public static GAParameters CreateRandom()
{
Random r = RandomNumberGeneratorProvider.Instance;
GAParameters g = new GAParameters();
g.ChromosomeRepresentationIndex = r.Next(0, ChromosomeRepresentation.Length);
g.PopulationSizeIndex = r.Next(0, PopulationSize.Length);
g.CrossoverRateIndex = r.Next(0, CrossoverRate.Length);
g.MutationRateIndex = r.Next(0, MutationRate.Length);
g.ElitismRateIndex = r.Next(0, ElitismRate.Length);
g.GenerationGapIndex = r.Next(0, GenerationGap.Length);
g.GAVariantIndex = r.Next(0, GAVariant.Length);
g.SelectionOperatorIndex = r.Next(0, SelectionOperator.Length);
g.CrossoverOperatorIndex = r.Next(0, CrossoverOperator.Length);
g.MutationOperatorIndex = r.Next(0, MutationOperator.Length);
g.TournamentSizeIndex = r.Next(0, TournamentSize.Length);
g.SelectivePressureIndex = r.Next(0, SelectivePressure.Length);
while (!g.IsValid())
{
g.ChromosomeRepresentationIndex = r.Next(0, ChromosomeRepresentation.Length);
g.PopulationSizeIndex = r.Next(0, PopulationSize.Length);
g.CrossoverRateIndex = r.Next(0, CrossoverRate.Length);
g.MutationRateIndex = r.Next(0, MutationRate.Length);
g.ElitismRateIndex = r.Next(0, ElitismRate.Length);
g.GenerationGapIndex = r.Next(0, GenerationGap.Length);
g.GAVariantIndex = r.Next(0, GAVariant.Length);
g.SelectionOperatorIndex = r.Next(0, SelectionOperator.Length);
g.CrossoverOperatorIndex = r.Next(0, CrossoverOperator.Length);
g.MutationOperatorIndex = r.Next(0, MutationOperator.Length);
g.TournamentSizeIndex = r.Next(0, TournamentSize.Length);
g.SelectivePressureIndex = r.Next(0, SelectivePressure.Length);
}
return(g);
}
public static Tuple <GAParameters, GAParameters> Cross(GAParameters g1, GAParameters g2)
{
var r = RandomNumberGeneratorProvider.Instance;
var prob = r.NextDouble();
if (prob < 0.05)
{
if (r.NextDouble() < 0.5)
{
g1.PopulationSizeIndex = r.Next(0, PopulationSize.Length);
}
else
{
g2.PopulationSizeIndex = r.Next(0, PopulationSize.Length);
}
}
else if (prob < 0.1)
{
if (r.NextDouble() < 0.5)
{
g1.CrossoverRateIndex = r.Next(0, CrossoverRate.Length);
}
else
{
g2.CrossoverRateIndex = r.Next(0, CrossoverRate.Length);
}
}
else if (prob < 0.15)
{
if (r.NextDouble() < 0.5)
{
g1.MutationRateIndex = r.Next(0, MutationRate.Length);
}
else
{
g2.MutationRateIndex = r.Next(0, MutationRate.Length);
}
}
else if (prob < 0.20)
{
if (r.NextDouble() < 0.5)
{
g1.ChromosomeRepresentationIndex = r.Next(0, ChromosomeRepresentation.Length);
}
else
{
g2.ChromosomeRepresentationIndex = r.Next(0, ChromosomeRepresentation.Length);
}
}
else if (prob < 0.25)
{
if (r.NextDouble() < 0.5)
{
g1.GAVariantIndex = r.Next(0, GAVariant.Length);
}
else
{
g2.GAVariantIndex = r.Next(0, GAVariant.Length);
}
}
else if (prob < 0.30)
{
if (r.NextDouble() < 0.5)
{
g1.CrossoverOperatorIndex = r.Next(0, CrossoverOperator.Length);
}
else
{
g2.CrossoverOperatorIndex = r.Next(0, CrossoverOperator.Length);
}
}
else if (prob < 0.35)
{
if (r.NextDouble() < 0.5)
{
g1.SelectionOperatorIndex = r.Next(0, SelectionOperator.Length);
}
else
{
g2.SelectionOperatorIndex = r.Next(0, SelectionOperator.Length);
}
}
else if (prob < 0.40)
{
if (r.NextDouble() < 0.5)
{
g1.MutationOperatorIndex = r.Next(0, MutationOperator.Length);
}
else
{
g2.MutationOperatorIndex = r.Next(0, MutationOperator.Length);
}
}
else if (prob < 0.45)
{
if (r.NextDouble() < 0.5)
{
g1.TournamentSizeIndex = r.Next(0, TournamentSize.Length);
}
else
{
g2.TournamentSizeIndex = r.Next(0, TournamentSize.Length);
}
}
else if (prob < 0.50)
{
if (r.NextDouble() < 0.5)
{
g1.ElitismRateIndex = r.Next(0, ElitismRate.Length);
}
else
{
g2.ElitismRateIndex = r.Next(0, ElitismRate.Length);
}
}
else if (prob < 0.50)
{
if (r.NextDouble() < 0.5)
{
g1.GenerationGapIndex = r.Next(0, GenerationGap.Length);
}
else
{
g2.GenerationGapIndex = r.Next(0, GenerationGap.Length);
}
}
else if (prob < 0.50)
{
if (r.NextDouble() < 0.5)
{
g1.SelectivePressureIndex = r.Next(0, SelectivePressure.Length);
}
else
{
g2.SelectivePressureIndex = r.Next(0, SelectivePressure.Length);
}
}
while (!g1.IsValid() && !g2.IsValid())
{
if (prob < 0.05)
{
if (r.NextDouble() < 0.5)
{
g1.PopulationSizeIndex = r.Next(0, PopulationSize.Length);
}
else
{
g2.PopulationSizeIndex = r.Next(0, PopulationSize.Length);
}
}
else if (prob < 0.1)
{
if (r.NextDouble() < 0.5)
{
g1.CrossoverRateIndex = r.Next(0, CrossoverRate.Length);
}
else
{
g2.CrossoverRateIndex = r.Next(0, CrossoverRate.Length);
}
}
else if (prob < 0.15)
{
if (r.NextDouble() < 0.5)
{
g1.MutationRateIndex = r.Next(0, MutationRate.Length);
}
else
{
g2.MutationRateIndex = r.Next(0, MutationRate.Length);
}
}
else if (prob < 0.20)
{
if (r.NextDouble() < 0.5)
{
g1.ChromosomeRepresentationIndex = r.Next(0, ChromosomeRepresentation.Length);
}
else
{
g2.ChromosomeRepresentationIndex = r.Next(0, ChromosomeRepresentation.Length);
}
}
else if (prob < 0.25)
{
if (r.NextDouble() < 0.5)
{
g1.GAVariantIndex = r.Next(0, GAVariant.Length);
}
else
{
g2.GAVariantIndex = r.Next(0, GAVariant.Length);
}
}
else if (prob < 0.30)
{
if (r.NextDouble() < 0.5)
{
g1.CrossoverOperatorIndex = r.Next(0, CrossoverOperator.Length);
}
else
{
g2.CrossoverOperatorIndex = r.Next(0, CrossoverOperator.Length);
}
}
else if (prob < 0.35)
{
if (r.NextDouble() < 0.5)
{
g1.SelectionOperatorIndex = r.Next(0, SelectionOperator.Length);
}
else
{
g2.SelectionOperatorIndex = r.Next(0, SelectionOperator.Length);
}
}
else if (prob < 0.40)
{
if (r.NextDouble() < 0.5)
{
g1.MutationOperatorIndex = r.Next(0, MutationOperator.Length);
}
else
{
g2.MutationOperatorIndex = r.Next(0, MutationOperator.Length);
}
}
else if (prob < 0.45)
{
if (r.NextDouble() < 0.5)
{
g1.TournamentSizeIndex = r.Next(0, TournamentSize.Length);
}
else
{
g2.TournamentSizeIndex = r.Next(0, TournamentSize.Length);
}
}
else if (prob < 0.50)
{
if (r.NextDouble() < 0.5)
{
g1.ElitismRateIndex = r.Next(0, ElitismRate.Length);
}
else
{
g2.ElitismRateIndex = r.Next(0, ElitismRate.Length);
}
}
else if (prob < 0.50)
{
if (r.NextDouble() < 0.5)
{
g1.GenerationGapIndex = r.Next(0, GenerationGap.Length);
}
else
{
g2.GenerationGapIndex = r.Next(0, GenerationGap.Length);
}
}
else if (prob < 0.50)
{
if (r.NextDouble() < 0.5)
{
g1.SelectivePressureIndex = r.Next(0, SelectivePressure.Length);
}
else
{
g2.SelectivePressureIndex = r.Next(0, SelectivePressure.Length);
}
}
}
return(new Tuple <GAParameters, GAParameters>(g1, g2));
}