public IList <IChromosome <T> > Solve <T>(IList <IChromosome <T> > population)
{
if (population.Count == 0)
{
return(population);
}
var currentPopulation = population.Clone();
do
{
var newPopulation = new List <IChromosome <T> >();
while (newPopulation.Count < _parameters.PopulationSize)
{
var selected = SelectionMethod.Selection(currentPopulation);
var chromozome = CrossoverAlgorithm.RunCrossover(selected.Item1, selected.Item2, _parameters.CrossOverProbability);
chromozome = MutationAlgorithm.RunMutation(chromozome, _parameters.MutationProbability);
chromozome.FintnessValue = EvaluationMethod.Evaluate(chromozome);
newPopulation.Add(chromozome);
}
currentPopulation = newPopulation;
} while (!Convirged());
return(currentPopulation);
}
public Genome CreateOffspring(float ignoreRatio)
{
Subject parent1 = GetProportionalRandomParent(ignoreRatio);
Subject parent2 = GetProportionalRandomParent(ignoreRatio);
return(CrossoverAlgorithm.Crossover(parent1.Genome, parent2.Genome));
}
internal static Genome[] Crossover(
Genome parent1, Genome parent2,
CrossoverAlgorithm algorithm, bool gaussian)
{
switch (algorithm)
{
case CrossoverAlgorithm.SinglePoint:
return(CrossoverNPoint(parent1, parent2, gaussian, 1));
case CrossoverAlgorithm.TwoPoint:
return(CrossoverNPoint(parent1, parent2, gaussian, 2));
case CrossoverAlgorithm.ThreePoint:
return(CrossoverNPoint(parent1, parent2, gaussian, 3));
case CrossoverAlgorithm.Linear:
return(CrossoverLinear(parent1, parent2, gaussian));
case CrossoverAlgorithm.Blend:
return(CrossoverBlend(parent1, parent2, gaussian));
case CrossoverAlgorithm.RandomSwap:
return(CrossoverRandomSwap(parent1, parent2, gaussian));
case CrossoverAlgorithm.SBC:
default:
throw new ArgumentOutOfRangeException(nameof(algorithm), algorithm, null);
}
}
// Use this for initialization
void Start()
{
fc = GetComponent <FitnessCalculation> ();
crossover = GetComponent <CrossoverAlgorithm> ();
spawnLocations = new Vector3[popSize];
for (int i = 0; i < spawnLocations.Length; i++)
{
spawnLocations[i].x = Random.Range(-20f, 20f);
spawnLocations[i].y = Random.Range(-20f, 20f);
spawnLocations[i].z = 0;
}
// Debug.Log ("Population Script: Loaded");
Initialize(popSize, true);
}
public static void SetCrossover(CrossoverAlgorithm newCrossoverAlgorithm)
{
crossoverAlgorithm = newCrossoverAlgorithm;
}
private void CreateChild_OnClick()
{
Parent1Genome.AdjustedFitness = 2;
Parent2Genome.AdjustedFitness = 1;
ChildGV.VisualizeGenome(CrossoverAlgorithm.Crossover(Parent1Genome, Parent2Genome), false, true);
}
