public GeneticAlgorithmTest()
{
bool found = false;
int target = 1547881;
generation = new Chromosome[PopulationSize];
for (int i = 0; i < PopulationSize; i++)
{
generation[i] = new Chromosome();
generation[i].ComputeFitness(target);
}
while (!found)
{
double totalFitness = 0.0f;
foreach (var chromosome in generation)
{
totalFitness += chromosome.Fitness;
if (chromosome.Fitness == 999)
{
Console.WriteLine("------------------");
Console.WriteLine("Result is {0}={1}", chromosome.Decode(chromosome.EncodedChromosome), target);
Console.WriteLine("------------------");
Console.WriteLine("Press any key to continue...");
Console.ReadKey();
found = true;
break;
}
}
Console.WriteLine("Total fitness {0}", totalFitness);
Chromosome[] newPopulation = new Chromosome[PopulationSize];
int newSize = 0;
do
{
Chromosome parent1 = this.Roulette(totalFitness, this.generation);
Chromosome parent2 = this.Roulette(totalFitness, this.generation);
Chromosome child = parent1.Mutate(parent2);
child.ComputeFitness(target);
newPopulation[newSize++] = child;
} while (newSize < PopulationSize);
generation = newPopulation;
}
}
public Chromosome Mutate(Chromosome chromosome)
{
int chromosomeLength = this.EncodedChromosome.Length;
if (chromosome.EncodedChromosome.Length != chromosomeLength)
{
throw new ApplicationException("Chromosomes can't make babies");
}
string childChromosome = this.EncodedChromosome;
int crossoverBeginIndex = Random.Next(chromosomeLength);
var array = childChromosome.ToCharArray();
if (this.GetRandomNumber() < CrossoverRate)
{
for (int i = crossoverBeginIndex; i < chromosomeLength; ++i)
{
array[i] = chromosome.EncodedChromosome[i];
}
}
for (int i = crossoverBeginIndex; i < chromosomeLength; ++i)
{
if (this.GetRandomNumber() < MutationRate)
{
array[i] = array[i] == '0' ? '1' : '0';
}
}
var child = new Chromosome(new string(array));
return child;
}