static void Main(string[] args)
{
var selection = new EliteSelection();
var crossover = new OnePointCrossover(0);
var mutation = new UniformMutation(true);
var fitness = new Issue1Fitness();
var chromosome = new Issue1Chromosome();
var population = new Population(50, 50, chromosome);
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation);
ga.Termination = new GenerationNumberTermination(100);
Console.WriteLine("GA running...");
ga.Start();
Console.WriteLine("GA done in {0} generations.", ga.GenerationsNumber);
var bestChromosome = ga.BestChromosome as Issue1Chromosome;
Console.WriteLine("Best solution found is X:{0}, Y:{1} with {2} fitness.", bestChromosome.X, bestChromosome.Y, bestChromosome.Fitness);
Console.ReadKey();
}
static void Main(string[] args)
{
var selection = new EliteSelection();
var crossover = new OnePointCrossover(0);
var mutation = new UniformMutation(true);
var fitness = new Issue1Fitness();
var chromosome = new Issue1Chromosome();
var population = new Population(50, 50, chromosome);
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation);
ga.Termination = new GenerationNumberTermination(100);
Console.WriteLine("GA running...");
ga.Start();
Console.WriteLine("GA done in {0} generations.", ga.GenerationsNumber);
var bestChromosome = ga.BestChromosome as Issue1Chromosome;
Console.WriteLine("Best solution found is X:{0}, Y:{1} with {2} fitness.", bestChromosome.X, bestChromosome.Y, bestChromosome.Fitness);
Console.ReadKey();
}
