/// <summary>
/// Mutate an individual
/// </summary>
/// <param name="indiv">Individual to mutate</param>
private static void Mutate(Individual indiv)
{
// Loop through genes
for (int i = 0; i < indiv.Size(); i++)
{
if (rnd.NextDouble() <= mutationRate)
{
// Create random gene
int gene = (int)Math.Round((double)rnd.Next() % randomGeneRange);
indiv.SetGene(i, gene);
}
}
}
/// <summary>
/// Calculate individuals fitness by comparing it to our solution
/// </summary>
/// <param name="individual">Individual to check health from</param>
/// <returns></returns>
internal static int GetFitness(Individual individual)
{
int fitness = 0;
//Loop through our individuals genes and compare them to our candidates
for (int i = 0; i < individual.Size() && i < solution.Length; i++)
{
if (individual.GetGene(i) == solution[i])
{
fitness++;
}
}
return(fitness);
}
/// <summary>
/// Crossover individuals
/// </summary>
/// <param name="indiv1">Parent individual 1</param>
/// <param name="indiv2">Parent individual 2</param>
/// <returns>Child individual</returns>
private static Individual Crossover(Individual indiv1, Individual indiv2)
{
Individual newSol = new Individual();
// Loop through genes
for (int i = 0; i < indiv1.Size(); i++)
{
// Crossover
if (rnd.NextDouble() <= uniformRate)
{
newSol.SetGene(i, indiv1.GetGene(i));
}
else
{
newSol.SetGene(i, indiv2.GetGene(i));
}
}
return(newSol);
}