private FunctionResult GetFunctionResultForChromosomes(BinaryChromosome chromosome1, BinaryChromosome chromosome2, Range range)
{
var x1Best = BinaryUtils.BinaryToDecimalRepresentation(chromosome1.BinaryRepresentation, range, NumberOfBitsInChromosome);
var x2Best = BinaryUtils.BinaryToDecimalRepresentation(chromosome2.BinaryRepresentation, range, NumberOfBitsInChromosome);
return(new FunctionResult(Function.Compute(x1Best, x2Best), x1Best, x2Best));
}
private double CalculateFunctionValue(List <BinaryChromosome> chromosomes, Range range, double bitsInChromosome)
{
if (chromosomes.Count != 2)
{
throw new ArgumentException("Incorrect chromosomes amount.");
}
return(function.Compute(
BinaryUtils.BinaryToDecimalRepresentation(chromosomes[0].BinaryRepresentation, range, bitsInChromosome),
BinaryUtils.BinaryToDecimalRepresentation(chromosomes[1].BinaryRepresentation, range, bitsInChromosome)));
}
private Dictionary <List <BinaryChromosome>, double> GetFunctionValueByChromosome(List <BinaryChromosome> chromosomes, Range range, double bitsInChromosome)
{
var valuesByChromosomes = new Dictionary <List <BinaryChromosome>, double>(chromosomes.Count);
for (int i = 0; i < chromosomes.Count; i += 2)
{
valuesByChromosomes.Add(new List <BinaryChromosome> {
chromosomes[i], chromosomes[i + 1]
},
function.Compute(
BinaryUtils.BinaryToDecimalRepresentation(chromosomes[i].BinaryRepresentation, range, bitsInChromosome),
BinaryUtils.BinaryToDecimalRepresentation(chromosomes[i + 1].BinaryRepresentation, range, bitsInChromosome)));
}
return(valuesByChromosomes);
}
public OptimizationResult Optimize(InputDataEntity inputDataEntity)
{
InputDataEntity = inputDataEntity;
NumberOfBitsInChromosome = PopulationService.CalculateNumberOfBitsInChromosome(inputDataEntity.DataRange, inputDataEntity.Accuracy);
BinaryChromosomes = PopulationService.GeneratePopulation(inputDataEntity.PopulationAmount, NumberOfBitsInChromosome);
// Method selection
ISelection selectionMethod = GetSelectionMethod(InputDataEntity.SelectionMethod, inputDataEntity);
ICross crossMethod = GetCrossMethod(InputDataEntity.CrossMethod);
IMutation mutationMethod = GetMutationMethod(InputDataEntity.MutationMethod);
var bestOfEachEpoch = new List <FunctionResult>();
List <BinaryChromosome> tmpBest = new List <BinaryChromosome>();
List <double> means = new List <double>();
List <double> standardDeviation = new List <double>();
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
for (int i = 0; i < InputDataEntity.EpochsAmount; i++)
{
List <BinaryChromosome> newPopulation = selectionMethod.ApplySelection(BinaryChromosomes, inputDataEntity.DataRange, NumberOfBitsInChromosome);
if (i != 0)
{
double newValue = GetFunctionResultForChromosomes(newPopulation[0], newPopulation[1], inputDataEntity.DataRange).FunctionValue;
double oldValue = GetFunctionResultForChromosomes(tmpBest[0], tmpBest[1], inputDataEntity.DataRange).FunctionValue;
if ((inputDataEntity.Maximize == false && newValue > oldValue) || (inputDataEntity.Maximize == true && newValue < oldValue))
{
newPopulation.InsertRange(0, tmpBest);
}
else
{
newPopulation.InsertRange(newPopulation.Count - 1, tmpBest);
}
}
bestOfEachEpoch.Add(GetFunctionResultForChromosomes(newPopulation[0], newPopulation[1], inputDataEntity.DataRange));
tmpBest.Clear();
for (int j = 0; j < inputDataEntity.EliteStrategyAmount * 2; j++)
{
tmpBest.Add(newPopulation[j]);
}
means.Add(CalculateMean(newPopulation, inputDataEntity.DataRange));
standardDeviation.Add(CalculateDeviation(newPopulation, inputDataEntity.DataRange, means[i]));
List <BinaryChromosome> crossedPopulation = crossMethod.Cross(newPopulation, InputDataEntity.CrossProbability);
List <BinaryChromosome> mutatedPopulation = mutationMethod.Mutate(crossedPopulation, InputDataEntity.MutationProbability);
List <BinaryChromosome> populationAfterInversion = Inversion.PerformInversion(mutatedPopulation, InputDataEntity.InversionProbability);
BinaryChromosomes = populationAfterInversion;
if (BinaryChromosomes.Count <= 2)
{
break;
}
}
var bestIndividuals = selectionMethod.ApplySelection(BinaryChromosomes, inputDataEntity.DataRange, NumberOfBitsInChromosome).Take(2).ToArray();
double x1 = BinaryUtils.BinaryToDecimalRepresentation(bestIndividuals[0].BinaryRepresentation, inputDataEntity.DataRange, NumberOfBitsInChromosome);
double x2 = BinaryUtils.BinaryToDecimalRepresentation(bestIndividuals[1].BinaryRepresentation, inputDataEntity.DataRange, NumberOfBitsInChromosome);
double extremum = Function.Compute(x1, x2);
stopwatch.Stop();
return(new OptimizationResult
{
ExtremeValue = extremum,
X1 = x1,
X2 = x2,
BestFromPreviousEpochs = bestOfEachEpoch,
MeanFromPreviousEpochs = means,
StandardDeviation = standardDeviation,
TimeElapsed = stopwatch.ElapsedMilliseconds
});
}
