static void Main(string[] args)
{
// Crossover = 80%
// Mutation = 5%
// Population size = 100
// Generations = 2000
// Genome size = 2
var crossover = 0.8;
var mutationRate = 0.05;
var populationSize = 100;
var generations = 2000;
var genomeSize = 2;
//create objects
var random = new Random((int)DateTime.Now.Ticks);
var genesFactory = new GenesFactory(random);
var genomeFactory = new GenomeFactory(genesFactory, random, mutationRate);
var geneticAlghoritm = new GeneticAlghoritm(random, FitnessFunction, genomeFactory, crossover, populationSize, generations, genomeSize);
//execute alghoritm
geneticAlghoritm.Execute();
//show results
ShowResults(true, geneticAlghoritm);
ShowResults(false, geneticAlghoritm);
//
Console.ReadKey();
}
private static void ShowResults(bool theBest, GeneticAlghoritm geneticAlghoritm)
{
IList <double> values;
double fitness;
if (theBest)
{
geneticAlghoritm.GetBest(out values, out fitness);
Console.WriteLine("Best ({0}):", fitness);
}
else
{
geneticAlghoritm.GetWorst(out values, out fitness);
Console.WriteLine("\nWorst ({0}):", fitness);
}
foreach (var value in values)
{
System.Console.WriteLine("{0} ", value);
}
}
