public override List <T> Procreate(List <T> population)
{
int max = population.Count;
for (int i = 0; i < max - 1; i += 2)
{
T parent_one = population[i];
T parent_two = population[i + 1];
Stopwatch sw = Stopwatch.StartNew();
// We verwachten maar 1 kind.
T child = crossover_provider.DoCrossover(parent_one, parent_two).Item1;
child = local_search.Search(child);
sw.Stop();
results.Add(child, sw.ElapsedTicks);
if (!child.Data.Equals(parent_one.Data) && !child.Data.Equals(parent_two.Data))
{
population.Add(child);
}
}
return(population);
}
private void searchThread(int pID, int max, int seed, INeighborhood <GraphGenome> neighborhood, bool silent = false)
{
Console.WriteLine("Thread {0} started...", pID);
Random random = new Random(seed);
// TODO: Resultaten (dus CPU computational time) opslaan in bestand.
LocalSearch <GraphGenome> local_search =
new LocalSearch <GraphGenome>(500,
neighborhood,
new GraphComparer <GraphGenome>(), random);
// Dit wil ik eigenlijk static doen, maar dan komen we in de knoei met data_size.
GraphGenome graph = new GraphGenome(500);
graph.CreateGraph("Graph500.txt");
GraphGenome optimum = null;
for (int i = 0; i < ExperimentAmount; ++i)
{
AssignmentTwoResults <GraphGenome> inner_results = new AssignmentTwoResults <GraphGenome>();
for (int j = 0; j < max; j++)
{
graph = new GraphGenome(500);
graph.Generate(ref random);
Stopwatch sw = Stopwatch.StartNew();
GraphGenome inner_optimum = local_search.Search(graph);
sw.Stop();
inner_results.Add(inner_optimum, sw.ElapsedTicks);
if (!silent)
{
Console.WriteLine("Found {0} in {1} ticks or {2}ms. ({3}/{4}), pID: {5}", inner_optimum.Fitness, sw.ElapsedTicks,
sw.ElapsedMilliseconds, j, max, pID);
}
if (optimum == null || optimum.Fitness >= inner_optimum.Fitness)
{
optimum = inner_optimum;
}
}
lock (solutionsThreads)
{
solutionsThreads[pID] = optimum;
}
lock (elapsedMilisecondsThreads)
{
elapsedMilisecondsThreads[pID].Add(inner_results);
}
}
}
public override List <T> Generate(int population_size, int genome_size)
{
List <T> population = new List <T>();
for (uint i = 0; i < population_size; ++i)
{
T g = (T)Activator.CreateInstance(typeof(T), genome_size);
g.Generate(ref random_source);
g = local_search.Search(g);
population.Add(g);
}
return(population);
}
private AssignmentTwoResultList <GraphGenome> IteratedLocalSearch(INeighborhood <GraphGenome> neighborhood, bool silent = false)
{
LocalSearch <GraphGenome> local_search =
new LocalSearch <GraphGenome>(500,
neighborhood,
new GraphComparer <GraphGenome>(), main_random_source);
IMutation <GraphGenome> pertubation = new ILSPertubation <GraphGenome>(main_random_source);
GraphGenome graph = new GraphGenome(500);
graph.CreateGraph("Graph500.txt");
GraphGenome optimum = null;
List <long> elapsedMilisecondsList = new List <long>();
AssignmentTwoResultList <GraphGenome> results = new AssignmentTwoResultList <GraphGenome>("$ILS_{" + neighborhood.Name + "}$");
for (int i = 0; i < ExperimentAmount; ++i)
{
AssignmentTwoResults <GraphGenome> res = new AssignmentTwoResults <GraphGenome>();
for (int j = 0; j < OptimaAmount; j++)
{
if (optimum == null)
{
graph = new GraphGenome(500);
graph.Generate(ref main_random_source);
}
else
{
graph = pertubation.Mutate(optimum);
}
Stopwatch sw = Stopwatch.StartNew();
GraphGenome inner_optimum = local_search.Search(graph);
sw.Stop();
elapsedMilisecondsList.Add(sw.ElapsedMilliseconds);
res.Add(inner_optimum, sw.ElapsedTicks);
if (!silent)
{
Console.WriteLine("Found {0} in {1} ticks or {2}ms. ({3}/{4})", inner_optimum.Fitness, sw.ElapsedTicks,
sw.ElapsedMilliseconds, j, OptimaAmount);
}
if (optimum == null || optimum.Fitness >= inner_optimum.Fitness)
{
optimum = inner_optimum;
}
optimum.FunctionEvaluations = 0;
}
results.Add(res);
}
//Console.WriteLine("Best solution found: {0} in an average of {1} ms", optimum.Fitness, cpu_ticks.Average());
Console.WriteLine("Best solution found: {0} in an average of {1} ms", optimum.Fitness, elapsedMilisecondsList.Sum() / OptimaAmount);
//Console.WriteLine("Total time: {0} sec", sw.ElapsedMilliseconds / 1000f);
optimum.ToImage(String.Format("results/ILS[{0}]-{1}.bmp", neighborhood.Name, optimum.Fitness), 3000, 3000);
//Console.ReadLine();
return(results);
}