public virtual Genome Crossover(Genome first, Genome second, int generation)
{
CustomGenome firstR = (CustomGenome)first;
CustomGenome secondR = (CustomGenome)second;
double d = 0;
bool changed = false;
for (int g = 0; g < firstR.Length; g++)
{
d = GeneticAlgorithmUtility.RandomProvider.NextDouble();
if (d <= crossoverP)
{
firstR[g] = secondR[g];
changed = true;
}
d = GeneticAlgorithmUtility.RandomProvider.NextDouble();
if (d <= mutationP)
{
firstR[g] = GeneticAlgorithmUtility.RandomProvider.Next(0, firstR.MaxValue + 1);
changed = true;
}
}
if (changed)
{
firstR.Generation = generation;
}
return(first);
}
public Genome CreateGenome(GeneticAlgorithm parent)
{
CustomGenome newCustomGenome = new CustomGenome(parent, numberOfValues);
newCustomGenome.MaxValue = maxValue;
newCustomGenome.MinValue = minValue;
RandomizeGenome(newCustomGenome);
return(newCustomGenome);
}
public bool Execute()
{
ga.Crossover = new CustomCrossover();
ga.GenomeFactory = new CustomFactory(0, parameters.Questoes.Count - 1, parameters.QtdQuestoes);
switch (parameters.Seletor)
{
case SeletorGA.Roleta:
ga.Selector = new WeightedSelector(ga.Genomes);
break;
case SeletorGA.Sequencial:
ga.Selector = new SequentialSelector(ga.Genomes);
break;
case SeletorGA.Randomico:
ga.Selector = new RandomSelector(ga.Genomes);
break;
}
ga.Crossover.CrossoverProbability = parameters.ProbabilidadeReproducao / 100.0; //0.3;0.2;
ga.Crossover.MutationProbability = parameters.ProbabilidadeMutacao / 100.0; //0.015;
ga.Elitism = parameters.HabilitaElitismo;
ga.CustomObj = parameters.Questoes;
if (OnGANewGeneration != null)
{
ga.NewGeneration += new GeneticAlgorithmEventHandler(this.OnNewGeneration);
}
if (OnGANewBestFitness != null)
{
ga.NewBestFitness += new GeneticAlgorithmGenomeEventHandler(this.OnNewBestFitness);
}
ga.QryBestFitness += new GeneticAlgorithmCancelEventHandler(this.OnQryBestFitness);
ga.Evaluator = new CustomEvaluator(parameters);
ga.CreateGenomes(9);
ga.ExitConditions.Duration = TimeSpan.FromSeconds(parameters.MaxDuration);
ga.ExitConditions.Generations = parameters.MaxGenerations;
ga.ExitConditions.FitnessGoal = parameters.MinFitnessGoal;
bestGenome = (CustomGenome)ga.Execute();
stopTime = DateTime.Now;
exitCondiction = ga.ExitConditions.ExitCondiction;
bestGenome.UpdateStat(parameters);
return(true);
}
public void OnQryBestFitness(GeneticAlgorithm sender, GenomeCancelEventArgs args)
{
CustomGenome genomeCustom = (CustomGenome)args.Genome;
String key = genomeCustom.ToOrderedString();
AvaliacaoAnterior a = parameters.AvaliacoesAnteriores.Find(x => x.Key.Equals(key));
if (genomeCustom.QtdTotal() != parameters.QtdQuestoes || (a != null && (DateTime.Today - a.DtUtilizacao).Days <= parameters.QtdNaoRepetirAvaliacao))
{
args.Cancel = true;
}
}
public void OnNewBestFitness(GeneticAlgorithm sender, GenomeEventArgs args)
{
CustomGenome genome = (CustomGenome)args.Genome;
genome.UpdateStat(parameters);
//int hash = genome.GetHashCode();
if (OnGANewBestFitness != null)
{
CustomGenomeEventArgs newArgs = new CustomGenomeEventArgs();
newArgs.Genome = genome;
OnGANewBestFitness(this, newArgs);
}
}
public void RandomizeGenome(CustomGenome value)
{
List <int> list = new List <int>();
for (int i = 0; i < value.Length; i++)
{
while (true)
{
value[i] = GeneticAlgorithmUtility.RandomProvider.Next(minValue, maxValue + 1);
if (value[i] > maxValue)
{
value[i] = maxValue;
}
if (!list.Exists(x => x == value[i]))
{
list.Add(value[i]);
break;
}
}
}
}
public double Eval(Genome candidate)
{
CustomGenome genome = (CustomGenome)candidate;
genome.UpdateStat(parameters);
double ret = 0;
ret += Math.Abs(genome.QtdTotal() - genome.Length) * 200;
if (parameters.TempoPrevistoAvaliacao > 0)
{
ret += Math.Abs(genome.TempoTotal() - parameters.TempoPrevistoAvaliacao);
}
foreach (ConfigComplexidade rule in parameters.ComplexRules)
{
ret += Math.Abs(genome.ComplexTotal(rule.ComplexIni, rule.ComplexFim) - rule.Quantidade) * 100;
}
int tipoQuestao;
foreach (ConfigTipoQuestao rule in parameters.TipoQuestaoRules)
{
tipoQuestao = (int)rule.TipoQuestao;
ret += Math.Abs(genome.TipoTotal(tipoQuestao, tipoQuestao) - rule.Quantidade) * 100;
}
if (ret > (double)int.MaxValue)
{
ret = (double)int.MaxValue;
}
return((((double)int.MaxValue) - ret) / ((double)int.MaxValue) * 100.0);
}
