public GeneticPathFinding(int[] order, OptimizationParameters parameters, DelegateFitness.CalcFitness calcFitness, CancellationToken ct, Random random)
{
var populationInitialization = new StandardPathInitialization(random);
var population = populationInitialization.InitializePopulation(order, parameters.PopulationSize, 0);
_genetic = new BaseGenetic(parameters, population, calcFitness, 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 GeneticWarehouse(OptimizationParameters optimizationParameters, int warehouseSize,
DelegateFitness.CalcFitness calcFitness, CancellationToken ct, Random random)
{
_warehouseSize = warehouseSize;
int[] itemsToSort = new int[_warehouseSize];
for (int i = 1; i < _warehouseSize; i++)
{
itemsToSort[i - 1] = i;
}
var populationInitialization = new StandardPathInitialization(random);
var population = populationInitialization.InitializePopulation(itemsToSort, optimizationParameters.PopulationSize, 0);
_genetic = new BaseGenetic(optimizationParameters, population, calcFitness, ct, random);
wm = new WarehouseModule();
_genetic.LoadModule(wm);
}
public GeneticTSP(int[] order, OptimizationParameters parameters, DelegateFitness.CalcFitness calcFitness, CancellationToken ct, Random random)
{
_use2opt = parameters.Use2opt;
var populationInitialization =
GeneticFactory.CreatePopulationInitialization(parameters.PopulationInitializationMethod, random);
var population = populationInitialization.InitializePopulation(order, parameters.PopulationSize, parameters.StartingId);
_genetic = new BaseGenetic(parameters, population, calcFitness, ct, random);
if (parameters.StopAfterEpochsWithoutChange)
{
_genetic.LoadModule(new TerminationModule(parameters.StopAfterEpochCount));
}
if (parameters.EnableCataclysm)
{
_genetic.LoadModule(new CataclysmModule(populationInitialization, parameters.DeathPercentage, parameters.CataclysmEpoch));
}
_tspModule = new TSPModule();
_tspModule.LoadCrossoverOperator(_genetic.Crossover);
_genetic.LoadModule(_tspModule);
}
public static double Find(int[] order, OptimizationParameters optimizationParameters, DelegateFitness.CalcFitness calcFitness, CancellationToken ct, Random random)
{
IPathFinder algorithmPathFinding = optimizationParameters.OptimizationMethod switch
{
OptimizationMethod.Permutations => new Permutations(optimizationParameters),
OptimizationMethod.NearestNeighbor => new NearestNeighbor(optimizationParameters),
OptimizationMethod.GeneticAlgorithm => new GeneticPathFinding(order, optimizationParameters, calcFitness, ct, random),
_ => throw new ArgumentException("Incorrect optimization method in config file")
};
int[] objectOrder = algorithmPathFinding.FindShortestPath(order);
double pathLength = Fitness.CalculateFitness(objectOrder);
if (optimizationParameters.ResultToFile)
{
Log log = new Log(optimizationParameters);
log.SaveResult(objectOrder, pathLength);
}
return(pathLength);
}