private IslandGeneticAlgorithmMainLoop(IslandGeneticAlgorithmMainLoop original, Cloner cloner)
: base(original, cloner)
{
}
private IslandGeneticAlgorithmMainLoop(IslandGeneticAlgorithmMainLoop original, Cloner cloner)
: base(original, cloner) {
}
public IslandGeneticAlgorithm()
: base()
{
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 ValueParameter <IntValue>("NumberOfIslands", "The number of islands.", new IntValue(5)));
Parameters.Add(new ValueParameter <IntValue>("MigrationInterval", "The number of generations that should pass between migration phases.", new IntValue(20)));
Parameters.Add(new ValueParameter <PercentValue>("MigrationRate", "The proportion of individuals that should migrate between the islands.", new PercentValue(0.15)));
Parameters.Add(new ConstrainedValueParameter <IMigrator>("Migrator", "The migration strategy."));
Parameters.Add(new ConstrainedValueParameter <ISelector>("EmigrantsSelector", "Selects the individuals that will be migrated."));
Parameters.Add(new ConstrainedValueParameter <IReplacer>("ImmigrationReplacer", "Selects the population from the unification of the original population and the immigrants."));
Parameters.Add(new ValueParameter <IntValue>("PopulationSize", "The size of the population of solutions.", new IntValue(100)));
Parameters.Add(new ValueParameter <IntValue>("MaximumGenerations", "The maximum number of generations that should be processed.", new IntValue(1000)));
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 ValueParameter <PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
Parameters.Add(new OptionalConstrainedValueParameter <IManipulator>("Mutator", "The operator used to mutate solutions."));
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 <MultiAnalyzer>("Analyzer", "The operator used to analyze the islands.", new MultiAnalyzer()));
Parameters.Add(new ValueParameter <MultiAnalyzer>("IslandAnalyzer", "The operator used to analyze each island.", new MultiAnalyzer()));
RandomCreator randomCreator = new RandomCreator();
UniformSubScopesProcessor ussp0 = new UniformSubScopesProcessor();
LocalRandomCreator localRandomCreator = new LocalRandomCreator();
RandomCreator globalRandomResetter = 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 = ussp0;
ussp0.Operator = localRandomCreator;
ussp0.Successor = globalRandomResetter;
// BackwardsCompatibility3.3
// the global random is resetted to ensure the same algorithm results
#region Backwards compatible code, remove global random resetter with 3.4 and rewire the operator graph
globalRandomResetter.RandomParameter.ActualName = "GlobalRandom";
globalRandomResetter.SeedParameter.ActualName = SeedParameter.Name;
globalRandomResetter.SeedParameter.Value = null;
globalRandomResetter.SetSeedRandomlyParameter.Value = new BoolValue(false);
globalRandomResetter.Successor = ussp1;
#endregion
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 <IntValue>("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 <IntValue>("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.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.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 <ISelector>().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 <ISelector>().Where(x => !(x is IMultiObjectiveSelector)).OrderBy(x => x.Name))
{
EmigrantsSelectorParameter.ValidValues.Add(selector);
}
foreach (IReplacer replacer in ApplicationManager.Manager.GetInstances <IReplacer>().OrderBy(x => x.Name))
{
ImmigrationReplacerParameter.ValidValues.Add(replacer);
}
ParameterizeSelectors();
foreach (IMigrator migrator in ApplicationManager.Manager.GetInstances <IMigrator>().OrderBy(x => x.Name))
{
// BackwardsCompatibility3.3
// Set the migration direction to counterclockwise
var unidirectionalRing = migrator as UnidirectionalRingMigrator;
if (unidirectionalRing != null)
{
unidirectionalRing.ClockwiseMigrationParameter.Value = new BoolValue(false);
}
MigratorParameter.ValidValues.Add(migrator);
}
qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
islandQualityAnalyzer = new BestAverageWorstQualityAnalyzer();
ParameterizeAnalyzers();
UpdateAnalyzers();
Initialize();
}
public IslandGeneticAlgorithm()
: base() {
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 ValueParameter<IntValue>("NumberOfIslands", "The number of islands.", new IntValue(5)));
Parameters.Add(new ValueParameter<IntValue>("MigrationInterval", "The number of generations that should pass between migration phases.", new IntValue(20)));
Parameters.Add(new ValueParameter<PercentValue>("MigrationRate", "The proportion of individuals that should migrate between the islands.", new PercentValue(0.15)));
Parameters.Add(new ConstrainedValueParameter<IMigrator>("Migrator", "The migration strategy."));
Parameters.Add(new ConstrainedValueParameter<ISelector>("EmigrantsSelector", "Selects the individuals that will be migrated."));
Parameters.Add(new ConstrainedValueParameter<IReplacer>("ImmigrationReplacer", "Selects the population from the unification of the original population and the immigrants."));
Parameters.Add(new ValueParameter<IntValue>("PopulationSize", "The size of the population of solutions.", new IntValue(100)));
Parameters.Add(new ValueParameter<IntValue>("MaximumGenerations", "The maximum number of generations that should be processed.", new IntValue(1000)));
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 ValueParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution.", new PercentValue(0.05)));
Parameters.Add(new OptionalConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
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<MultiAnalyzer>("Analyzer", "The operator used to analyze the islands.", new MultiAnalyzer()));
Parameters.Add(new ValueParameter<MultiAnalyzer>("IslandAnalyzer", "The operator used to analyze each island.", new MultiAnalyzer()));
RandomCreator randomCreator = new RandomCreator();
UniformSubScopesProcessor ussp0 = new UniformSubScopesProcessor();
LocalRandomCreator localRandomCreator = new LocalRandomCreator();
RandomCreator globalRandomResetter = 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 = ussp0;
ussp0.Operator = localRandomCreator;
ussp0.Successor = globalRandomResetter;
// BackwardsCompatibility3.3
// the global random is resetted to ensure the same algorithm results
#region Backwards compatible code, remove global random resetter with 3.4 and rewire the operator graph
globalRandomResetter.RandomParameter.ActualName = "GlobalRandom";
globalRandomResetter.SeedParameter.ActualName = SeedParameter.Name;
globalRandomResetter.SeedParameter.Value = null;
globalRandomResetter.SetSeedRandomlyParameter.Value = new BoolValue(false);
globalRandomResetter.Successor = ussp1;
#endregion
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<IntValue>("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<IntValue>("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.ReevaluateElitesParameter.ActualName = ReevaluateElitesParameter.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<ISelector>().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<ISelector>().Where(x => !(x is IMultiObjectiveSelector)).OrderBy(x => x.Name))
EmigrantsSelectorParameter.ValidValues.Add(selector);
foreach (IReplacer replacer in ApplicationManager.Manager.GetInstances<IReplacer>().OrderBy(x => x.Name))
ImmigrationReplacerParameter.ValidValues.Add(replacer);
ParameterizeSelectors();
foreach (IMigrator migrator in ApplicationManager.Manager.GetInstances<IMigrator>().OrderBy(x => x.Name)) {
// BackwardsCompatibility3.3
// Set the migration direction to counterclockwise
var unidirectionalRing = migrator as UnidirectionalRingMigrator;
if (unidirectionalRing != null) unidirectionalRing.ClockwiseMigrationParameter.Value = new BoolValue(false);
MigratorParameter.ValidValues.Add(migrator);
}
qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
islandQualityAnalyzer = new BestAverageWorstQualityAnalyzer();
ParameterizeAnalyzers();
UpdateAnalyzers();
Initialize();
}