public (List <int> jobOrder, int minTardiness) Solve(IMethodOptions imethodoptions, Stopwatch stopwatch)
{
var options = imethodoptions as SimulatedAnnealingOptions;
List <int> bestOrder = options.Data.Select(x => x.Index).ToList();
var minTardiness = int.MaxValue;
var count = 0;
int step = 2;
options.GuiConnection?.LogText?.Invoke($"Start : {DateTime.Now:HH:mm:ss.fff}");
stopwatch.Start();
try
{
while (count < options.IterationCount)
{
options.GuiConnection?.LogText?.Invoke($"Iteracja: {count}");
List <int> candidateOrder = new List <int>(bestOrder);
candidateOrder.Swap(ThreadSafeRandom.ThisThreadsRandom.Next(0, bestOrder.Count), ThreadSafeRandom.ThisThreadsRandom.Next(0, bestOrder.Count));
options.GuiConnection?.LogText?.Invoke($"Kandydat: {string.Join(",", candidateOrder)}");
var delta = options.Data.JobsFromIndexList(candidateOrder).CountPenalty() - options.Data.JobsFromIndexList(bestOrder).CountPenalty();
options.GuiConnection?.LogText?.Invoke($"Zmiana sumy opóźnień: {delta}");
var alpha = 10 + count * step * 2; // control parameter
var acceptanceProbability = Math.Exp(-alpha * delta);
options.GuiConnection?.LogText?.Invoke($"Szansa akceptacji = { acceptanceProbability}");
if (acceptanceProbability > ThreadSafeRandom.GetRandomDouble(0, 1))
{
bestOrder = candidateOrder;
options.GuiConnection?.LogText?.Invoke($"Zaakceptowano{Environment.NewLine}");
}
count += 1;
options.CancellationToken.ThrowIfCancellationRequested();
}
}
catch (OperationCanceledException)
{
imethodoptions.GuiConnection?.LogText("Przerwano wykonwanie zadania");
}
stopwatch.Stop();
minTardiness = options.Data.JobsFromIndexList(bestOrder).CountPenalty();
return(bestOrder, minTardiness);
}
public (List <int> jobOrder, int minTardiness) Solve(IMethodOptions imethodoptions, Stopwatch stopwatch)
{
var options = imethodoptions as AlphaDominantGeneticOptions;
var minTardiness = options.Data.CountPenalty();
int dataCount = options.Data.Count;
List <int> best = options.Data.Select(x => x.Index).ToList();
List <(List <int> indiv, double fitness)> pop;
string prev = "";
options.OldPopCount = (int)(options.PopulationSize * (1 - options.CrossoverRate));
options.GuiConnection?.LogText?.Invoke($"Wielkość starej populacji: {options.OldPopCount}");
options.GuiConnection?.LogText?.Invoke($"Start : {DateTime.Now:HH:mm:ss.fff}");
stopwatch.Start();
try
{
options.GuiConnection?.LogText?.Invoke("Generowanie populacji startowej");
pop = GenerateStartingPopulation(options.Data, options.PopulationSize);
options.GuiConnection?.LogText?.Invoke("Sortowanie");
pop.Sort((x, y) => y.fitness.CompareTo(x.fitness));
best = pop[0].indiv;
int iter = 0;
while (iter < options.IterationCount)
{
options.GuiConnection?.LogText?.Invoke($"Osobnik alpha o F = {pop[0].fitness}");
options.GuiConnection?.LogText?.Invoke($"Iteracja: {iter}, generowanie nowej populacji");
pop = GenerateNewPopulation(pop, options);
for (int i = 0; i < pop.Count; i++)
{
if (ThreadSafeRandom.GetRandomDouble() < options.MutationChance)
{
if (options.GuiConnection != null)
{
prev = $"{string.Join(',', pop[i].indiv)}, F = {pop[i].fitness}";
}
int index1 = ThreadSafeRandom.ThisThreadsRandom.Next(dataCount);
int index2 = ThreadSafeRandom.ThisThreadsRandom.Next(dataCount);
pop[i].indiv.Swap(index1, index2);
pop[i] = (pop[i].indiv, CalculateFitness(pop[i].indiv, options.Data));
options.GuiConnection?.LogText?.Invoke($" Mutacja: i = {i} | {prev} -> {string.Join(',', pop[i].indiv)}, F = {pop[i].fitness}");
}
}
options.GuiConnection?.LogText?.Invoke(" Sortowanie");
pop.Sort((x, y) => y.fitness.CompareTo(x.fitness));
best = pop[0].indiv;
iter += 1;
options.CancellationToken.ThrowIfCancellationRequested();
}
}
catch (OperationCanceledException)
{
imethodoptions.GuiConnection?.LogText("Przerwano wykonwanie zadania");
}
stopwatch.Stop();
options.GuiConnection?.LogText?.Invoke($"Koniec : {DateTime.Now:HH:mm:ss.fff}");
minTardiness = options.Data.JobsFromIndexList(best).CountPenalty();
return(best, minTardiness);
}
