private Population runAlgorithem(Population population, int amountOfGenerations)
{
const double crossoverProbability = 0.65;
const double mutationProbability = 0.08;
const int elitismPercentage = 5;
//create the genetic operators
var elite = new Elite(elitismPercentage);
var crossover = new Crossover(crossoverProbability, true)
{
CrossoverType = CrossoverType.SinglePoint
};
var mutation = new SwapPlayerMutation(mutationProbability, this.players, this.groupedPlayers);
//create the GA itself
var ga = new GeneticAlgorithm(population, evaluateFitness);
//subscribe to the GAs Generation Complete event
ga.OnGenerationComplete += this.getOnGenerationComplete();
//add the operators to the ga process pipeline
ga.Operators.Add(elite);
ga.Operators.Add(crossover);
ga.Operators.Add(mutation);
//run the GA
ga.Run(GetTerminateFunction(amountOfGenerations));
this.performanceMonitor.SavePerformanceLog("./results");
return(ga.Population);
}
public IEnumerable <Player> FindSolution()
{
const double crossoverProbability = 0.65;
const double mutationProbability = 0.08;
const int elitismPercentage = 5;
//create the population
var population = new Population();
Random rnd = new Random();
//create the chromosomes
for (var p = 0; p < 100; p++)
{
var chromosome = new Chromosome();
for (var g = 0; g < 11; g++)
{
chromosome.Genes.Add(new Gene(rnd.Next(0, this.players.Count())));
}
chromosome.Genes.ShuffleFast();
population.Solutions.Add(chromosome);
}
//create the genetic operators
var elite = new Elite(elitismPercentage);
var crossover = new Crossover(crossoverProbability, true)
{
CrossoverType = CrossoverType.SinglePoint
};
var mutation = new SwapPlayerMutation(0.02, this.players);
//create the GA itself
var ga = new GeneticAlgorithm(population, evaluateFitness);
//subscribe to the GAs Generation Complete event
ga.OnGenerationComplete += ga_OnGenerationComplete;
//add the operators to the ga process pipeline
ga.Operators.Add(elite);
ga.Operators.Add(crossover);
ga.Operators.Add(mutation);
//run the GA
ga.Run(TerminateAlgorithm);
var topSolution = this.getPlayersFromChromosome(ga.Population.GetTop(1).First());
this.calculator.PrintFitnessDetails(topSolution);
return(topSolution.OrderBy(p => p.type));
}
