private void ShowBestInGeneration(List <Specimen> generation, PopulationSetting population)
{
StringBuilder sb = new StringBuilder();
sb.Append("Лучший в поколении №" + geneticAlgorithm.GenerationNum + ": " + generation[0] + "\n");
sb.Append("Значение функции: " + population.FittingFunction(generation[0]));
Console.WriteLine(sb);
}
private void ShowBestOfAllTime(List <List <Specimen> > generations, PopulationSetting population)
{
Specimen best = null;
Specimen worst = null;
int bestGeneration = 0;
int worstGeneration = 0;
var bestList = new List <Specimen>();
var tempList = new List <Specimen>();
StringBuilder sb = new StringBuilder();
for (int i = 0; i < generations.Count; i++)
{
tempList = generations[i];
tempList.Sort((a, b) => population.FittingFunction(a).CompareTo(population.FittingFunction(b)));
bestList.Add(tempList[0]);
}
for (int i = 0; i < bestList.Count; i++)
{
best = bestList[0];
worst = bestList[1];
if (population.FittingFunction(bestList[i]) < population.FittingFunction(best))
{
best = bestList[i];
bestGeneration = i;
}
if (population.FittingFunction(bestList[i]) > population.FittingFunction(worst))
{
worst = bestList[i];
worstGeneration = i;
}
}
sb.Append("\n\nВывод\n");
sb.Append("Лучший из всех в поколении №" + (bestGeneration + 1) + ": " + best + "\n Значение функции: " + population.FittingFunction(best) + "\n\n");
sb.Append("Худший из всех в поколении №" + (worstGeneration + 1) + ": " + worst + "\n Значение функции: " + population.FittingFunction(worst) + "\n");
Console.WriteLine(sb);
}
public void NewGeneration()
{
if (CurrentGeneration.Count <= 0)
{
return;
}
newGeneration = new List <Specimen>();
oldGeneration = new List <Specimen>();
List <Specimen> bestOfTheBest = new List <Specimen>();
allGenerations.Add(CurrentGeneration);
for (int i = 0; i < CurrentGeneration.Count; i++)
{
for (int j = 0; j < CurrentGeneration.Count; j++)
{
if (i == j)
{
j++;
}
if (j == CurrentGeneration.Count)
{
break;
}
var firstParent = CurrentGeneration[i];
var secondParent = CurrentGeneration[j];
var child = firstParent.CrossoverWith(secondParent);
if (RandomForGA.Generator.NextDouble() < Parameters.MutationRate)
{
child.Mutate(Parameters.MutationAmplitude);
}
newGeneration.Add(child);
}
}
for (int i = 0; i < CurrentGeneration.Count; i++)
{
oldGeneration.Add(CurrentGeneration[i]);
}
CurrentGeneration.Clear();
for (int i = 0; i < oldGeneration.Count; i++)
{
CurrentGeneration.Add(oldGeneration[i]);
}
for (int i = 0; i < newGeneration.Count; i++)
{
CurrentGeneration.Add(newGeneration[i]);
}
CalculateFitness();
CurrentGeneration.Sort((a, b) => population.FittingFunction(a).CompareTo(population.FittingFunction(b)));
for (int i = 0; i < Parameters.PopulationSize; i++)
{
bestOfTheBest.Add(CurrentGeneration[i]);
}
CurrentGeneration = bestOfTheBest;
GenerationNum++;
}