public static WarehouseResult Optimize(WarehouseParameters warehouseParameters, CancellationToken ct, Random random)
{
WarehouseManager warehouseManager = new WarehouseManager();
double[][] distancesMatrix = warehouseManager.CreateWarehouseDistancesMatrix(warehouseParameters.WarehousePath);
Distances.Create(distancesMatrix);
Orders orders = new Orders(warehouseParameters.OrdersPath, warehouseManager.WarehouseSize);
GeneticWarehouse geneticWarehouse = new GeneticWarehouse(warehouseParameters.WarehouseGeneticAlgorithmParameters,
warehouseManager.WarehouseSize,
(population) =>
{
double[] fitness = new double[population.Length];
warehouseParameters.FitnessGeneticAlgorithmParameters.WriteCsv = false;
Parallel.For(0, population.Length, i =>
{
var results = Fitness.CalculateAllOrdersFitness(orders, population[i],
warehouseParameters.FitnessGeneticAlgorithmParameters, random);
fitness[i] = results.Sum(x => x.Fitness);
});
return(fitness);
}, ct, random);
var z = geneticWarehouse.Run();
var result = Fitness.CalculateAllOrdersFitness(orders, z.BestChromosome, warehouseParameters.FitnessGeneticAlgorithmParameters, random);
z.FinalFitness = result.Sum(x => x.Fitness);
z.FinalOrderPaths = result.Select(x => x.Path).ToArray();
return(z);
}
public static double FindShortestPath(OptimizationParameters optimizationParameters, CancellationToken ct, int seed = 0)
{
seed = GetSeed(seed);
var random = new Random(seed);
var matrix = Files.ReadArray(optimizationParameters.DataPath);
Distances.Create(matrix);
return(PathFinding.ShortestPath.Find(PointsArrayGenerator.GeneratePointsToVisit(matrix.Length), optimizationParameters, ct, random));
}
public static void FindShortestPath(OptimizationParameters optimizationParameters,
DelegateFitness.CalcFitness calcFitness, int seed = 0)
{
seed = GetSeed(seed);
var random = new Random(seed);
var matrix = Files.ReadArray(optimizationParameters.DataPath);
Distances.Create(matrix);
PathFinding.ShortestPath.Find(PointsArrayGenerator.GeneratePointsToVisit(matrix.Length), optimizationParameters, calcFitness, CancellationToken.None, random);
}
public static TSPResult TSP(OptimizationParameters optimizationParameters, CancellationToken ct, int seed = 0)
{
seed = GetSeed(seed);
var random = new Random(seed);
var matrix = Files.ReadArray(optimizationParameters.DataPath);
Distances.Create(matrix);
var tsp = new GeneticTSP(PointsArrayGenerator.GeneratePointsToVisit(matrix.Length), optimizationParameters,
(population) =>
{
double[] fitness = new double[population.Length];
for (int i = 0; i < population.Length; i++)
{
fitness[i] = Fitness.CalculateFitness(population[i]);
}
return(fitness);
}, ct, random);
var result = tsp.Run();
result.Seed = seed;
return(result);
}
/// <summary>Returns an empty distance map.</summary>
protected Distance[,] GetEmptyDistances()
{
return(Distances.Create(this.Map));
}
