private void InitializePopulation()
{
var minArray = HelperFunctions.GetArray(Constants.LowerBoundary, Constants.ChromosomeSize);
var maxArray = HelperFunctions.GetArray(Constants.UpperBoundary, Constants.ChromosomeSize);
for (var i = 0; i < PopulationSize; i++)
{
var chromosome = new DecimalArrayChromosome(Constants.ChromosomeSize);
chromosome.GenerateRandom(minArray, maxArray);
chromosome.Fitness = FitnessFunction.GetValue(chromosome);
Population.Add(chromosome);
}
}
public override DecimalArrayChromosome FindOptimum()
{
var best = new DecimalArrayChromosome(Constants.ChromosomeSize)
{
Fitness = decimal.MaxValue
};
for (var i = 0; i < IterationLimit; i++)
{
var selectedFromPopulation = Selection.Select(Population);
var childChromosome = Crossover.Cross(selectedFromPopulation[0], selectedFromPopulation[1]);
childChromosome = Mutation.Mutate(childChromosome);
childChromosome.Fitness = FitnessFunction.GetValue(childChromosome);
Population.Remove(selectedFromPopulation[2]);
Population.Add(childChromosome);
var populationBest = decimal.MaxValue;
var bestIndex = 0;
var index = 0;
foreach (var chromosome in Population)
{
if (chromosome.Fitness < populationBest)
{
populationBest = chromosome.Fitness;
bestIndex = index;
}
index++;
}
if (populationBest < best.Fitness)
{
best = Population.GetAtIndex(bestIndex);
Console.WriteLine("Iteration: " + i + ", Best fitness: " + populationBest + ", " + best);
}
if (populationBest < FitnessTerminator)
{
break;
}
}
return(best);
}
public override DecimalArrayChromosome FindOptimum()
{
var best = new DecimalArrayChromosome(Constants.ChromosomeSize)
{
Fitness = decimal.MaxValue
};
for (var i = 0; i < IterationLimit; i++)
{
var nextGeneration = new Population <DecimalArrayChromosome>(PopulationSize);
if (Elitism)
{
nextGeneration.Add(GetPopulationBest());
}
while (nextGeneration.Count() < PopulationSize)
{
var selectedFromPopulation = Selection.Select(Population);
var childChromosome =
Crossover.Cross(selectedFromPopulation.First(), selectedFromPopulation[1]);
childChromosome = Mutation.Mutate(childChromosome);
childChromosome.Fitness = FitnessFunction.GetValue(childChromosome);
nextGeneration.Add(childChromosome);
}
Population = nextGeneration;
var populationBest = GetPopulationBest();
if (populationBest.Fitness < best.Fitness)
{
best = populationBest;
Console.WriteLine("Iteration: " + i + ", Best fitness: " + populationBest.Fitness + ", " + best);
}
if (populationBest.Fitness < FitnessTerminator)
{
break;
}
}
return(best);
}