// Evolves a population over one generation
public static Population evolvePopulation(Population pop)
{
Population newPopulation = new Population(pop.populationSize(), false);
// Keep our best individual if elitism is enabled
int elitismOffset = 0;
if (elitism)
{
newPopulation.saveTour(0, pop.getFittest());
elitismOffset = 1;
}
// Crossover population
// Loop over the new population's size and create individuals from
// Current population
for (int i = elitismOffset; i < newPopulation.populationSize()-1; i++)
{
// Select parents
Tour parent1 = tournamentSelection(pop);
Tour parent2 = tournamentSelection(pop);
// Crossover parents
//if (rdm1.NextDouble() < 0.8)
//{
Tour[] child = crossover(parent1, parent2);
// Add child to new population
newPopulation.saveTour(i++, child[0]);
newPopulation.saveTour(i, child[1]);
//}
//else
//newPopulation.saveTour(i, parent1);
}
Tour parent3 = tournamentSelection(pop);
Tour parent4 = tournamentSelection(pop);
// Crossover parents
//if (rdm1.NextDouble() < 0.8)
//{
Tour[] child1 = crossover(parent3, parent4);
// Add child to new population
newPopulation.saveTour(newPopulation.populationSize() - 1, child1[0]);
// Mutate the new population a bit to add some new genetic material
for (int i = elitismOffset; i < newPopulation.populationSize(); i++)
{
if (rdm1.NextDouble() < mutationRate)
{
mutate(newPopulation.getTour(i));
}
}
return newPopulation;
}
public static int[] tsp(Point[] cidades, int[][] adjacencyMatrix, int inicio)
{
TourManager.clear();
for (int i = 0; i < cidades.Length; i++)
{
City city = new City(i, cidades[i].X, cidades[i].Y, adjacencyMatrix[i]);
TourManager.addCity(city);
}
// Initialize population
Population pop = new Population(3, true);
Console.WriteLine("Initial distance: " + pop.getFittest().getDistance());
// Evolve population for 100 generations
pop = TSP_GA.evolvePopulation(pop);
for (int i = 0; i < 1000; i++)
{
pop = TSP_GA.evolvePopulation(pop);
Console.WriteLine("Intermediate distance: " + pop.getTour(0).getDistance());
}
// Print final results
Console.WriteLine("Finished");
Console.WriteLine("Final distance: " + pop.getFittest().getDistance());
Console.WriteLine("Solution:");
Console.WriteLine(pop.getFittest().ToString());
int[] caminho = new int[cidades.Length + 1];
caminho[caminho.Length - 1] = pop.getFittest().getDistance();
List<int> per = pop.getFittest().getPercurso();
for (int i = 0; i < caminho.Length-1; i++)
{
caminho[i] = per[i];
}
return caminho;
}
// Selects candidate tour for crossover
private static Tour tournamentSelection(Population pop)
{
// Create a tournament population
Population tournament = new Population(tournamentSize, false);
// For each place in the tournament get a random candidate tour and
// add it
for (int i = 0; i < tournamentSize; i++)
{
int randomId = rdm1.Next(pop.populationSize());
tournament.saveTour(i, pop.getTour(randomId));
//Console.WriteLine(randomId);
}
// Get the fittest tour
Tour fittest = tournament.getFittest();
return fittest;
}
