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);
}
