private ISolver EvolutionaryMakerParametrized(int population, int parentCandidates, double mutationRate, double crossoverRate, double mutationProbability, double crossoverProbability, string desc)
{
Evolutionary solver = new Evolutionary()
{
ParallelAllowed = true,
ParallelOptions = new ParallelOptions()
{
MaxDegreeOfParallelism = 15
},
ScoringFunction = new Scorer(),
DiagnosticMessages = true,
PropagateRandomSeed = true,
TimeLimit = new TimeSpan(0, 15, 0),
PopulationCount = population,
CandidatesForParent = parentCandidates,
MutationRate = mutationRate,
CrossoverRate = crossoverRate,
NumberOfMutationsToBreakCount = mutationProbability,
ProportionOfBreaksCrossed = crossoverProbability,
GenerationImproverGenerator = LocalSearchForEvolutionaryImprovement,
Description = desc,
};
return(solver);
}
private ISolver EvolutionaryBest()
{
Evolutionary solver = new Evolutionary()
{
ParallelAllowed = true,
ParallelOptions = new ParallelOptions()
{
MaxDegreeOfParallelism = 15
},
ScoringFunction = new Scorer(),
DiagnosticMessages = true,
PropagateRandomSeed = true,
BreakAfterLoopsWithoutImprovement = 2,
TimeLimit = new TimeSpan(1, 30, 0),
PopulationCount = 38,
CandidatesForParent = 4,
MutationRate = 0.394736842105263,
CrossoverRate = 0.657894736842105,
NumberOfMutationsToBreakCount = 0.000790520968624,
ProportionOfBreaksCrossed = 0.083086983070447,
GenerationImproverGenerator = LocalSearchForEvolutionaryImprovement,
Description = "evolutionary_best_2",
};
return(solver);
}
private static ISolver EvolutionarySolver()
{
Evolutionary solver = new Evolutionary()
{
Description = "evolutionary2",
ScoringFunction = new Scorer(),
DiagnosticMessages = true,
PropagateRandomSeed = true,
ParallelAllowed = true,
Seed = 10,
GenerationImproverGenerator = LocalSearchForEvolutionaryImprovement,
GenerationCreatorGenerator = LocalSearchEvolutionaryInitial,
};
return(solver);
}
private static void runEvolutionary(string fileName, Method method)
{
FileReader fileReader = new FileReader(new NetworkModel());
NetworkModel network = fileReader.ReadFile(fileName);
int maxMutationNumber, maxNumberOfContinuousNonBetterSolutions, maxTime, population, maxNumberOfGenerations, seed;
float pCross, pMutate, percentOfBestChromosomes;
Console.WriteLine("Podaj maksymaln¹ liczbê mutacji");
Int32.TryParse(Console.ReadLine(), out maxMutationNumber);
Console.WriteLine("Podaj maksymaln¹ liczbê prób szukania lepszego rozwi¹zania:");
Int32.TryParse(Console.ReadLine(), out maxNumberOfContinuousNonBetterSolutions);
Console.WriteLine("Podaj maksymalny czas[s]");
Int32.TryParse(Console.ReadLine(), out maxTime);
Console.WriteLine("Podaj populacjê:");
Int32.TryParse(Console.ReadLine(), out population);
Console.WriteLine("Podaj liczbê generacji:");
Int32.TryParse(Console.ReadLine(), out maxNumberOfGenerations);
Console.WriteLine("Podaj pstwo krzy¿owañ:[np.0,6]");
float.TryParse(Console.ReadLine(), out pCross);
Console.WriteLine("Podaj pstwo mutacji:[np.0,6]");
float.TryParse(Console.ReadLine(), out pMutate);
Console.WriteLine("Podaj ziarno:[np.100]");
Int32.TryParse(Console.ReadLine(), out seed);
Console.WriteLine("Podaj procent najlepszych chromosomow[np. 70]:");
float.TryParse(Console.ReadLine(), out percentOfBestChromosomes);
var evolutionary = new Evolutionary(pCross, pMutate, maxTime, population, percentOfBestChromosomes, maxNumberOfGenerations,
maxMutationNumber, maxNumberOfContinuousNonBetterSolutions, seed, network);
if (method == Method.DAP)
{
Stopwatch stopWatch = new Stopwatch();
stopWatch.Start();
var result = evolutionary.RunDAP();
stopWatch.Stop();
Console.WriteLine($"Liczba iteracji: {evolutionary.CurrentGeneration}");
Console.WriteLine($"Czas uzyskania rozwi¹zania: {stopWatch.Elapsed}");
Console.WriteLine($"Przeci¹¿enie DAP: {result.CapacityExceededLinksNumber}");
Console.WriteLine("Najlepsze rozwi¹zanie: ");
var demandId = result.XesDictionary.ElementAt(0).Key.DemandId;
Console.WriteLine("");
Console.Write($"[{demandId}]");
foreach (var item in result.XesDictionary)
{
if (item.Key.DemandId != demandId)
{
Console.WriteLine("");
Console.Write($"[{item.Key.DemandId}]");
demandId = item.Key.DemandId;
}
Console.Write($"{item.Key.PathId} -> {item.Value};");
}
FileWriter writer = new FileWriter();
writer.WriteToFile(result, "DAP_" + fileName);
}
else
{
Stopwatch stopWatch = new Stopwatch();
stopWatch.Start();
var result = evolutionary.RunDDAP();
stopWatch.Stop();
Console.WriteLine($"Liczba iteracji: {evolutionary.CurrentGeneration}");
Console.WriteLine($"Czas uzyskania rozwi¹zania: {stopWatch.Elapsed}");
Console.WriteLine($"Koszt DDAP: {result.NetworkCost}");
int demandId;
if (result.XesDictionary.Count > 0)
{
demandId = result.XesDictionary.ElementAt(0).Key.DemandId;
}
else
{
demandId = 1;
}
Console.WriteLine("");
Console.Write($"[{demandId}]");
foreach (var item in result.XesDictionary)
{
if (item.Key.DemandId != demandId)
{
Console.WriteLine("");
Console.Write($"[{item.Key.DemandId}]");
demandId = item.Key.DemandId;
}
Console.Write($"{item.Key.PathId} -> {item.Value};");
}
FileWriter writer = new FileWriter();
writer.WriteToFile(result, "DDAP_" + fileName);
}
}
