/// <summary>
/// Considers one customer for relocation.
/// </summary>
/// <param name="problem"></param>
/// <param name="route"></param>
/// <param name="previous"></param>
/// <param name="current"></param>
/// <param name="next"></param>
/// <param name="route_weight"></param>
/// <param name="max"></param>
/// <returns></returns>
private bool ConsiderCustomer(IProblemWeights problem, IRoute route, int previous, int current, int next, double route_weight, double max)
{
// calculate the removal gain of the customer.
double removal_gain = problem.WeightMatrix[previous][current] + problem.WeightMatrix[current][next]
- problem.WeightMatrix[previous][next];
if (removal_gain > 0.0001)
{
// try and place the customer in the next route.
CheapestInsertionResult result =
CheapestInsertionHelper.CalculateBestPlacement(problem, route, current);
if (result.Increase < removal_gain - 0.001 && route_weight + result.Increase < max)
{ // there is a gain in relocating this customer.
int count_before = route.Count;
// string route_string = route.ToString();
// and the route is still within bounds!
route.ReplaceEdgeFrom(result.CustomerBefore, result.Customer);
route.ReplaceEdgeFrom(result.Customer, result.CustomerAfter);
int count_after = route.Count;
if (count_before + 1 != count_after)
{
throw new Exception();
}
return(true);
}
}
return(false);
}
/// <summary>
/// Generates individuals based on a random first customer for each route.
/// </summary>
/// <param name="solver"></param>
/// <returns></returns>
public Individual <MaxTimeSolution, MaxTimeProblem, Fitness> Generate(
Solver <MaxTimeSolution, MaxTimeProblem, Fitness> solver)
{
MaxTimeProblem problem = solver.Problem;
MaxTimeSolution solution = new MaxTimeSolution(problem.Size, true);
// create the problem for the genetic algorithm.
List <int> customers = new List <int>();
for (int customer = 0; customer < problem.Size; customer++)
{
customers.Add(customer);
}
//BestPlacementHelper helper = new BestPlacementHelper();
// keep placing customer until none are left.
while (customers.Count > 0)
{
// select a random customer.
double weight = 0;
int customer_idx = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(customers.Count);
int customer = customers[customer_idx];
customers.RemoveAt(customer_idx);
// use best placement to generate a route.
IRoute current_route = solution.Add(customer);
//Console.WriteLine("Starting new route with {0}", customer);
while (customers.Count > 0)
{
// calculate the best placement.
int customer_to_place = customers[OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(customers.Count)];
CheapestInsertionResult result = CheapestInsertionHelper.CalculateBestPlacement(problem, current_route, customer_to_place);
// calculate the new weight.
double potential_weight = result.Increase + weight + 20;
// cram as many customers into one route as possible.
if (potential_weight < problem.Max.Value)
{ // ok we are done!
customers.Remove(result.Customer);
//current_route.InsertAfterAndRemove(result.CustomerBefore, result.Customer, result.CustomerAfter);
current_route.InsertAfter(result.CustomerBefore, result.Customer);
weight = potential_weight;
}
else
{
break;
}
}
}
return(new Individual <MaxTimeSolution, MaxTimeProblem, Fitness>(solution));
}
/// <summary>
/// Solves the given problem.
/// </summary>
/// <returns></returns>
public sealed override Tour Solve(STSProblem problem, STSPObjective objective, out STSPFitness fitness)
{
// generate random pool to select customers from.
if (_randomPool == null || _randomPool.Size < problem.Weights.Length)
{
_randomPool = new RandomPool(problem.Weights.Length);
}
else
{
_randomPool.Reset();
}
// keep adding customers until no more space is left or no more customers available.
var tour = problem.CreateEmptyTour();
fitness = new STSPFitness()
{
Weight = 0,
Customers = 1
};
while (_randomPool.MoveNext())
{
var customer = _randomPool.Current;
if (customer == problem.First ||
customer == problem.Last)
{
continue;
}
Pair location;
var cost = CheapestInsertionHelper.CalculateCheapest(tour, problem.Weights, customer, out location);
if (cost + fitness.Weight < problem.Max)
{
tour.InsertAfter(location.From, customer);
fitness.Weight = fitness.Weight + cost;
fitness.Customers = fitness.Customers + 1;
}
}
// calculate fitness.
fitness = objective.Calculate(problem, tour);
return(tour);
}
/// <summary>
/// Re-inserts a customer in the route.
/// </summary>
/// <param name="weights"></param>
/// <param name="route"></param>
/// <param name="customer"></param>
/// <param name="difference"></param>
/// <returns></returns>
public static bool InsertOne(IProblemWeights weights, IRoute route, int customer,
out double difference)
{
// calculate placement.
CheapestInsertionResult result =
CheapestInsertionHelper.CalculateBestPlacement(weights, route, customer);
// place the customer.
if (result.CustomerAfter >= 0 && result.CustomerBefore >= 0)
{
//route.InsertAfterAndRemove(result.CustomerBefore, result.Customer, result.CustomerAfter);
route.InsertAfter(result.CustomerBefore, result.Customer);
difference =
-(weights.WeightMatrix[result.CustomerBefore][result.CustomerAfter]) +
(weights.WeightMatrix[result.CustomerBefore][result.Customer]) +
(weights.WeightMatrix[result.Customer][result.CustomerAfter]);
return(true);
}
difference = 0;
return(false);
}
/// <summary>
/// Executes a solver procedure.
/// </summary>
/// <param name="problem"></param>
/// <returns></returns>
internal override MaxTimeSolution Solve(MaxTimeProblem problem)
{
// create the calculator.
MaxTimeCalculator calculator = new MaxTimeCalculator(problem);
// create the solution.
MaxTimeSolution solution = new MaxTimeSolution(problem.Size, true);
// keep placing customer until none are left.
List <int> customers = new List <int>(problem.Customers);
while (customers.Count > 0)
{
// select a customer using some heuristic.
int customer_idx = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(customers.Count);
int customer = customers[customer_idx];
customers.Remove(customer);
// start a route r.
double current_route_weight = 0;
IRoute current_route = solution.Add(customer);
//Console.WriteLine("Starting new route with {0}", customer);
while (customers.Count > 0)
{
// calculate the best placement.
CheapestInsertionResult result =
CheapestInsertionHelper.CalculateBestPlacement(problem, current_route, customers);
// calculate the new weight.
double potential_weight = calculator.CalculateOneRouteIncrease(current_route_weight, result.Increase);
// cram as many customers into one route as possible.
if (potential_weight < problem.Max.Value)
{
// insert the customer, it is
customers.Remove(result.Customer);
//current_route.InsertAfterAndRemove(result.CustomerBefore, result.Customer, result.CustomerAfter);
current_route.InsertAfter(result.CustomerBefore, result.Customer);
current_route_weight = potential_weight;
//// improve if needed.
////if (improvement_probalitity > OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(1))
//if (((problem.Size - customers.Count) % _k) == 0)
//{ // an improvement is descided.
// current_route_weight = this.ImproveIntraRoute(problem,
// current_route, current_route_weight);
//}
}
else
{// ok we are done!
//// apply the intra-route heuristics.
//for (int route_idx = 0; route_idx < solution.Count - 1; route_idx++)
//{ // apply the intra-route heurstic between the new and all existing routes.
// this.ImproveInterRoute(problem, solution.Route(route_idx), current_route);
//}
//// apply the inter-route heuristics.
//for (int route_idx = 0; route_idx < solution.Count; route_idx++)
//{ // apply heurstic for each route.
// IRoute route = solution.Route(route_idx);
// this.ImproveIntraRoute(problem, current_route, current_route_weight);
//}
// break the route.
break;
}
}
}
return(solution);
}
/// <summary>
/// Executes a solver procedure.
/// </summary>
/// <param name="problem"></param>
/// <returns></returns>
internal override MaxTimeSolution Solve(MaxTimeProblem problem)
{
// create the solution.
var solution = new MaxTimeSolution(problem.Size);
// keep placing customer until none are left.
var customers = new List <int>(problem.Customers);
customers.RemoveAt(0);
double max = problem.Max.Value - (problem.Max.Value * _deltaPercentage);
// keep a list of cheapest insertions.
IInsertionCosts costs = new BinaryHeapInsertionCosts();
double percentage = _thresholdPercentage;
while (customers.Count > 0)
{
//// try and distribute the remaining customers if there are only a few left.
//if (customers.Count < problem.Size * percentage)
//{
// bool succes = true;
// while (succes && customers.Count > 0)
// {
// succes = false;
// CheapestInsertionResult best = new CheapestInsertionResult();
// best.Increase = float.MaxValue;
// int best_idx = -1;
// for (int route_idx = 0; route_idx < solution.Count; route_idx++)
// {
// IRoute route = solution.Route(route_idx);
// CheapestInsertionResult result =
// CheapestInsertionHelper.CalculateBestPlacement(problem, route, customers);
// if (best.Increase > result.Increase)
// {
// best = result;
// best_idx = route_idx;
// }
// }
// IRoute best_route = solution.Route(best_idx);
// double route_time = problem.Time(best_route);
// if (route_time + best.Increase < max)
// { // insert the customer.
// best_route.InsertAfter(best.CustomerBefore, best.Customer);
// customers.Remove(best.Customer);
// this.Improve(problem, solution, max, best_idx);
// succes = true;
// }
// }
//}
// select a customer using some heuristic.
int customer = this.SelectSeed(problem, problem.MaxTimeCalculator, solution, customers);
customers.Remove(customer);
// start a route r.
IRoute currentRoute = solution.Add(customer);
solution[solution.Count - 1] = 0;
while (customers.Count > 0)
{
// calculate the best placement.
CheapestInsertionResult result;
if (_useSeedCost)
{ // use the seed cost; the cost to the seed customer.
result = CheapestInsertionHelper.CalculateBestPlacement(problem, currentRoute, customers,
customer, 0.7);
// calculate the 'real' increase.
result.Increase = (problem.WeightMatrix[result.CustomerBefore][result.Customer] +
problem.WeightMatrix[result.Customer][result.CustomerAfter]) -
problem.WeightMatrix[result.CustomerBefore][result.CustomerAfter];
}
else
{ // just use cheapest insertion.
result = CheapestInsertionHelper.CalculateBestPlacement(problem, currentRoute, customers, costs);
}
// calculate the new weight.
solution[solution.Count - 1] = problem.Time(solution.Route(solution.Count - 1));
double potentialWeight = problem.MaxTimeCalculator.CalculateOneRouteIncrease(solution[solution.Count - 1],
result.Increase);
// cram as many customers into one route as possible.
if (potentialWeight < max)
{
// insert the customer, it is
customers.Remove(result.Customer);
currentRoute.InsertAfter(result.CustomerBefore, result.Customer);
// free some memory in the costs list.
costs.Remove(result.CustomerBefore, result.CustomerAfter);
// update the cost of the route.
solution[solution.Count - 1] = potentialWeight;
// improve if needed.
if (((problem.Size - customers.Count) % _k) == 0)
{ // an improvement is decided.
// apply the inter-route improvements.
var copy = (solution.Clone() as MaxTimeSolution);
int countBefore = solution.Route(solution.Count - 1).Count;
solution[solution.Count - 1] = this.ImproveIntraRoute(problem,
solution.Route(solution.Count - 1), solution[solution.Count - 1]);
if (!solution.IsValid())
{
throw new Exception();
}
int countAfter = solution.Route(solution.Count - 1).Count;
if (countAfter != countBefore)
{
throw new Exception();
}
// also to the inter-improvements.
currentRoute = this.Improve(problem, solution, max, solution.Count - 1);
}
}
else
{// ok we are done!
this.Improve(problem, solution, max, solution.Count - 1);
// break the route.
break;
}
}
}
// remove empty routes.
for (int routeIdx = solution.Count - 1; routeIdx >= 0; routeIdx--)
{
if (solution.Route(routeIdx).IsEmpty)
{
solution.Remove(routeIdx);
}
}
return(solution);
}
/// <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);
}
/// <summary>
/// Does the mutation.
/// </summary>
/// <param name="solver"></param>
/// <param name="mutating"></param>
/// <returns></returns>
public Individual <List <Genome>, Problem, Fitness> Mutate(
Solver <List <Genome>, Problem, Fitness> solver,
Individual <List <Genome>, Problem, Fitness> mutating)
{
// get the route information.
Genome multi_route = mutating.Genomes[0];
int[] size_new = null;
int[] customers_new = null;
if (multi_route.Sizes.Length > 1)
{ // TODO: Maybe add some extra code for the the route-count is very low and chances of collisions are big.
// TODO: investigate what is more expensive, and extra random generation or creating a list and remove items.
// http://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle
// select a route.
int source_route_idx = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(multi_route.Sizes.Length);
int target_route_idx = -1;
do
{
target_route_idx = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(multi_route.Sizes.Length);
} while (source_route_idx == target_route_idx);
int source_count = multi_route.Sizes[source_route_idx];
int target_count = multi_route.Sizes[target_route_idx];
if (target_count > 0 && source_count > 3)
{
// take a part out of the orginal.
int size = (int)OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(source_count);
int source_location = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(source_count);
int first = source_location - (size / 2);
if (first < 0)
{
first = 0;
}
first = multi_route.StartOf(source_route_idx) + first;
int last = source_location + (size / 2);
if (last > source_count - 1)
{
last = source_count - 1;
}
last = multi_route.StartOf(source_route_idx) + last;
int idx = -1;
List <int> part_of_orginal = new List <int>();
foreach (int customer in multi_route.Customers)
{
idx++;
if (idx >= first && idx <= last)
{
part_of_orginal.Add(customer);
}
}
// place it somewhere in the target.
if (part_of_orginal.Count > 0)
{
IRoute target = multi_route.Route(target_route_idx);
CheapestInsertionResult route_placement = CheapestInsertionHelper.CalculateBestPlacement(
solver.Problem, target, part_of_orginal[0], part_of_orginal[part_of_orginal.Count - 1]);
// create a new array and start copying.
customers_new = new int[multi_route.Customers.Length];
int new_idx = 0;
for (idx = 0; idx < multi_route.Customers.Length; idx++)
{
if (idx >= first && idx <= last)
{
// do nothing.
}
else
{
customers_new[new_idx] = multi_route.Customers[idx];
new_idx++;
if (multi_route.Customers[idx] == route_placement.CustomerBefore)
{ // insert the entire between part here.
for (int between_idx = 0; between_idx < part_of_orginal.Count; between_idx++)
{
customers_new[new_idx] = part_of_orginal[between_idx];
new_idx++;
}
}
}
}
// adjust sizes array.
size_new = new int[multi_route.Sizes.Length];
for (idx = 0; idx < multi_route.Sizes.Length; idx++)
{
if (idx == source_route_idx)
{
size_new[idx] = multi_route.Sizes[idx] - part_of_orginal.Count;
}
else if (idx == target_route_idx)
{
size_new[idx] = multi_route.Sizes[idx] + part_of_orginal.Count;
}
else
{
size_new[idx] = multi_route.Sizes[idx];
}
}
}
}
}
if (size_new == null || customers_new == null)
{
size_new = multi_route.Sizes.Clone() as int[];
customers_new = multi_route.Customers.Clone() as int[];
}
// remove all zero's.
List <int> sizes = new List <int>(size_new);
while (sizes.Remove(0))
{
}
size_new = sizes.ToArray <int>();
List <Genome> genomes = new List <Genome>();
Genome genome = new Genome();
genome.Sizes = size_new;
genome.Customers = customers_new;
if (!genome.IsValid())
{
throw new Exception();
}
genomes.Add(genome);
Individual <List <Genome>, Problem, Fitness> individual = new Individual <List <Genome>, Problem, Fitness>(genomes);
//individual.Initialize();
return(individual);
}
/// <summary>
/// Tries to relocate customers using the source the same as the CrossExchange but places customers using cheapest insertion.
/// </summary>
/// <param name="problem"></param>
/// <param name="solution"></param>
/// <param name="route1_idx"></param>
/// <param name="route2_idx"></param>
/// <param name="max"></param>
/// <returns></returns>
public bool Improve(MaxTimeProblem problem, MaxTimeSolution solution,
int route1_idx, int route2_idx, double max)
{
int max_window = 10;
IRoute route1 = solution.Route(route1_idx);
IRoute route2 = solution.Route(route2_idx);
double total_before = problem.Time(solution.Route(route1_idx)) +
problem.Time(solution.Route(route2_idx));
int route1_customers = route1.Count;
int route2_customers = route2.Count;
double[] route1_cumul = problem.TimeCumul(route1);
double[] route2_cumul = problem.TimeCumul(route2);
// build all edge weights.
List <Edge> route1_edges = new List <Edge>(route1.Edges());
List <Edge> route2_edges = new List <Edge>(route2.Edges());
double[] route1_weights = new double[route1_edges.Count];
for (int idx = 0; idx < route1_edges.Count; idx++)
{
Edge edge = route1_edges[idx];
route1_weights[idx] = problem.WeightMatrix[edge.From][edge.To];
}
double[] route2_weights = new double[route2_edges.Count];
for (int idx = 0; idx < route2_edges.Count; idx++)
{
Edge edge = route2_edges[idx];
route2_weights[idx] = problem.WeightMatrix[edge.From][edge.To];
}
List <EdgePair> route2_pairs = new List <EdgePair>();
for (int i_idx = 0; i_idx < route2_edges.Count - 2; i_idx++)
{
Edge i = route2_edges[i_idx];
double i_weight = route2_weights[i_idx];
double weight_before_i = route2_cumul[i_idx];
int k_idx_max = route2_edges.Count;
if (k_idx_max > i_idx + 2 + max_window)
{
k_idx_max = i_idx + 2 + max_window;
}
for (int k_idx = i_idx + 2; k_idx < k_idx_max; k_idx++)
{
Edge k = route2_edges[k_idx];
double k_weight = route2_weights[k_idx];
double weight_after_k = route2_cumul[route2_cumul.Length - 1] - route2_cumul[k_idx + 1];
double weight_between_route = route2_cumul[k_idx] - route2_cumul[i_idx + 1];
route2_pairs.Add(new EdgePair()
{
First = i,
FirstWeight = i_weight,
Second = k,
SecondWeight = k_weight,
Between = new List <int>(route2.Between(i.To, k.From)),
WeightTotal = i_weight + k_weight,
WeightAfter = weight_after_k,
WeightBefore = weight_before_i,
WeightBetween = weight_between_route,
CustomersBetween = k_idx - i_idx
});
}
}
// try to relocate all and find best pair.
double route1_weight = route1_cumul[route1_cumul.Length - 1];
EdgePair best = null;
CheapestInsertionResult best_result = new CheapestInsertionResult();
double best_extra = double.MaxValue;
foreach (EdgePair pair2 in route2_pairs)
{
// calculate cheapest insertion.
CheapestInsertionResult result =
CheapestInsertionHelper.CalculateBestPlacement(problem, route1,
pair2.First.To, pair2.Second.From);
double extra_route2 = problem.WeightMatrix[pair2.First.From][pair2.Second.To];
// check if the result has a net-decrease.
if (result.Increase + extra_route2 < pair2.WeightTotal - 0.01)
{ // there is a net decrease.
// calculate the real increase.
double new_weight = problem.Time(route1_weight + result.Increase + pair2.WeightBetween, route1_customers +
pair2.CustomersBetween);
// check the max.
if (new_weight < max && new_weight < best_extra)
{ // the route is smaller than max.
best_extra = new_weight;
best_result = result;
best = pair2;
}
}
}
if (best != null)
{
if (route2.Last == best.Second.To)
{
//throw new Exception();
}
route2.ReplaceEdgeFrom(best.First.From, best.Second.To);
int previous = best_result.CustomerBefore;
foreach (int customer in best.Between)
{
route1.ReplaceEdgeFrom(previous, customer);
previous = customer;
}
route1.ReplaceEdgeFrom(previous, best_result.CustomerAfter);
// check validity.
if (!route2.IsValid())
{
throw new Exception();
}
if (!route1.IsValid())
{
throw new Exception();
}
if (route1.Count + route2.Count != route1_customers + route2_customers)
{
throw new Exception();
}
double total_after = problem.Time(solution.Route(route1_idx)) +
problem.Time(solution.Route(route2_idx));
if (total_after >= total_before)
{
throw new Exception("this is not an improvement!");
}
return(true);
}
return(false);
}
public Individual <List <Genome>, Problem, Fitness> CrossOver(
Solver <List <Genome>, Problem, Fitness> solver,
Individual <List <Genome>, Problem, Fitness> parent1,
Individual <List <Genome>, Problem, Fitness> parent2)
{
Genome route1 = parent1.Genomes[0];
Genome route2 = parent2.Genomes[0];
// get the minimum size of both routes.
int size = route1.Sizes.Length;
if (route2.Sizes.Length < size)
{
size = route2.Sizes.Length;
}
// select a random number of routes.
HashSet <int> selected_first = new HashSet <int>();
HashSet <int> selected_second = new HashSet <int>();
List <IRoute> selected_routes = new List <IRoute>();
bool first = true;
while (selected_routes.Count < size)
{
// select route.
int selected_route = -1;
if (first)
{
selected_route = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(route1.Sizes.Length);
while (selected_first.Contains(selected_route))
{
selected_route = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(route1.Sizes.Length);
}
selected_first.Add(selected_route);
selected_routes.Add(route1.Route(selected_route));
}
else
{
selected_route = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(route2.Sizes.Length);
while (selected_second.Contains(selected_route))
{
selected_route = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(route2.Sizes.Length);
}
selected_second.Add(selected_route);
selected_routes.Add(route2.Route(selected_route));
}
first = !first;
}
// generate the new customer genome.
HashSet <int> selected_customers = new HashSet <int>();
List <int> customers = new List <int>();
List <int> sizes = new List <int>();
foreach (IRoute route in selected_routes)
{
int current_size = 0;
foreach (int customer in route)
{
if (!selected_customers.Contains(customer))
{
customers.Add(customer);
current_size++;
selected_customers.Add(customer);
}
}
sizes.Add(current_size);
}
while (sizes.Remove(0))
{
}
Genome genome = new Genome();
genome.Sizes = sizes.ToArray();
genome.Customers = customers.ToArray();
// insert all non-placed customers in the order of the first route.
foreach (int customer in route1.Customers)
{
if (!selected_customers.Contains(customer))
{
// try reinsertion.
CheapestInsertionResult result = new CheapestInsertionResult();
result.Increase = float.MaxValue;
int target_idx = -1;
for (int idx = 0; idx < genome.Sizes.Length; idx++)
{
IRoute route = genome.Route(idx);
if (genome.Sizes[idx] > 0)
{
CheapestInsertionResult current_result =
CheapestInsertionHelper.CalculateBestPlacement(solver.Problem.Weights, route, customer);
if (current_result.Increase < result.Increase)
{
target_idx = idx;
result = current_result;
if (result.Increase <= 0)
{
break;
}
}
}
}
// insert the customer.
for (int idx = 0; idx < customers.Count; idx++)
{
if (customers[idx] == result.CustomerBefore)
{
if (customers.Count - 1 == idx)
{
customers.Add(customer);
}
else
{
customers.Insert(idx + 1, customer);
}
break;
}
}
// set the mutated.
genome.Sizes[target_idx] = genome.Sizes[target_idx] + 1;
genome.Customers = customers.ToArray();
}
}
if (!genome.IsValid())
{
throw new Exception();
}
List <Genome> genomes = new List <Genome>();
genomes.Add(genome);
Individual <List <Genome>, Problem, Fitness> individual = new Individual <List <Genome>, Problem, Fitness>(genomes);
//individual.Initialize();
return(individual);
}
private void FillRoutes(MaxTimeCalculator calculator, MaxTimeSolution route1, MaxTimeSolution solution,
MaxTimeProblem problem)
{
double[] weights = new double[solution.Count];
// insert all non-placed customers in the order of the first route.
HashSet <int> unplaced = new HashSet <int>();
for (int route_idx = 0; route_idx < route1.Count; route_idx++)
{
IRoute route1_route = route1.Route(route_idx);
foreach (int customer in route1_route)
{
if (!solution.Contains(customer))
{
unplaced.Add(customer);
}
}
}
for (int idx = 0; idx < solution.Count; idx++)
{
IRoute route = solution.Route(idx);
weights[idx] = calculator.CalculateOneRoute(route);
}
// insert all non-placed customers in the order of the first route.
//for (int route_idx = 0; route_idx < route1.Count; route_idx++)
//{
// IRoute route1_route = route1.Route(route_idx);
// foreach (int customer in route1_route)
// {
// if (!solution.Contains(customer))
// {
while (unplaced.Count > 0)
{
int customer = unplaced.First <int>();
// try reinsertion.
CheapestInsertionResult result = new CheapestInsertionResult();
result.Increase = double.MaxValue;
int target_idx = -1;
CheapestInsertionResult unlimited_result = new CheapestInsertionResult();
unlimited_result.Increase = double.MaxValue;
int unlimited_target_idx = -1;
for (int idx = 0; idx < solution.Count; idx++)
{
IRoute route = solution.Route(idx);
CheapestInsertionResult current_result =
CheapestInsertionHelper.CalculateBestPlacement(problem.Weights, route, customer);
if (current_result.Increase < result.Increase)
{
if (weights[idx] + current_result.Increase < problem.Max.Value)
{
target_idx = idx;
result = current_result;
if (result.Increase <= 0)
{
break;
}
}
}
if (current_result.Increase < unlimited_result.Increase)
{
unlimited_target_idx = idx;
unlimited_result = current_result;
}
}
if (target_idx < 0)
{
result = unlimited_result;
target_idx = unlimited_target_idx;
}
// get the target route and insert.
IRoute target_route = solution.Route(target_idx);
weights[target_idx] = weights[target_idx] + result.Increase;
//target_route.InsertAfterAndRemove(result.CustomerBefore, result.Customer, result.CustomerAfter);
target_route.InsertAfter(result.CustomerBefore, result.Customer);
unplaced.Remove(result.Customer);
////solution.ToString();
//if (!solution.IsValid())
//{
// throw new Exception();
//}
}
// }
//}
}
/// <summary>
/// Applies this operator.
/// </summary>
public bool Apply(STSProblem problem, STSPObjective objective, Tour solution, out STSPFitness delta)
{
var before = objective.Calculate(problem, solution);
var weights = problem.Weights;
delta = objective.Zero;
var i = _n;
var toInsert = new List <int>();
if (!_insertNew)
{ // select existing customers, to reinsert.
while (solution.Count > 1 && i > 0)
{
i--;
var index = RandomGeneratorExtensions.GetRandom().Generate(solution.Count);
var current = solution.GetCustomerAt(index);
if (current != Constants.NOT_SET)
{
if (current != solution.First &&
current != solution.Last &&
solution.Remove(current))
{
toInsert.Add(current);
}
}
}
}
else if (solution.Count < problem.Weights.Length)
{ // select random new customer to insert.
while (solution.Count > 1 && i > 0)
{
i--;
var current = RandomGeneratorExtensions.GetRandom().Generate(problem.Weights.Length);
if (!solution.Contains(current))
{
if (current != solution.First &&
current != solution.Last &&
solution.Remove(current))
{
toInsert.Add(current);
}
}
}
}
var fitness = objective.Calculate(problem, solution);
foreach (var current in toInsert)
{
// insert new.
Pair position;
var cost = CheapestInsertionHelper.CalculateCheapest(solution, weights, current, out position);
if (cost + fitness.Weight < problem.Max)
{
solution.InsertAfter(position.From, current);
fitness.Weight = fitness.Weight + cost;
fitness.Customers = fitness.Customers + 1;
}
}
var after = objective.Calculate(problem, solution);
delta = objective.Subtract(problem, after, before);
return(objective.CompareTo(problem, before, after) > 0);
}
/// <summary>
/// Executes a solver procedure.
/// </summary>
/// <param name="problem"></param>
/// <returns></returns>
internal override MaxTimeSolution Solve(MaxTimeProblem problem)
{
MaxTimeCalculator calculator = new MaxTimeCalculator(problem);
// get the seed customers.
ICollection <int> seeds = _seed_selector.SelectSeeds(
problem, _k);
double[] weights = new double[seeds.Count];
// start the seed routes.
List <int> selectable_customers = problem.Customers;
MaxTimeSolution routes = new MaxTimeSolution(
problem.Size, true);
foreach (int seed in seeds)
{
routes.Add(seed);
selectable_customers.Remove(seed);
}
if (!routes.IsValid())
{
throw new Exception();
}
// keep a list of cheapest insertions.
IInsertionCosts costs = new BinaryHeapInsertionCosts();
// keep looping until all customers have been placed.
while (selectable_customers.Count > 0)
{
// try and place into every route.
CheapestInsertionResult best_result = new CheapestInsertionResult();
best_result.Increase = float.MaxValue;
int best_route_idx = -1;
CheapestInsertionResult best_result_above_max = new CheapestInsertionResult();
best_result_above_max.Increase = float.MaxValue;
int best_route_above_max_idx = -1;
for (int route_idx = 0; route_idx < routes.Count; route_idx++)
{
IRoute current_route = routes.Route(route_idx);
// choose the next customer.
CheapestInsertionResult result =
CheapestInsertionHelper.CalculateBestPlacement(problem, current_route, selectable_customers, costs);
if (result.Customer == result.CustomerAfter)
{
throw new Exception();
}
// get the current weight
double weight = weights[route_idx];
if (result.Increase < best_result.Increase)
{
if (weight + result.Increase + calculator.DeliveryTime < problem.Max.Value)
{ // route will still be inside bounds.
best_result = result;
best_route_idx = route_idx;
}
else
{ // route will become above max.
if (result.Increase < best_result_above_max.Increase)
{
best_result_above_max = result;
best_route_above_max_idx = route_idx;
}
}
}
}
// do the placement if a placement is found without max violation.
// else do the placement in the above max route.
CheapestInsertionResult placement_result = new CheapestInsertionResult();
placement_result.Increase = double.MaxValue;
int placement_result_idx = -1;
if (best_route_idx >= 0)
{ // best placement found.
placement_result = best_result;
placement_result_idx = best_route_idx;
}
else
{ // best placement found but only above max.
placement_result = best_result_above_max;
placement_result_idx = best_route_above_max_idx;
}
// do the actual placement.
weights[placement_result_idx] = calculator.CalculateOneRouteIncrease(
weights[placement_result_idx], placement_result.Increase);
selectable_customers.Remove(placement_result.Customer);
//routes.Route(placement_result_idx).InsertAfterAndRemove(
// placement_result.CustomerBefore, placement_result.Customer, placement_result.CustomerAfter);
routes.Route(placement_result_idx).InsertAfter(
placement_result.CustomerBefore, placement_result.Customer);
if (!routes.IsValid())
{
throw new Exception();
}
}
return(routes);
}
/// <summary>
/// Returns a solution found using best-placement.
/// </summary>
/// <returns></returns>
protected override IRoute DoSolve(IProblem problem)
{
// build the customer list to place.
List <int> customers = null;
if (_customers != null)
{ // copy the list of the given customers and keep this order.
customers = new List <int>(_customers);
}
else
{ // generate some random route.
customers = new List <int>();
List <int> customers_to_place = new List <int>();
for (int customer = 0; customer < problem.Size; customer++)
{
customers_to_place.Add(customer);
}
while (customers_to_place.Count > 0)
{
int idx = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(customers_to_place.Count);
customers.Add(customers_to_place[idx]);
customers_to_place.RemoveAt(idx);
}
}
// initialize the route based on the problem definition.
IRoute route = null;
double weight = double.MaxValue;
if (problem.Symmetric)
{ // create a symmetric route that is dynamic and can accept new customers.
if (problem.First.HasValue && problem.Last.HasValue && problem.First == problem.Last)
{ // route is a round.
route = new DynamicSymmetricRoute(problem.First.Value);
}
else
{ // not a round.
throw new NotImplementedException("No symmetric routes implemented that are not rounds!");
}
}
else
{ // create a asymmetric route that is dynamic and can accept new customers.
if (problem.First.HasValue)
{ // the first customer is set.
// test if the last customer is the same.
if (!problem.Last.HasValue ||
problem.Last == problem.First)
{ // the route is a round.
route = new DynamicAsymmetricRoute(customers.Count, problem.First.Value, true);
// remove the first customer.
customers.Remove(problem.First.Value);
}
else
{ // the route is not a round.
route = new DynamicAsymmetricRoute(customers.Count, problem.First.Value, false);
route.InsertAfter(problem.First.Value, problem.Last.Value);
// remove the first customer.
customers.Remove(problem.First.Value);
customers.Remove(problem.Last.Value);
}
}
else
{ // the first and last customer can be choosen randomly.
// find two customers close together.
int from = -1;
int to = -1;
for (int x = 0; x < customers.Count; x++)
{
for (int y = 0; y < customers.Count; y++)
{
if (x != y)
{ // only different customers.
double current_weight = problem.WeightMatrix[x][y];
if (current_weight < weight)
{ // the current weight is better.
from = x;
to = y;
weight = current_weight;
if (weight == 0)
{ // no edge with less weight is going to be found.
break;
}
}
}
}
}
route = new DynamicAsymmetricRoute(customers.Count, from, false);
route.InsertAfter(from, to);
// remove the first customer.
customers.Remove(from);
customers.Remove(to);
}
}
// insert the rest of the customers.
while (customers.Count > 0 && !_stopped)
{ // keep placing customer 0 until all customers are placed.
// calculate placement.
CheapestInsertionResult result =
CheapestInsertionHelper.CalculateBestPlacement(problem, route, customers);
// place the customer.
if (result.CustomerAfter >= 0 && result.CustomerBefore >= 0)
{
//route.InsertAfterAndRemove(result.CustomerBefore, result.Customer, result.CustomerAfter);
route.InsertAfter(result.CustomerBefore, result.Customer);
customers.Remove(result.Customer);
}
}
return(route);
}
/// <summary>
/// Executes a solver procedure.
/// </summary>
/// <param name="problem"></param>
/// <returns></returns>
internal override MaxTimeSolution Solve(MaxTimeProblem problem)
{
// create the solution.
MaxTimeSolution solution = new MaxTimeSolution(problem.Size, true);
// keep placing customer until none are left.
List <int> customers = new List <int>(problem.Customers);
double max = problem.Max.Value - (problem.Max.Value * _delta_percentage);
// keep a list of cheapest insertions.
IInsertionCosts costs = new BinaryHeapInsertionCosts();
double percentage = _threshold_percentage;
while (customers.Count > 0)
{
// try and distribute the remaining customers if there are only a few left.
if (customers.Count < problem.Size * percentage)
{
bool succes = true;
while (succes && customers.Count > 0)
{
succes = false;
CheapestInsertionResult best = new CheapestInsertionResult();
best.Increase = float.MaxValue;
int best_idx = -1;
for (int route_idx = 0; route_idx < solution.Count; route_idx++)
{
IRoute route = solution.Route(route_idx);
CheapestInsertionResult result =
CheapestInsertionHelper.CalculateBestPlacement(problem, route, customers);
if (best.Increase > result.Increase)
{
best = result;
best_idx = route_idx;
}
}
IRoute best_route = solution.Route(best_idx);
double route_time = problem.Time(best_route);
if (route_time + best.Increase < max)
{ // insert the customer.
best_route.InsertAfter(best.CustomerBefore, best.Customer);
customers.Remove(best.Customer);
this.Improve(problem, solution, max, best_idx);
succes = true;
}
}
}
// select a customer using some heuristic.
if (customers.Count > 0)
{
// select a customer using some heuristic.
int customer = -1;
if (_use_seed)
{ // use a seeding heuristic.
customer = this.SelectSeed(problem, problem.MaxTimeCalculator, solution, customers);
}
else
{ // just select a random customer.
customer = customers[Math.Random.StaticRandomGenerator.Get().Generate(customers.Count)];
}
customers.Remove(customer);
// start a route r.
IRoute current_route = solution.Add(customer);
solution[solution.Count - 1] = 0;
while (customers.Count > 0)
{
//OsmSharp.IO.Output.OutputStreamHost.WriteLine("{0}/{1} placed!",
// customers.Count, problem.Size);
// calculate the best placement.
CheapestInsertionResult result;
if (_use_seed_cost)
{ // use the seed cost; the cost to the seed customer.
result = CheapestInsertionHelper.CalculateBestPlacement(problem, current_route, customers,
customer, _lambda);
// calculate the 'real' increase.
result.Increase = (problem.WeightMatrix[result.CustomerBefore][result.Customer] +
problem.WeightMatrix[result.Customer][result.CustomerAfter]) -
problem.WeightMatrix[result.CustomerBefore][result.CustomerAfter];
}
else
{ // just use cheapest insertion.
result = CheapestInsertionHelper.CalculateBestPlacement(problem, current_route, customers, costs);
}
// calculate the new weight.
solution[solution.Count - 1] = problem.Time(solution.Route(solution.Count - 1));
double potential_weight = problem.MaxTimeCalculator.CalculateOneRouteIncrease(solution[solution.Count - 1],
result.Increase);
// cram as many customers into one route as possible.
if (potential_weight < max)
{
// insert the customer, it is
customers.Remove(result.Customer);
current_route.InsertAfter(result.CustomerBefore, result.Customer);
// free some memory in the costs list.
costs.Remove(result.CustomerBefore, result.CustomerAfter);
// update the cost of the route.
solution[solution.Count - 1] = potential_weight;
// improve if needed.
if (((problem.Size - customers.Count) % _k) == 0)
{ // an improvement is descided.
// apply the inter-route improvements.
int count_before = solution.Route(solution.Count - 1).Count;
solution[solution.Count - 1] = this.ImproveIntraRoute(problem,
current_route, solution[solution.Count - 1]);
if (!solution.IsValid())
{
throw new Exception();
}
int count_after = solution.Route(solution.Count - 1).Count;
// also to the inter-improvements.
current_route = this.Improve(problem, solution, max, solution.Count - 1);
}
}
else
{// ok we are done!
this.Improve(problem, solution, max, solution.Count - 1);
// break the route.
break;
}
}
//else
//{// ok we are done!
// solution[solution.Count - 1] = this.ImproveIntraRoute(problem,
// current_route, solution[solution.Count - 1]);
// if (!solution.IsValid())
// {
// throw new Exception();
// }
// int count_after = solution.Route(solution.Count - 1).Count;
// this.Improve(problem, solution, max, solution.Count - 1);
// // break the route.
// break;
//}
}
}
// remove empty routes.
for (int route_idx = solution.Count - 1; route_idx >= 0; route_idx--)
{
if (solution.Route(route_idx).IsEmpty)
{
solution.Remove(route_idx);
}
}
return(solution);
}
/// <summary>
/// Executes the RAI.
/// </summary>
/// <param name="problem"></param>
/// <param name="solver"></param>
/// <param name="initial_route"></param>
/// <returns></returns>
private static IRoute DoSolve(RandomizedArbitraryInsertionSolver solver, IProblem problem, IRoute initial_route)
{
// initialize a route using best-placement.
DynamicAsymmetricRoute route = null;
if (initial_route == null)
{
OsmSharp.Math.TSP.ArbitraryInsertion.ArbitraryInsertionSolver ai_solver =
new OsmSharp.Math.TSP.ArbitraryInsertion.ArbitraryInsertionSolver();
initial_route = ai_solver.Solve(problem);
}
// get/create the dynamic route.
if (initial_route is DynamicAsymmetricRoute)
{ // initial route is already the correct type.
route = initial_route as DynamicAsymmetricRoute;
}
else
{ // convert the initial route to a route of the correct type.
route = DynamicAsymmetricRoute.CreateFrom(initial_route);
}
// do the Arbitrary Insertion.
double weight = route.CalculateWeight(problem);
int try_count = 0;
while (try_count < (route.Count * route.Count))
{ // keep trying for a given number of times.
int factor = 2;
// cut out a part.
int i = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate((route.Count / factor) - 1) + 1;
int j = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate((route.Count / factor) - 1) + 1;
while (i == j)
{
j = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate((route.Count / factor) - 1) + 1;
}
if (i > j)
{
int k = j;
j = i;
i = k;
}
// cut out the i->j part.
int length = j - i;
if (length > 0)
{
// cut and remove.
DynamicAsymmetricRoute.CutResult cut_result = route.CutAndRemove(
problem, weight, i, length);
// calculate the weight that was removed.
double new_weight = cut_result.Weight;
List <int> cut_part = cut_result.CutPart;
DynamicAsymmetricRoute cut_route = cut_result.Route;
// use best placement to re-insert.
int c = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(cut_part.Count);
while (cut_part.Count > 0)
{ // loop until it's empty.
int customer = cut_part[c];
cut_part.RemoveAt(c);
// calculate the best placement.
CheapestInsertionResult result = CheapestInsertionHelper.CalculateBestPlacement(
problem, cut_route, customer);
//cut_route.InsertAfterAndRemove(result.CustomerBefore, result.Customer, result.CustomerAfter);
cut_route.InsertAfter(result.CustomerBefore, result.Customer);
new_weight = new_weight + result.Increase;
// choose next random customer.
c = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(cut_part.Count);
}
// descide to keep new route or not.
if (weight > new_weight)
{
route = cut_route;
weight = new_weight;
//if (this.CanRaiseIntermidiateResult())
//{
// this.RaiseIntermidiateResult(route.ToArray<int>(), weight);
//}
}
}
// increase the try count.
try_count++;
}
if (solver != null && solver.CanRaiseIntermidiateResult())
{
solver.RaiseIntermidiateResult(route.ToArray <int>());
}
return(route);
}
/// <summary>
/// Does the mutation.
/// </summary>
/// <param name="solver"></param>
/// <param name="mutating"></param>
/// <returns></returns>
public Individual <MaxTimeSolution, MaxTimeProblem, Fitness> Mutate(
Solver <MaxTimeSolution, MaxTimeProblem, Fitness> solver,
Individual <MaxTimeSolution, MaxTimeProblem, Fitness> mutating)
{
// get the route information.
MaxTimeSolution multi_route = mutating.Genomes.Clone() as MaxTimeSolution;
if (multi_route.Count > 1)
{ // TODO: Maybe add some extra code for the the route-count is very low and chances of collisions are big.
// TODO: investigate what is more expensive, and extra random generation or creating a list and remove items.
// http://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle
// select a route.
int source_route_idx = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(multi_route.Count);
int target_route_idx = -1;
do
{
target_route_idx = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(multi_route.Count);
} while (source_route_idx == target_route_idx);
int source_count = multi_route.Sizes[source_route_idx];
int target_count = multi_route.Sizes[target_route_idx];
if (target_count > 0 && source_count > 3)
{
// take a part out of the orginal.
int size = (int)OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(source_count);
int source_location = OsmSharp.Math.Random.StaticRandomGenerator.Get().Generate(source_count);
int first = source_location - (size / 2);
if (first < 0)
{
first = 0;
}
//first = multi_route.StartOf(source_route_idx) + first;
int last = source_location + (size / 2);
if (last > source_count - 1)
{
last = source_count - 1;
}
//last = multi_route.StartOf(source_route_idx) + last;
int idx = -1;
IRoute source = multi_route.Route(source_route_idx);
List <int> part_of_orginal = new List <int>();
foreach (int customer in source)
{
idx++;
if (idx >= first && idx <= last)
{
part_of_orginal.Add(customer);
}
}
// remove from the source.
foreach (int customer in part_of_orginal)
{
multi_route.RemoveCustomer(customer);
}
// place it somewhere in the target.
if (part_of_orginal.Count > 0)
{
IRoute target = multi_route.Route(target_route_idx);
CheapestInsertionResult route_placement = CheapestInsertionHelper.CalculateBestPlacement(
solver.Problem, target, part_of_orginal[0], part_of_orginal[part_of_orginal.Count - 1]);
int from = route_placement.CustomerBefore;
foreach (int customer in part_of_orginal)
{
target.InsertAfter(from, customer);
//target.InsertAfterAndRemove(from, customer, -1);
from = customer;
}
}
}
}
return(new Individual <MaxTimeSolution, MaxTimeProblem, Fitness>(multi_route));
}
