public async Task <double[]> SearchAsync(int size, IPairMatrix <double> inputRow)
{
var random = new Random();
var functions = new EvaluationFunctions(size, inputRow, random);
var maxPopulationCount = int.Parse(ConfigurationManager.AppSettings["MaxPopulationCount"]);
var elitismPercentage = int.Parse(ConfigurationManager.AppSettings["ElitismPercentage"]);
var mutationProbability = double.Parse(ConfigurationManager.AppSettings["MutationProbability"], System.Globalization.CultureInfo.InvariantCulture);
var crossoverProbability = double.Parse(ConfigurationManager.AppSettings["CrossoverProbability"], System.Globalization.CultureInfo.InvariantCulture);
var maxGenerationNumber = int.Parse(ConfigurationManager.AppSettings["MaxGenerationNumber"]);
var geneticAlgorithm = new GeneticAlgorithm <byte>(maxPopulationCount,
8 * size,
random,
functions.GetRandomGene,
functions.EvaluateFitness,
elitismPercentage,
mutationProbability,
crossoverProbability);
var searchingTask = Task.Factory.StartNew(() =>
{
for (var i = 0; i < maxGenerationNumber && geneticAlgorithm.BestFitness < 1; i++)
{
geneticAlgorithm.NewGeneration();
}
return(geneticAlgorithm.BestChromosome.ToDoubleArray());
}, CancellationToken.None, TaskCreationOptions.None, TaskScheduler.Default)
.ConfigureAwait(false);
return(await searchingTask);
}
public EvaluationFunctions(int size, IPairMatrix <double> inputRow, Random random)
{
_size = size;
_inputRow = inputRow;
_random = random;
}