyzer, qualityAnalyzer.EnabledByDefault);
}
private IslandGeneticAlgorithmMainLoop FindMainLoop(IOperator start) {
IOperator mainLoop = start;
while (mainLoop != null && !(mainLoop is IslandGeneticAlgorithmMainLoop))
mainLoop = ((SingleSuccessorOperator)mainLoop).Successor;
if (mainLoop == null) return null;
else return (IslandGeneticAlgorithmMainLoop)mainLoop;
}
#endregion
}
}