public void Setup()
{
tournamentSel = new TournamentSelection();
crossOver = new CrossOverSpawnFunction();
ga = new GeneticAlgorithm(tournamentSel, crossOver);
}
/// <summary>
/// Initializes a new instance of a GeneticAlgorithm.
/// </summary>
/// <param name="mutationFunction">Mutation function to apply during evolution.</param>
/// <param name="crossoverFunction">Crossover Function used during evolution.</param>
/// <param name="selectionFunction">Selection Function used in chromosome selection.</param>
/// <param name="pairingFunction">Pairing function used to select pairs of chromosomes during crossover.</param>
public GeneticAlgorithm(IMutationFunction mutationFunction, ICrossoverFunction crossoverFunction,
ISelectionFunction selectionFunction, IPairingFunction pairingFunction)
{
this.Mutation = mutationFunction;
this.Crossover = crossoverFunction;
this.Selection = selectionFunction;
this.Pairing = pairingFunction;
}
public Population(IFitnessFunction fitnessFunction, List <IGenome> population)
{
//Log.Create("../../Logs/");
this.selection = DefaultParameter.selection;
this.crossover = DefaultParameter.crossover;
this.mutation = DefaultParameter.mutation;
this.population = population;
}
public Population(IFitnessFunction fitnessFunction, List<IGenome> population)
{
//Log.Create("../../Logs/");
this.selection = DefaultParameter.selection;
this.crossover = DefaultParameter.crossover;
this.mutation = DefaultParameter.mutation;
this.population = population;
}
public Population(IFitnessFunction fitnessFunction, int size)
{
// Log.Create("../../Logs/");
this.selection = DefaultParameter.selection;
this.crossover = DefaultParameter.crossover;
this.mutation = DefaultParameter.mutation;
this.generation = 1;
this.avarageFitness = 0;
this.fitnessFunction = fitnessFunction;
IInitialPopulationMethod initial = DefaultParameter.initialPopulation;
this.population = initial.Generate(DefaultParameter.genomeSize, fitnessFunction);
}
public Population(IFitnessFunction fitnessFunction, int size)
{
// Log.Create("../../Logs/");
this.selection = DefaultParameter.selection;
this.crossover = DefaultParameter.crossover;
this.mutation = DefaultParameter.mutation;
this.generation = 1;
this.avarageFitness = 0;
this.fitnessFunction = fitnessFunction;
IInitialPopulationMethod initial = DefaultParameter.initialPopulation;
this.population = initial.Generate(DefaultParameter.genomeSize, fitnessFunction);
}
public GeneticAlgorithm(ISelectionFunction selectionFunction, ISpawnIndividualFunction spawnFunction)
{
this.selectionFunction = selectionFunction;
this.spawnFunction = spawnFunction;
rand = new Random();
}
