public static Population EvolvePopulation(Population p)
{
Population newPopulation = new Population(p.Size(), false);
if (elitism)
{
newPopulation.SaveIndividual(0, p.GetFittest());
}
int elitismOffset;
if (elitism)
{
elitismOffset = 1;
}
else
{
elitismOffset = 0;
}
for (int i = elitismOffset; i < p.Size(); i++)
{
Individual indiv1 = TournamentSelection(p);
Individual indiv2 = TournamentSelection(p);
Individual newIndiv = Crossover(indiv1, indiv2);
newPopulation.SaveIndividual(i, newIndiv);
}
for (int i = elitismOffset; i < newPopulation.Size(); i++)
{
Mutate(newPopulation.GetIndividual(i));
}
return(newPopulation);
}
void RunGA()
{
FitnessCalculator.SetSolution("1111000000000001111000000000000000000000000000000000000000001111");
Population pop = new Population(6, true);
int epoch = 0;
while (pop.GetFittest().GetFitness() < FitnessCalculator.GetMaxFitness())
{
epoch++;
pop = Algorithm.EvolvePopulation(pop);
System.Console.WriteLine("Generation: " + epoch + " Fittest: " + pop.GetFittest().GetFitness());
System.Console.WriteLine(pop.GetFittest());
}
System.Console.WriteLine("Solution found");
System.Console.WriteLine("Generation: " + epoch);
System.Console.WriteLine("Genes:");
System.Console.WriteLine(pop.GetFittest());
}
/// <summary>
///
/// </summary>
/// <param name="p"></param>
/// <returns></returns>
private static Individual TournamentSelection(Population p)
{
Population tournament = new Population(tournamentSize, false);
Random rndgen = new Random();
for (int i = 0; i < tournamentSize; i++)
{
int randomID = (int)(rndgen.NextDouble() * p.Size());
tournament.SaveIndividual(i, p.GetIndividual(randomID));
}
Individual fittest = tournament.GetFittest();
return(fittest);
}
void Start()
{
//We need to set a candidate solution (feel free ti change this if you want to)
FitnessCalc.SetSolution(new byte[] { 1, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 1, 1, 1 });
//Create initial population, a population of 50 should be fine
Population myPop = new Population(50, true);
int generationCount = 0;
int bestFittness = 0;
while (myPop.GetFittest().GetFitness() < FitnessCalc.GetMaxFitness())
{
generationCount++;
if (myPop.GetFittest().GetFitness() > bestFittness)
{
Console.WriteLine("Generation: " + generationCount + " Fittest: " + myPop.GetFittest().GetFitness());
Console.WriteLine("Fittest: ");
foreach (byte b in myPop.GetFittest().GetGenes())
{
Console.Write(b);
}
Console.WriteLine("");
bestFittness = myPop.GetFittest().GetFitness();
}
myPop = Algorithm.EvolvePopulation(myPop);
}
Console.WriteLine("Solution found!");
Console.WriteLine("Generation: " + generationCount);
Console.WriteLine("Genes: ");
Console.WriteLine(myPop.GetFittest());
}