private AlpsGeneticAlgorithm CreateAlpsGaTspSample() {
AlpsGeneticAlgorithm alpsGa = new AlpsGeneticAlgorithm();
#region Problem Configuration
var provider = new TSPLIBTSPInstanceProvider();
var instance = provider.GetDataDescriptors().Single(x => x.Name == "ch130");
TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
tspProblem.Load(provider.LoadData(instance));
tspProblem.UseDistanceMatrix.Value = true;
#endregion
#region Algorithm Configuration
alpsGa.Name = "ALPS Genetic Algorithm - TSP";
alpsGa.Description = "An age-layered population structure genetic algorithm which solves the \"ch130\" traveling salesman problem (imported from TSPLIB)";
alpsGa.Problem = tspProblem;
SamplesUtils.ConfigureAlpsGeneticAlgorithmParameters<GeneralizedRankSelector, MultiPermutationCrossover, InversionManipulator>(alpsGa,
numberOfLayers: 1000,
popSize: 100,
mutationRate: 0.05,
elites: 1,
plusSelection: true,
agingScheme: AgingScheme.Polynomial,
ageGap: 20,
ageInheritance: 1.0,
maxGens: 1000);
var checkedCrossovers = new[] { typeof(EdgeRecombinationCrossover), typeof(MaximalPreservativeCrossover), typeof(OrderCrossover2) };
var multiCrossover = (MultiPermutationCrossover)alpsGa.Crossover;
var crossovers = multiCrossover.Operators.Where(c => checkedCrossovers.Any(cc => cc.IsInstanceOfType(c))).ToList();
foreach (var c in multiCrossover.Operators)
multiCrossover.Operators.SetItemCheckedState(c, crossovers.Contains(c));
#endregion
return alpsGa;
}
private AlpsGeneticAlgorithm(AlpsGeneticAlgorithm original, Cloner cloner)
: base(original, cloner)
{
qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
layerQualityAnalyzer = cloner.Clone(original.layerQualityAnalyzer);
ageAnalyzer = cloner.Clone(original.ageAnalyzer);
layerAgeAnalyzer = cloner.Clone(original.layerAgeAnalyzer);
ageDistributionAnalyzer = cloner.Clone(original.ageDistributionAnalyzer);
layerAgeDistributionAnalyzer = cloner.Clone(original.layerAgeDistributionAnalyzer);
generationsTerminator = cloner.Clone(original.generationsTerminator);
evaluationsTerminator = cloner.Clone(original.evaluationsTerminator);
qualityTerminator = cloner.Clone(original.qualityTerminator);
executionTimeTerminator = cloner.Clone(original.executionTimeTerminator);
Initialize();
}
private AlpsGeneticAlgorithm CreateAlpsGaSymRegSample() {
AlpsGeneticAlgorithm alpsGa = new AlpsGeneticAlgorithm();
#region Problem Configuration
var provider = new VladislavlevaInstanceProvider();
var instance = provider.GetDataDescriptors().Single(x => x.Name.StartsWith("Vladislavleva-5 F5"));
var symbRegProblem = new SymbolicRegressionSingleObjectiveProblem();
symbRegProblem.Load(provider.LoadData(instance));
symbRegProblem.MaximumSymbolicExpressionTreeDepth.Value = 35;
symbRegProblem.MaximumSymbolicExpressionTreeLength.Value = 35;
var grammar = (TypeCoherentExpressionGrammar)symbRegProblem.SymbolicExpressionTreeGrammar;
grammar.Symbols.OfType<Exponential>().Single().Enabled = false;
grammar.Symbols.OfType<Logarithm>().Single().Enabled = false;
#endregion
#region Algorithm Configuration
alpsGa.Name = "ALPS Genetic Programming - Symbolic Regression";
alpsGa.Description = "An ALPS-GP to solve a symbolic regression problem (Vladislavleva-5 dataset)";
alpsGa.Problem = symbRegProblem;
SamplesUtils.ConfigureAlpsGeneticAlgorithmParameters<GeneralizedRankSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>(alpsGa,
numberOfLayers: 1000,
popSize: 100,
mutationRate: 0.25,
elites: 1,
plusSelection: false,
agingScheme: AgingScheme.Polynomial,
ageGap: 15,
ageInheritance: 1.0,
maxGens: 500);
#endregion
return alpsGa;
}
private AlpsGeneticAlgorithm(AlpsGeneticAlgorithm original, Cloner cloner)
: base(original, cloner) {
qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
layerQualityAnalyzer = cloner.Clone(original.layerQualityAnalyzer);
ageAnalyzer = cloner.Clone(original.ageAnalyzer);
layerAgeAnalyzer = cloner.Clone(original.layerAgeAnalyzer);
ageDistributionAnalyzer = cloner.Clone(original.ageDistributionAnalyzer);
layerAgeDistributionAnalyzer = cloner.Clone(original.layerAgeDistributionAnalyzer);
generationsTerminator = cloner.Clone(original.generationsTerminator);
evaluationsTerminator = cloner.Clone(original.evaluationsTerminator);
qualityTerminator = cloner.Clone(original.qualityTerminator);
executionTimeTerminator = cloner.Clone(original.executionTimeTerminator);
Initialize();
}
