public void UpdatePopulation()
{
var min = CurrentPopulation.First(y => CalculateCF(y) == CurrentPopulation.Min(x => CalculateCF(x)));
if (CalculateCF(CurrentBlueChild) > CalculateCF(min))
{
CurrentPopulation[CurrentPopulation.IndexOf(min)] = CurrentBlueChild;
min = CurrentPopulation.First(y => CalculateCF(y) == CurrentPopulation.Min(x => CalculateCF(x)));
}
if (CalculateCF(CurrentYellowChild) > CalculateCF(min))
{
CurrentPopulation[CurrentPopulation.IndexOf(min)] = CurrentYellowChild;
}
}
private void SetBestIndividual()
{
var bestIndividual = CurrentPopulation.First();
for (int i = 1; i < MaxPopulationCount; i++)
{
var currentIndividual = CurrentPopulation[i];
if ((OptimizationTarget == OptimizationTarget.Maximum && currentIndividual.Result > bestIndividual.Result) ||
(OptimizationTarget == OptimizationTarget.Minimum && currentIndividual.Result < bestIndividual.Result))
{
bestIndividual = currentIndividual;
}
}
BestIndividual = bestIndividual;
}
public (List <int>, float) GetTheBestChromosome()
{
var best = CurrentPopulation.First(y => CalculateCF(y) == CurrentPopulation.Max(x => CalculateCF(x)));
List <int> cf_names = new List <int>();
for (int i = 0; i < best.Count; i++)
{
if (best[i] == 1)
{
cf_names.Add(i);
}
}
var cf = CalculateCF(best);
return(cf_names, cf);
}
public void GetCurrentFittestCoefficients()
{
Chromosome bestChromosome = CurrentPopulation.First();
foreach (Chromosome c in CurrentPopulation)
{
if (c.Fitness > bestChromosome.Fitness)
{
bestChromosome = c;
}
}
Tuple <double, double, double> cf = bestChromosome.GetCoefficients();
List <double> coefficients = new List <double>();
coefficients.Add(cf.Item1);
coefficients.Add(cf.Item2);
coefficients.Add(cf.Item3);
SaveData(coefficients, "FunctionCoefficients");
}