public override List <int> Fill(int size)
{
List <int> solution;
do
{
solution = Shuffler.GenereteShuffledOrder(size, rnd);
} while (!pcConstraint.IsFeasible(solution));
return(Shuffler.GenereteShuffledOrder(size, rnd));
}
protected override void AddToNewPopulation <Element>(List <Individual <Element> > population, List <Individual <Element> > newPopulation)
{
if (size == -1)
{
size = Convert.ToInt32(population.Count * proportion);
}
for (int i = 0; i < population.Count; ++i)
{
var indices = Shuffler.GenereteShuffledOrder(population.Count, new Random());
newPopulation.Add(new Individual <Element>(TournamentWinner(population, indices)));
}
}
private void RemoveItems(Individual <bool> individual)
{
Shuffler shuffler = new Shuffler(this.seed);
List <int> order;
if (this.seed == null)
{
order = shuffler.GenereteShuffledOrder(populationSize, new Random());
}
else
{
order = shuffler.GenereteShuffledOrder(populationSize, new Random(this.seed.Value));
}
foreach (var geneIndex in order)
{
individual.Genotype[geneIndex] = false;
if (isValid(individual))
{
break;
}
}
}
protected override bool RunIteration(long itertionNumber, DateTime startTime)
{
List <int> optOrder = shuffler.GenereteShuffledOrder(optimizedSolution.Count, rnd);
foreach (int order in optOrder)
{
optimizedSolution[order] = !optimizedSolution[order];
if (!CheckNewBest(optimizedSolution, Evaluation.dEvaluate(optimizedSolution)))
{
optimizedSolution[order] = !optimizedSolution[order];
}
}
return(CheckNewBest(optimizedSolution, Evaluation.dEvaluate(optimizedSolution)));
}