protected DifferentialEvolutionAlgorithm(OptimizationProblem optimizationProblem, int populationSize,
double mutationFactor, double crossoverProbability, IConvergenceCriterion convergenceCriterion,
Random randomNumberGenerator)
{
this.dimension = optimizationProblem.Dimension;
this.lowerBound = optimizationProblem.LowerBound;
this.upperBound = optimizationProblem.UpperBound;
this.designFactory = optimizationProblem.DesignFactory;
this.populationSize = populationSize;
this.mutationFactor = mutationFactor;
this.crossoverProbability = crossoverProbability;
this.convergenceCriterion = convergenceCriterion;
this.randomNumberGenerator = randomNumberGenerator;
}
public ParticleSwarmOptimizationAlgorithm(int dimension, double[] lowerBound, double[] upperBound, IDesignFactory designFactory,
int swarmSize, double omega, double phip, double phig, IConvergenceCriterion convergenceCriterion, IOptimizationLogger logger,
Random randomNumberGenerator)
{
this.dimension = dimension;
this.lowerBound = lowerBound;
this.upperBound = upperBound;
this.designFactory = designFactory;
this.swarmSize = swarmSize;
this.omega = omega;
this.phip = phip;
this.phig = phig;
this.convergenceCriterion = convergenceCriterion;
this.logger = logger;
this.randomNumberGenerator = randomNumberGenerator;
}
private GeneticAlgorithm(int continuousVariablesCount, int integerVariablesCount, IDesignFactory designFactory,
IOptimizationLogger logger, IConvergenceCriterion convergenceCriterion, IInitializer <double> initializer,
IEncoding <T> encoding, int populationSize, IPopulationStrategy <T> populationStrategy,
ISelectionStrategy <T> selection, IRecombinationStrategy <T> recombination, IMutationStrategy <T> mutation)
{
this.continuousVariablesCount = continuousVariablesCount;
this.integerVariablesCount = integerVariablesCount;
this.designFactory = designFactory;
this.logger = logger;
this.convergenceCriterion = convergenceCriterion;
this.initializer = initializer;
this.encoding = encoding;
this.populationSize = populationSize;
this.populationStrategy = populationStrategy;
this.selection = selection;
this.recombination = recombination;
this.mutation = mutation;
this.CurrentIteration = -1; // Initialization phase is not counted towards iterations
this.BestPosition = null;
this.BestFitness = double.MaxValue;
}
internal OrCriterion(IConvergenceCriterion criterion1, IConvergenceCriterion criterion2)
{
this.criterion1 = criterion1;
this.criterion2 = criterion2;
}
public static IConvergenceCriterion NOT(IConvergenceCriterion originalCriterion)
{
return(new NotCriterion(originalCriterion));
}
internal NotCriterion(IConvergenceCriterion originalCriterion)
{
this.originalCriterion = originalCriterion;
}
public static IConvergenceCriterion OR(IConvergenceCriterion criterion1, IConvergenceCriterion criterion2)
{
return(new OrCriterion(criterion1, criterion2));
}
public static IConvergenceCriterion AND(IConvergenceCriterion criterion1, IConvergenceCriterion criterion2)
{
return(new AndCriterion(criterion1, criterion2));
}
