public AlpsGeneticAlgorithm()
: base() {
#region Add parameters
Parameters.Add(new ValueParameter<IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
Parameters.Add(new ValueParameter<BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
Parameters.Add(new FixedValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze all individuals from all layers combined.", new MultiAnalyzer()));
Parameters.Add(new FixedValueParameter<MultiAnalyzer>("LayerAnalyzer", "The operator used to analyze each layer.", new MultiAnalyzer()));
Parameters.Add(new ValueParameter<IntValue>("NumberOfLayers", "The number of layers.", new IntValue(10)));
Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "The size of the population of solutions in each layer.", new IntValue(100)));
Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions for reproduction."));
Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
Parameters.Add(new FixedValueParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)", new BoolValue(false)) { Hidden = true });
Parameters.Add(new ValueParameter<BoolValue>("PlusSelection", "Include the parents in the selection of the invividuals for the next generation.", new BoolValue(false)));
Parameters.Add(new ValueParameter<EnumValue<AgingScheme>>("AgingScheme", "The aging scheme for setting the age-limits for the layers.", new EnumValue<AgingScheme>(ALPS.AgingScheme.Polynomial)));
Parameters.Add(new ValueParameter<IntValue>("AgeGap", "The frequency of reseeding the lowest layer and scaling factor for the age-limits for the layers.", new IntValue(20)));
Parameters.Add(new ValueParameter<DoubleValue>("AgeInheritance", "A weight that determines the age of a child after crossover based on the older (1.0) and younger (0.0) parent.", new DoubleValue(1.0)) { Hidden = true });
Parameters.Add(new ValueParameter<IntArray>("AgeLimits", "The maximum age an individual is allowed to reach in a certain layer.", new IntArray(new int[0])) { Hidden = true });
Parameters.Add(new ValueParameter<IntValue>("MatingPoolRange", "The range of layers used for creating a mating pool. (1 = current + previous layer)", new IntValue(1)) { Hidden = true });
Parameters.Add(new ValueParameter<BoolValue>("ReduceToPopulationSize", "Reduce the CurrentPopulationSize after elder migration to PopulationSize", new BoolValue(true)) { Hidden = true });
Parameters.Add(new ValueParameter<MultiTerminator>("Terminator", "The termination criteria that defines if the algorithm should continue or stop.", new MultiTerminator()));
#endregion
#region Create operators
var globalRandomCreator = new RandomCreator();
var layer0Creator = new SubScopesCreator() { Name = "Create Layer Zero" };
var layer0Processor = new SubScopesProcessor();
var localRandomCreator = new LocalRandomCreator();
var layerSolutionsCreator = new SolutionsCreator();
var initializeAgeProcessor = new UniformSubScopesProcessor();
var initializeAge = new VariableCreator() { Name = "Initialize Age" };
var initializeCurrentPopulationSize = new SubScopesCounter() { Name = "Initialize CurrentPopulationCounter" };
var initializeLocalEvaluatedSolutions = new Assigner() { Name = "Initialize LayerEvaluatedSolutions" };
var initializeGlobalEvaluatedSolutions = new DataReducer() { Name = "Initialize EvaluatedSolutions" };
var resultsCollector = new ResultsCollector();
var mainLoop = new AlpsGeneticAlgorithmMainLoop();
#endregion
#region Create and parameterize operator graph
OperatorGraph.InitialOperator = globalRandomCreator;
globalRandomCreator.RandomParameter.ActualName = "GlobalRandom";
globalRandomCreator.SeedParameter.Value = null;
globalRandomCreator.SeedParameter.ActualName = SeedParameter.Name;
globalRandomCreator.SetSeedRandomlyParameter.Value = null;
globalRandomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
globalRandomCreator.Successor = layer0Creator;
layer0Creator.NumberOfSubScopesParameter.Value = new IntValue(1);
layer0Creator.Successor = layer0Processor;
layer0Processor.Operators.Add(localRandomCreator);
layer0Processor.Successor = initializeGlobalEvaluatedSolutions;
localRandomCreator.Successor = layerSolutionsCreator;
layerSolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
layerSolutionsCreator.Successor = initializeAgeProcessor;
initializeAgeProcessor.Operator = initializeAge;
initializeAgeProcessor.Successor = initializeCurrentPopulationSize;
initializeCurrentPopulationSize.ValueParameter.ActualName = "CurrentPopulationSize";
initializeCurrentPopulationSize.Successor = initializeLocalEvaluatedSolutions;
initializeAge.CollectedValues.Add(new ValueParameter<DoubleValue>("Age", new DoubleValue(0)));
initializeAge.Successor = null;
initializeLocalEvaluatedSolutions.LeftSideParameter.ActualName = "LayerEvaluatedSolutions";
initializeLocalEvaluatedSolutions.RightSideParameter.ActualName = "CurrentPopulationSize";
initializeLocalEvaluatedSolutions.Successor = null;
initializeGlobalEvaluatedSolutions.ReductionOperation.Value.Value = ReductionOperations.Sum;
initializeGlobalEvaluatedSolutions.TargetOperation.Value.Value = ReductionOperations.Assign;
initializeGlobalEvaluatedSolutions.ParameterToReduce.ActualName = "LayerEvaluatedSolutions";
initializeGlobalEvaluatedSolutions.TargetParameter.ActualName = "EvaluatedSolutions";
initializeGlobalEvaluatedSolutions.Successor = resultsCollector;
resultsCollector.CollectedValues.Add(new LookupParameter<IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
resultsCollector.Successor = mainLoop;
mainLoop.GlobalRandomParameter.ActualName = "GlobalRandom";
mainLoop.LocalRandomParameter.ActualName = localRandomCreator.LocalRandomParameter.Name;
mainLoop.EvaluatedSolutionsParameter.ActualName = "EvaluatedSolutions";
mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
mainLoop.LayerAnalyzerParameter.ActualName = LayerAnalyzerParameter.Name;
mainLoop.NumberOfLayersParameter.ActualName = NumberOfLayersParameter.Name;
mainLoop.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
mainLoop.CurrentPopulationSizeParameter.ActualName = "CurrentPopulationSize";
mainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
mainLoop.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
mainLoop.ElitesParameter.ActualName = ElitesParameter.Name;
mainLoop.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name;
mainLoop.PlusSelectionParameter.ActualName = PlusSelectionParameter.Name;
mainLoop.AgeParameter.ActualName = "Age";
mainLoop.AgeGapParameter.ActualName = AgeGapParameter.Name;
mainLoop.AgeInheritanceParameter.ActualName = AgeInheritanceParameter.Name;
mainLoop.AgeLimitsParameter.ActualName = AgeLimitsParameter.Name;
mainLoop.MatingPoolRangeParameter.ActualName = MatingPoolRangeParameter.Name;
mainLoop.ReduceToPopulationSizeParameter.ActualName = ReduceToPopulationSizeParameter.Name;
mainLoop.TerminatorParameter.ActualName = TerminatorParameter.Name;
#endregion
#region Set selectors
foreach (var selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(s => !(s is IMultiObjectiveSelector)).OrderBy(s => Name))
SelectorParameter.ValidValues.Add(selector);
var defaultSelector = SelectorParameter.ValidValues.OfType<GeneralizedRankSelector>().FirstOrDefault();
if (defaultSelector != null) {
defaultSelector.PressureParameter.Value = new DoubleValue(4.0);
SelectorParameter.Value = defaultSelector;
}
#endregion
#region Create analyzers
qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
layerQualityAnalyzer = new BestAverageWorstQualityAnalyzer();
ageAnalyzer = new OldestAverageYoungestAgeAnalyzer();
layerAgeAnalyzer = new OldestAverageYoungestAgeAnalyzer();
ageDistributionAnalyzer = new AgeDistributionAnalyzer();
layerAgeDistributionAnalyzer = new AgeDistributionAnalyzer();
#endregion
#region Create terminators
generationsTerminator = new ComparisonTerminator<IntValue>("Generations", ComparisonType.Less, new IntValue(1000)) { Name = "Generations" };
evaluationsTerminator = new ComparisonTerminator<IntValue>("EvaluatedSolutions", ComparisonType.Less, new IntValue(int.MaxValue)) { Name = "Evaluations" };
qualityTerminator = new SingleObjectiveQualityTerminator() { Name = "Quality" };
executionTimeTerminator = new ExecutionTimeTerminator(this, new TimeSpanValue(TimeSpan.FromMinutes(5)));
#endregion
#region Parameterize
UpdateAnalyzers();
ParameterizeAnalyzers();
ParameterizeSelectors();
UpdateTerminators();
ParameterizeAgeLimits();
#endregion
Initialize();
}
private AlpsGeneticAlgorithmMainLoop(AlpsGeneticAlgorithmMainLoop original, Cloner cloner)
: base(original, cloner)
{
}
private AlpsGeneticAlgorithmMainLoop(AlpsGeneticAlgorithmMainLoop original, Cloner cloner)
: base(original, cloner) { }
public AlpsGeneticAlgorithm()
: base()
{
#region Add parameters
Parameters.Add(new ValueParameter <IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
Parameters.Add(new ValueParameter <BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
Parameters.Add(new FixedValueParameter <MultiAnalyzer>("Analyzer", "The operator used to analyze all individuals from all layers combined.", new MultiAnalyzer()));
Parameters.Add(new FixedValueParameter <MultiAnalyzer>("LayerAnalyzer", "The operator used to analyze each layer.", new MultiAnalyzer()));
Parameters.Add(new ValueParameter <IntValue>("NumberOfLayers", "The number of layers.", new IntValue(10)));
Parameters.Add(new ValueParameter <IntValue>("PopulationSize", "The size of the population of solutions in each layer.", new IntValue(100)));
Parameters.Add(new ConstrainedValueParameter <ISelector>("Selector", "The operator used to select solutions for reproduction."));
Parameters.Add(new ConstrainedValueParameter <ICrossover>("Crossover", "The operator used to cross solutions."));
Parameters.Add(new OptionalConstrainedValueParameter <IManipulator>("Mutator", "The operator used to mutate solutions."));
Parameters.Add(new ValueParameter <PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
Parameters.Add(new ValueParameter <IntValue>("Elites", "The numer of elite solutions which are kept in each generation.", new IntValue(1)));
Parameters.Add(new FixedValueParameter <BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)", new BoolValue(false))
{
Hidden = true
});
Parameters.Add(new ValueParameter <BoolValue>("PlusSelection", "Include the parents in the selection of the invividuals for the next generation.", new BoolValue(false)));
Parameters.Add(new ValueParameter <EnumValue <AgingScheme> >("AgingScheme", "The aging scheme for setting the age-limits for the layers.", new EnumValue <AgingScheme>(ALPS.AgingScheme.Polynomial)));
Parameters.Add(new ValueParameter <IntValue>("AgeGap", "The frequency of reseeding the lowest layer and scaling factor for the age-limits for the layers.", new IntValue(20)));
Parameters.Add(new ValueParameter <DoubleValue>("AgeInheritance", "A weight that determines the age of a child after crossover based on the older (1.0) and younger (0.0) parent.", new DoubleValue(1.0))
{
Hidden = true
});
Parameters.Add(new ValueParameter <IntArray>("AgeLimits", "The maximum age an individual is allowed to reach in a certain layer.", new IntArray(new int[0]))
{
Hidden = true
});
Parameters.Add(new ValueParameter <IntValue>("MatingPoolRange", "The range of layers used for creating a mating pool. (1 = current + previous layer)", new IntValue(1))
{
Hidden = true
});
Parameters.Add(new ValueParameter <BoolValue>("ReduceToPopulationSize", "Reduce the CurrentPopulationSize after elder migration to PopulationSize", new BoolValue(true))
{
Hidden = true
});
Parameters.Add(new ValueParameter <MultiTerminator>("Terminator", "The termination criteria that defines if the algorithm should continue or stop.", new MultiTerminator()));
#endregion
#region Create operators
var globalRandomCreator = new RandomCreator();
var layer0Creator = new SubScopesCreator()
{
Name = "Create Layer Zero"
};
var layer0Processor = new SubScopesProcessor();
var localRandomCreator = new LocalRandomCreator();
var layerSolutionsCreator = new SolutionsCreator();
var initializeAgeProcessor = new UniformSubScopesProcessor();
var initializeAge = new VariableCreator()
{
Name = "Initialize Age"
};
var initializeCurrentPopulationSize = new SubScopesCounter()
{
Name = "Initialize CurrentPopulationCounter"
};
var initializeLocalEvaluatedSolutions = new Assigner()
{
Name = "Initialize LayerEvaluatedSolutions"
};
var initializeGlobalEvaluatedSolutions = new DataReducer()
{
Name = "Initialize EvaluatedSolutions"
};
var resultsCollector = new ResultsCollector();
var mainLoop = new AlpsGeneticAlgorithmMainLoop();
#endregion
#region Create and parameterize operator graph
OperatorGraph.InitialOperator = globalRandomCreator;
globalRandomCreator.RandomParameter.ActualName = "GlobalRandom";
globalRandomCreator.SeedParameter.Value = null;
globalRandomCreator.SeedParameter.ActualName = SeedParameter.Name;
globalRandomCreator.SetSeedRandomlyParameter.Value = null;
globalRandomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
globalRandomCreator.Successor = layer0Creator;
layer0Creator.NumberOfSubScopesParameter.Value = new IntValue(1);
layer0Creator.Successor = layer0Processor;
layer0Processor.Operators.Add(localRandomCreator);
layer0Processor.Successor = initializeGlobalEvaluatedSolutions;
localRandomCreator.Successor = layerSolutionsCreator;
layerSolutionsCreator.NumberOfSolutionsParameter.ActualName = PopulationSizeParameter.Name;
layerSolutionsCreator.Successor = initializeAgeProcessor;
initializeAgeProcessor.Operator = initializeAge;
initializeAgeProcessor.Successor = initializeCurrentPopulationSize;
initializeCurrentPopulationSize.ValueParameter.ActualName = "CurrentPopulationSize";
initializeCurrentPopulationSize.Successor = initializeLocalEvaluatedSolutions;
initializeAge.CollectedValues.Add(new ValueParameter <DoubleValue>("Age", new DoubleValue(0)));
initializeAge.Successor = null;
initializeLocalEvaluatedSolutions.LeftSideParameter.ActualName = "LayerEvaluatedSolutions";
initializeLocalEvaluatedSolutions.RightSideParameter.ActualName = "CurrentPopulationSize";
initializeLocalEvaluatedSolutions.Successor = null;
initializeGlobalEvaluatedSolutions.ReductionOperation.Value.Value = ReductionOperations.Sum;
initializeGlobalEvaluatedSolutions.TargetOperation.Value.Value = ReductionOperations.Assign;
initializeGlobalEvaluatedSolutions.ParameterToReduce.ActualName = "LayerEvaluatedSolutions";
initializeGlobalEvaluatedSolutions.TargetParameter.ActualName = "EvaluatedSolutions";
initializeGlobalEvaluatedSolutions.Successor = resultsCollector;
resultsCollector.CollectedValues.Add(new LookupParameter <IntValue>("Evaluated Solutions", null, "EvaluatedSolutions"));
resultsCollector.Successor = mainLoop;
mainLoop.GlobalRandomParameter.ActualName = "GlobalRandom";
mainLoop.LocalRandomParameter.ActualName = localRandomCreator.LocalRandomParameter.Name;
mainLoop.EvaluatedSolutionsParameter.ActualName = "EvaluatedSolutions";
mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
mainLoop.LayerAnalyzerParameter.ActualName = LayerAnalyzerParameter.Name;
mainLoop.NumberOfLayersParameter.ActualName = NumberOfLayersParameter.Name;
mainLoop.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
mainLoop.CurrentPopulationSizeParameter.ActualName = "CurrentPopulationSize";
mainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
mainLoop.MutationProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
mainLoop.ElitesParameter.ActualName = ElitesParameter.Name;
mainLoop.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.Name;
mainLoop.PlusSelectionParameter.ActualName = PlusSelectionParameter.Name;
mainLoop.AgeParameter.ActualName = "Age";
mainLoop.AgeGapParameter.ActualName = AgeGapParameter.Name;
mainLoop.AgeInheritanceParameter.ActualName = AgeInheritanceParameter.Name;
mainLoop.AgeLimitsParameter.ActualName = AgeLimitsParameter.Name;
mainLoop.MatingPoolRangeParameter.ActualName = MatingPoolRangeParameter.Name;
mainLoop.ReduceToPopulationSizeParameter.ActualName = ReduceToPopulationSizeParameter.Name;
mainLoop.TerminatorParameter.ActualName = TerminatorParameter.Name;
#endregion
#region Set selectors
foreach (var selector in ApplicationManager.Manager.GetInstances <ISelector>().Where(s => !(s is IMultiObjectiveSelector)).OrderBy(s => Name))
{
SelectorParameter.ValidValues.Add(selector);
}
var defaultSelector = SelectorParameter.ValidValues.OfType <GeneralizedRankSelector>().FirstOrDefault();
if (defaultSelector != null)
{
defaultSelector.PressureParameter.Value = new DoubleValue(4.0);
SelectorParameter.Value = defaultSelector;
}
#endregion
#region Create analyzers
qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
layerQualityAnalyzer = new BestAverageWorstQualityAnalyzer();
ageAnalyzer = new OldestAverageYoungestAgeAnalyzer();
layerAgeAnalyzer = new OldestAverageYoungestAgeAnalyzer();
ageDistributionAnalyzer = new AgeDistributionAnalyzer();
layerAgeDistributionAnalyzer = new AgeDistributionAnalyzer();
#endregion
#region Create terminators
generationsTerminator = new ComparisonTerminator <IntValue>("Generations", ComparisonType.Less, new IntValue(1000))
{
Name = "Generations"
};
evaluationsTerminator = new ComparisonTerminator <IntValue>("EvaluatedSolutions", ComparisonType.Less, new IntValue(int.MaxValue))
{
Name = "Evaluations"
};
qualityTerminator = new SingleObjectiveQualityTerminator()
{
Name = "Quality"
};
executionTimeTerminator = new ExecutionTimeTerminator(this, new TimeSpanValue(TimeSpan.FromMinutes(5)));
#endregion
#region Parameterize
UpdateAnalyzers();
ParameterizeAnalyzers();
ParameterizeSelectors();
UpdateTerminators();
ParameterizeAgeLimits();
#endregion
Initialize();
}
