public Solver(SurvivalSelection survivalSelection, Breeder breeder, IMutator mutator, int maxStepsWithoutChanges)
{
_breeder = breeder;
_mutator = mutator;
_maxStepsWithoutChanges = maxStepsWithoutChanges;
_survivalSelection = survivalSelection;
}
private static void Run()
{
const int initialSpeciesNumber = 4;
const int survivalSelectionThreshold = 3;
const double mutationProbability = 0.3;
const double betterParentGeneSelectionProbability = 0.8;
Console.WriteLine("Dataset name:");
string datasetName = Console.ReadLine();
Console.WriteLine("Accuracy");
int maxStepsWithoutChanges = int.Parse(Console.ReadLine());
var settings = Settings.ParseDataSet(datasetName);
var fitnessFun = new SimpleFitnessFun(settings.MaxVolume, settings.Profits, settings.Weights);
var survivalSelection = new SurvivalSelection(survivalSelectionThreshold);
IGenesCrossover crossover = new SimpleGenesCrossover(fitnessFun, betterParentGeneSelectionProbability);
Breeder breeder = new Breeder(initialSpeciesNumber, new RandomBreedingSelector(), crossover);
var mutator = new RandomMutator(mutationProbability);
var solver = new Solver(survivalSelection, breeder, mutator, maxStepsWithoutChanges);
var initialSpecies = GenerateInitialSpecies(initialSpeciesNumber, settings.Profits.Length, fitnessFun);
Console.WriteLine("Начальные особи");
PrintSpecies(initialSpecies);
// while (true)
// {
// initialSpecies = solver.Step(initialSpecies);
// PrintSpecies(initialSpecies);
// Console.WriteLine();
//
// var key = Console.ReadKey();
// if (key.Key == ConsoleKey.X) break;
// }
Species best = solver.FindBest(initialSpecies);
Console.WriteLine();
Console.WriteLine($"Calcula best:{PrintSpecies(best)}. Steps: {solver.Steps}");
if (settings.DatasetBest != null)
{
Console.WriteLine($"Dataset best:{PrintSpecies(settings.DatasetBest)}");
}
}
