public void NewGeneration()
{
int finalCount = Settings.PopulationSize + Settings.NumNewDNA;
List <Chromosome> newPopulation = new List <Chromosome>();
if (finalCount <= 0)
{
return;
}
if (Population.Count > 0)
{
CalculateAllFitness();
Population = Population.OrderBy(chrmsm => chrmsm.Fitness).ToList();
}
for (int i = 0; i < finalCount; i++)
{
// Keep only top individuals of the previous generation
if (i < Elitism && i < Settings.PopulationSize)
{
newPopulation.Add(Population[i]);
//Console.WriteLine("Generation: " + Generation);
//Console.WriteLine("/n");
//Console.WriteLine("genes: [{0}]", string.Join(",\t", Population[i].genes));
//Console.WriteLine(Population[i].fitness);
}
else if (i < Settings.PopulationSize)
{
Chromosome parent1 = Selection.PerformSelection(Population);
Chromosome parent2 = Selection.PerformSelection(Population);
Chromosome child = Crossover.PerformCrossover(parent1, parent2);
child = Mutation.PerformMutation(child);
newPopulation.Add(child);
}
else if (Settings.EnableCrossoverNewDNA)
{
newPopulation.Add(new Chromosome(shouldInitGenes: true));
}
}
Population = newPopulation;
Generation++;
}
public void Epoch()
{
CalcFitness();
var newpopulations = new List <IGenome>();
Population = Population.OrderBy(o => o.Fitness).ToList();
for (int j = 0; j < GASettings.BestSolutionToPick; j++)
{
Population[j].Fitness = Fitness.Calc(Population[j]);
Population[j].Score = 0;
newpopulations.Add(Population[j]);
}
int ran = Rand.Next(1, Population.Count);
while (newpopulations.Count < Population.Count)
{
// Selection
var nodemom = Selection.Select(Population);
var nodedad = Selection.Select(Population);
// CrossOver
var cross = Crossover.Calc(new CrossoverOperation(nodemom, nodedad));
//// Mutation
nodemom = Mutate.Calc(cross.Mom);
nodedad = Mutate.Calc(cross.Dad);
// Adaptation
nodemom = Adaptation.Calc(nodemom);
nodedad = Adaptation.Calc(nodedad);
nodemom.Fitness = Fitness.Calc(nodemom);
nodedad.Fitness = Fitness.Calc(nodedad);
// Add in new population
newpopulations.Add(nodemom);
newpopulations.Add(nodedad);
}
Population = null;
Population = newpopulations.ToList();
Generation++;
}