private static void LaunchGenetic()
{
int production_size = default;
string[] production_names = default;
float[] ecologies = default;
int[] costs = default;
int[] profits = default;
int a = default;
Console.WriteLine("Choose input data:\n" +
"1 - from console;\n" +
"2 - from file;\n");
int choose = int.Parse(Console.ReadLine());
if (choose == 1)
{
ReadStartInfoFromConsole(ref production_size, ref production_names, ref ecologies, ref costs, ref profits, ref a);
}
else if (choose == 2)
{
ReadStartInfoFromFile(ref production_size, ref production_names, ref ecologies, ref costs, ref profits, ref a);
}
Console.Write("Enter population size: ");
int population_size = Convert.ToInt32(Console.ReadLine());
GeneticAlgorithm algorithm = new GeneticAlgorithm(production_size, ecologies.ToList(), costs.ToList(), profits.ToList(), a, population_size);
int i_not = 0;
int i = 0;
string[] rez_names = default;
float rez_cf = default;
Dictionary <float, List <string> > best = new Dictionary <float, List <string> >();
best.Add(0, null);
while (i_not < 30)
{
i++;
//WriteInfoAboutProduction(production_names, algorithm);
algorithm.GetStartPopulation();
//WritePopulationMatrix(algorithm);
WriteBest(algorithm, production_names);
algorithm.GetParents();
//WriteParents(algorithm);
algorithm.CreateMask();
//WriteMask(algorithm);
algorithm.GetChildren();
//WriteChildren(algorithm);
var rez = algorithm.GetTheBestChromosome();
rez_names = ConvertNames(rez.Item1, production_names).ToArray();
rez_cf = rez.Item2;
algorithm.UpdatePopulation();
WriteIterationBestResultToFile(i, rez_cf);
if (rez.Item2 <= best.Keys.Max())
{
i_not++;
}
else
{
i_not = 0;
}
if (!best.ContainsKey(rez_cf))
{
best.Add(rez_cf, rez_names.ToList());
}
}
var item = best.First(x => x.Key == best.Keys.Max());
WriteResultToFile(item.Value.ToArray(), item.Key);
}