public static Genome CreateFrom(DynamicAsymmetricMultiRoute route)
{
Genome genome = new Genome();
List <int> customers = new List <int>();
List <int> sizes = new List <int>();
for (int idx = 0; idx < route.Count; idx++)
{
int customer_idx = 0;
foreach (int customer in route.Route(idx))
{
customer_idx++;
customers.Add(customer);
}
sizes.Add(customer_idx);
}
genome.Customers = customers.ToArray();
genome.Sizes = sizes.ToArray();
return(genome);
}
/// <summary>
/// Generates individuals based on a random first customer for each route.
/// </summary>
/// <param name="solver"></param>
/// <returns></returns>
public Individual <List <Genome>, Problem, Fitness> Generate(
Solver <List <Genome>, Problem, Fitness> solver)
{
Problem problem = solver.Problem;
DynamicAsymmetricMultiRoute multi_route = new DynamicAsymmetricMultiRoute(problem.Size, true);
// create the problem for the genetic algorithm.
List <int> customers = new List <int>();
for (int customer = problem.Depots.Count; customer < problem.Size; customer++)
{
customers.Add(customer);
}
CheapestInsertionHelper helper = new CheapestInsertionHelper();
List <double> weights = new List <double>();
for (int i = 0; i < problem.Depots.Count; i++)
{
multi_route.Add(i);
weights.Add(0);
}
int k = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(problem.Depots.Count);
// keep placing customer until none are left.
while (customers.Count > 0)
{
k = (k + 1) % problem.Depots.Count;
// use best placement to generate a route.
IRoute current_route = multi_route.Route(k);
//Console.WriteLine("Starting new route with {0}", customer);
while (customers.Count > 0)
{
// calculate the best placement.
CheapestInsertionResult result = CheapestInsertionHelper.CalculateBestPlacement(problem, current_route, customers);
if (result.CustomerAfter == -1 || result.CustomerBefore == -1)
{
customers.Remove(result.Customer);
continue;
}
// calculate the new weight.
customers.Remove(result.Customer);
//current_route.InsertAfterAndRemove(result.CustomerBefore, result.Customer, result.CustomerAfter);
current_route.InsertAfter(result.CustomerBefore, result.Customer);
weights[k] += result.Increase + 15 * 60;
if (weights[k] == weights.Max())
{
break;
}
}
}
for (int i = 0; i < problem.Depots.Count; i++)
{
multi_route.RemoveCustomer(i);
}
List <Genome> genomes = new List <Genome>();
genomes.Add(Genome.CreateFrom(multi_route));
Individual <List <Genome>, Problem, Fitness> individual = new Individual <List <Genome>, Problem, Fitness>(genomes);
//individual.Initialize();
return(individual);
}
