private void FitGeneration()
{
var fitnessList = new List <int>();
foreach (var robot in Population)
{
robot.CalculateFitness();
fitnessList.Add(robot.Fitness);
try
{
if (robot.Fitness > BestRun.Fitness)
{
BestRun = robot;
}
if (robot.Fitness < WorstRun.Fitness)
{
WorstRun = robot;
}
}
catch (Exception e)
{
BestRun = robot;
WorstRun = robot;
}
}
GeneticOperations.SetGenerationReproductionProbabilities(Population);
FitnessAverage = MathematicalOperations.Average(fitnessList, fitnessList.Count);
}
private void GenerationalMutation()
{
/*
* Mutates a bit from random individuals from the population.
* Number of mutations dictated in Constants.cs
*/
int individualIndex;
int bitIndex;
string completeChromosome;
int softwareOrHardwareMutate;
for (int times = 0; times < Constants.MutationProbability; times++)
{
individualIndex =
MathematicalOperations.RandomIntegerInRange(0, Constants.PopulationSize);
softwareOrHardwareMutate = MathematicalOperations.RandomIntegerInRange(0, 2);
if (softwareOrHardwareMutate == 1)
{
bitIndex =
MathematicalOperations.RandomIntegerInRange(0, Constants.CompleteChromosomeSize);
completeChromosome = Population[individualIndex].Hardware.CompleteChromosome;
completeChromosome =
GeneticOperations.Mutate(bitIndex, completeChromosome);
Population[individualIndex].Hardware.Mutate(completeChromosome);
}
else
{
bitIndex =
MathematicalOperations.RandomIntegerInRange(0, Constants.SoftwareChromosomeSize);
completeChromosome = Population[individualIndex].Software.CompleteChromosome;
GeneticOperations.Mutate(bitIndex, completeChromosome);
Population[individualIndex].Software.Mutate(completeChromosome);
}
}
}