public void ExecuteMetaheuristic(ref Solution bestSolution)
{
ShiftInter = 0;
IntraRouteInsertionOP = 0;
WRI_IntraOP = 0;
IntraSwap = 0;
Debug.WriteLine("\n\nNueva búsuqeda: ");
bool ls1 = true;
bool ls2 = true;
bool ls3 = true;
bool ls4 = true;
while (ls1 || ls2 || ls3 || ls4)
{
List <int> localInternal = Enumerable.Range(0, 3).ToList();
do
{
var variable = localInternal[_random.Next(0, localInternal.Count)];
switch (variable)
{
case 0:
ls1 = WRI_Intra(ref bestSolution);
localInternal.Remove(0);
break;
case 1:
ls3 = IntraRouteInsertion(ref bestSolution);
localInternal.Remove(1);
break;
case 2:
ls4 = Swap_Intra(ref bestSolution);
localInternal.Remove(2);
break;
}
}while (localInternal.Count > 0);
//ls4 = Swap_Intra(ref bestSolution);
//ls1 = WRI_Intra(ref bestSolution);
ls2 = Shift1_0Inter(ref bestSolution);
//ls3 = IntraRouteInsertion(ref bestSolution);
//ls1 = false;
//ls2 = false;
//ls3 = false;
//ls4 = false;
}
DARPAlgorithms.UpdateConstraintsSolution(ref bestSolution, _problem);
CheckFesiability(ref bestSolution);
}
public static List <Solution> Optimization(RunMetaheuristicInput input)
{
var problems = input.Problems;
//Set randomized value.
_random = input.Random;
List <Solution> Solutions = new List <Solution>();
var default_Metaheuristic = Constants.TypeMetaheuristics.ILS;
IMetaheuristic metaheuristic = MetaheuristicFactory.CreateMetaheuristic(default_Metaheuristic, input.HeuristicSettings, input.Problems.First(), input.Random);
//Ejecutar cada problema.
foreach (var problem in problems)
{
//Primer paso. Preprocesar los problemas (ajustar ventanas de tiempo cuando sea posible).
SplashGlobalData.SetSplashData(Constants.SPLASH_NAME_PROBLEM, problem.ID_Problem);
SplashGlobalData.SetSplashData(Constants.SPLASH_PROGRESS, 0.0);
//Create Solution
for (int number_Repetition = 0; number_Repetition < input.HeuristicSettings.MaxRepetitions; number_Repetition++)
{
var watch = System.Diagnostics.Stopwatch.StartNew();
Solution solution = new Solution(problem.ID_Problem);
DARPAlgorithms.BuildInitialSolution(ref solution, problem, ref _random);
solution.InitialSolution = GenericCopier <Solution> .DeepCopy(solution);
//Update Splash.
SplashGlobalData.SetSplashData(Constants.SPLASH_NUMBER_REPETITION, number_Repetition + 1);
SplashGlobalData.SetSplashData(Constants.SPLASH_PROGRESS, Convert.ToDouble(SplashGlobalData.GetSplashData <double>(Constants.SPLASH_PROGRESS)) + 1);
//Execute Heuristic
metaheuristic.ExecuteMetaheuristic(ref solution);
watch.Stop();
solution.ExecutionTime = watch.ElapsedMilliseconds;
Solutions.Add(solution);
//Validation.Validator.ValidateSolution(ref solution, problem);
}
}
return(Solutions);
}
public void ExecuteMetaheuristic(ref Solution bestSolution)
{
int bestIteration = 0;
Solution partialSolution = GenericCopier <Solution> .DeepCopy(bestSolution);
int control_Diversify = 0;
SummaryDetails summary = new SummaryDetails();
Splash.SplashGlobalData.SetSplashData(Constants.SPLASH_BEST_SOLUTION, bestSolution.Fitness);
double pertCost = 0, vnsCost = 0;
int iterations = 0;
//Guardar coste inicial.
summary.ILSSummary.InitCost = bestSolution.Parc_Cost;
for (int i = 0; iterations < _ilsSettings.MaxILSIterations && i < _ilsSettings.MaxILSNoImprovement; i++)
{
//Control de intensificación-diversificación.
if (i % _DIVERSIFY_MAX == 0)
{
_diversify--;
}
_diversify = _diversify < 3 ? 3 : _diversify;
if (i % 100 == 0)
{
_diversify = _DIVERSIFY_MAX;
}
//Guardar valores estadísticos.
var initCost = partialSolution.Parc_Cost;
var initFitness = partialSolution.Fitness;
Splash.SplashGlobalData.SetSplashData(Constants.SPLASH_ILS_TOTAL_ITERATIONS, iterations + 1);
//Apply VNS local search.
_vns.ExecuteMetaheuristic(ref partialSolution);
//Validator.ValidateSolution(ref partialSolution, _problem);
bool feasible = partialSolution.Feasible;
//Guardar valores estadísticos.
vnsCost = Costs.ParcialCostSolution(partialSolution, _problem); // partialSolution.Parc_Cost;
var vnsFitness = partialSolution.Fitness;
if (vnsFitness < initFitness)
{
summary.ILSSummary.TotalImpPrevious++; //Incrementar el número de veces que se mejora la solución previa (perturbada).
}
if (bestSolution.Feasible)
{
if (partialSolution.Feasible && (Math.Round(partialSolution.Fitness, 2) < Math.Round(bestSolution.Fitness, 2)))
{
bestSolution = GenericCopier <Solution> .DeepCopy(partialSolution);
//Actualizar la mejor solución con los nuevos parámetros.
control_Diversify = 0;
bestIteration = i;
i = 0;
_diversify = _DIVERSIFY_MAX;
summary.ILSSummary.BestIteration = iterations + 1; //Guardar mejor iteración encontrada.
summary.ILSSummary.TotalImpBest++; //Incrementar el número de veces que se mejora la mejor solución.
Singleton.Instance.UpdatePenaltyTerms(partialSolution);
Splash.SplashGlobalData.SetSplashData(Constants.SPLASH_ILS_IMPROVEMENTS, summary.ILSSummary.TotalImpBest);
Splash.SplashGlobalData.SetSplashData(Constants.SPLASH_BEST_SOLUTION, Math.Round(bestSolution.Fitness, 2));
}
else
{
control_Diversify++;
}
}
else
{
if (partialSolution.Feasible || Math.Round(partialSolution.Fitness, 2) < Math.Round(bestSolution.Fitness, 2))
{
if (partialSolution.Feasible && summary.ILSSummary.FirstItFeasible == null)
{
summary.ILSSummary.FirstItFeasible = iterations + 1; //Guardar primera iteración factible.
}
bestSolution = GenericCopier <Solution> .DeepCopy(partialSolution);
control_Diversify = 0;
i = 0;
_diversify = _DIVERSIFY_MAX;
summary.ILSSummary.BestIteration = iterations + 1; //Guardar mejor iteración encontrada.
summary.ILSSummary.TotalImpBest++; //Incrementar el número de veces que se mejora la mejor solución.
Singleton.Instance.UpdatePenaltyTerms(partialSolution);
//bestSolution.Fitness = Costs.EvaluationSolution(bestSolution, _problem);
Splash.SplashGlobalData.SetSplashData(Constants.SPLASH_ILS_IMPROVEMENTS, summary.ILSSummary.TotalImpBest);
Splash.SplashGlobalData.SetSplashData(Constants.SPLASH_BEST_SOLUTION, bestSolution.Fitness);
}
else
{
control_Diversify++;
}
}
if (control_Diversify > _diversify)
{
partialSolution = GenericCopier <Solution> .DeepCopy(bestSolution);
control_Diversify = 0;
}
var perturbation = _perturbations.ExecutePerturbation(ref partialSolution);
//Guardar valores estadísticos.
pertCost = partialSolution.Parc_Cost;
var pertFitness = partialSolution.Fitness;
//Añadir resumen de la iteración.
summary.VNSOperators.Add(new VNSOperators(iterations, _vns.ShiftInter, 0, _vns.WRI_IntraOP, _vns.IntraRouteInsertionOP, _vns.IntraSwap));
summary.ILSEvolution.Add(new ILSEvolution(iterations, Math.Round(initCost, 2), Math.Round(initFitness, 2), Math.Round(vnsCost, 2), Math.Round(vnsFitness, 2), perturbation, Math.Round(pertFitness, 2), Math.Round(pertCost, 2), feasible));
Splash.SplashGlobalData.SetSplashData(Constants.SPLASH_PROGRESS, Convert.ToDouble(Splash.SplashGlobalData.GetSplashData <double>(Constants.SPLASH_PROGRESS)) + _coef_Updater_Splash);
//Guardar cambios de cada operador.
iterations++;
}
//Recalcular con el proceso de 8 pasos y actualizar el coste.
foreach (var vehicle in bestSolution.Vehicles)
{
DARPAlgorithms.EightStepsEvaluationProcedure(ref bestSolution, vehicle, _problem);
}
bestSolution.TotalDuration = bestSolution.Vehicles.Sum(t => t.VehicleDuration);
bestSolution.TimeWindowViolation = bestSolution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
bestSolution.RideTimeViolation = bestSolution.Vehicles.Sum(r => r.TotalRideTimeViolation);
bestSolution.DurationViolation = bestSolution.Vehicles.Sum(d => d.TotalDurationViolation);
bestSolution.LoadViolation = bestSolution.Vehicles.Sum(l => l.TotalLoadViolation);
bestSolution.TotalWaitingTime = bestSolution.Vehicles.Sum(t => t.TotalWaitingTime);
DARPAlgorithms.UpdateConstraintsSolution(ref bestSolution, _problem);
bestSolution.Fitness = Costs.EvaluationSolution(bestSolution, _problem);
bestSolution.Parc_Cost = Costs.ParcialCostSolution(bestSolution, _problem);
summary.ILSSummary.TotalIterations = iterations + 1;
summary.ILSSummary.FinalCost = bestSolution.Parc_Cost;
bestSolution.SummaryDetails = summary;
}
private void ShiftPerturbation(ref Solution solution)
{
int v1 = -1, v2 = -1;
//marcar todos los vehículos como no perturbados.
solution.Vehicles = solution.Vehicles.Select(t => { t.Perturbed = true; return(t); }).ToList();
//Recorrer todos los vehículos
//for (int v = 0; v < solution.Vehicles.Count; v++)
//{
//Seleccionar el primer vehículo.
do
{
v1 = _random.Next(0, PerturbationMechanism.Keys.Count);
}while (solution.Vehicles[v1].Requests.Count <= 4);
if (PerturbationMechanism[v1].Count == 0)
{
ResetPerturbationMechanism(false, v1);
}
do
{
v2 = PerturbationMechanism[v1][_random.Next(0, PerturbationMechanism[v1].Count)];
}while (v1 == v2);
//Seleccionar aleatoriamente un cliente de v1.
List <Request> nodes = new List <Request>();
var node = solution.Vehicles[v1].Requests[_random.Next(1, solution.Vehicles[v1].Requests.Count - 1)];
nodes = solution.Vehicles[v1].Requests.FindAll(t => t.PairID.Equals(node.PairID)); //Extraemos inicio y destino.
//Siguiente paso. Insertarlos en su mejor posición posible.
var origin = nodes.Find(t => t.Origin == true);
int posOrigin = solution.Vehicles[v1].Requests.IndexOf(origin);
var destination = nodes.Find(t => t.Origin == false);
int posDestination = solution.Vehicles[v1].Requests.IndexOf(destination);
if (solution.Vehicles[v2].Requests.Count == 2)
{
solution.Vehicles[v2].Requests.Insert(1, destination);
solution.Vehicles[v2].Requests.Insert(1, origin);
}
else
{
solution.Vehicles[v1].Requests.RemoveAll(t => t.PairID.Equals(nodes.First().PairID)); //Los eliminamos de su ruta inicio.
//Determinamos nodo crítico (será el primero a insertar).
Request critical;
Request notCritical;
if (origin.IsCritical)
{
critical = origin;
notCritical = destination;
}
else
{
critical = destination;
notCritical = origin;
}
//Seleccionar posiciones en el vehículo v2
Dictionary <int, int> bestPair = new Dictionary <int, int>();
int bestPosSource = -1;
double min = double.MaxValue;
for (int pos = 1; pos < solution.Vehicles[v2].Requests.Count; pos++)
{
double twDist = 0.0;
if (pos == 1)
{
if ((critical.TimeWindow.LowerBound + _problem.Distances[critical.ID_Unique][solution.Vehicles[v2].Requests[pos].ID_Unique]) > solution.Vehicles[v2].Requests[pos].TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(critical, v2, pos, solution);
}
else if (pos == solution.Vehicles[v2].Requests.Count - 1)
{
if ((solution.Vehicles[v2].Requests[pos].TimeWindow.LowerBound + _problem.Distances[critical.ID_Unique][solution.Vehicles[v2].Requests[pos].ID_Unique]) > critical.TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(critical, v2, pos - 1, solution);
}
else
{
if (((solution.Vehicles[v2].Requests[pos - 1].TimeWindow.LowerBound + _problem.Distances[critical.ID_Unique][solution.Vehicles[v2].Requests[pos - 1].ID_Unique]) > critical.TimeWindow.UpperBound) ||
(critical.TimeWindow.LowerBound + _problem.Distances[critical.ID_Unique][solution.Vehicles[v2].Requests[pos].ID_Unique]) > solution.Vehicles[v2].Requests[pos].TimeWindow.UpperBound)
{
continue;
}
twDist = (CalculateDistance(critical, v2, pos, solution) + CalculateDistance(critical, v2, pos - 1, solution)) / 2.0;
}
if (twDist < min)
{
bestPosSource = pos;
min = twDist;
}
}
if (bestPosSource == -1) //Insertar en pos = 1;
{
bestPosSource = 1;
}
solution.Vehicles[v2].Requests.Insert(bestPosSource, critical);
int notCriticalPos = -1;
min = double.MaxValue;
//Insertar no crítico.
if (critical.Origin)
{
//De pos en adelante.
for (int init = bestPosSource + 1; init < solution.Vehicles[v2].Requests.Count; init++)
{
if ((solution.Vehicles[v2].Requests[init - 1].TimeWindow.LowerBound + _problem.Distances[solution.Vehicles[v2].Requests[init - 1].ID_Unique][notCritical.ID_Unique]) > notCritical.TimeWindow.UpperBound)
{
continue;
}
double twDist = 0.0;
if (init == solution.Vehicles[v2].Requests.Count)
{
if ((solution.Vehicles[v2].Requests[init - 1].TimeWindow.LowerBound + _problem.Distances[critical.ID_Unique][solution.Vehicles[v2].Requests[init - 1].ID_Unique]) > critical.TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(critical, v2, init - 1, solution);
}
else
{
if (((solution.Vehicles[v2].Requests[init - 1].TimeWindow.LowerBound + _problem.Distances[critical.ID_Unique][solution.Vehicles[v2].Requests[init - 1].ID_Unique]) > critical.TimeWindow.UpperBound) ||
(critical.TimeWindow.LowerBound + _problem.Distances[critical.ID_Unique][solution.Vehicles[v2].Requests[init].ID_Unique]) > solution.Vehicles[v2].Requests[init].TimeWindow.UpperBound)
{
continue;
}
twDist = (CalculateDistance(critical, v2, init, solution) + CalculateDistance(critical, v2, init - 1, solution)) / 2.0;
}
//var diff = Problem.EuclideanDistance(notCritical.TimeWindow.LowerBound, notCritical.TimeWindow.UpperBound, solution.Vehicles[v2].Requests[init - 1].TimeWindow.LowerBound, solution.Vehicles[v2].Requests[init - 1].TimeWindow.UpperBound);
if (twDist < min)
{
notCriticalPos = init;
min = twDist;
}
}
}
else
{
//De pos hacia atrás.
for (int init = bestPosSource; init > 0; init--)
{
if ((notCritical.TimeWindow.LowerBound + _problem.Distances[notCritical.ID_Unique][solution.Vehicles[v2].Requests[init].ID_Unique]) > solution.Vehicles[v2].Requests[init].TimeWindow.UpperBound)
{
continue;
}
//var diff = Problem.EuclideanDistance(notCritical.TimeWindow.LowerBound, notCritical.TimeWindow.UpperBound, solution.Vehicles[v2].Requests[init].TimeWindow.LowerBound, solution.Vehicles[v2].Requests[init].TimeWindow.UpperBound);
double twDist = 0.0;
if (init == 1)
{
if ((critical.TimeWindow.LowerBound + _problem.Distances[critical.ID_Unique][solution.Vehicles[v2].Requests[init].ID_Unique]) > solution.Vehicles[v2].Requests[init].TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(critical, v2, init, solution);
}
else
{
if (((solution.Vehicles[v2].Requests[init - 1].TimeWindow.LowerBound + _problem.Distances[critical.ID_Unique][solution.Vehicles[v2].Requests[init - 1].ID_Unique]) > critical.TimeWindow.UpperBound) ||
(critical.TimeWindow.LowerBound + _problem.Distances[critical.ID_Unique][solution.Vehicles[v2].Requests[init].ID_Unique]) > solution.Vehicles[v2].Requests[init].TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(critical, v2, init, solution);
}
if (twDist < min)
{
notCriticalPos = init;
min = twDist;
}
}
}
solution.Vehicles[v2].Requests.Insert(notCriticalPos, notCritical);
}
// }
//Recalcular con el proceso de 8 pasos y actualizar el coste.
foreach (var vehicle in solution.Vehicles)
{
DARPAlgorithms.EightStepsEvaluationProcedure(ref solution, vehicle, _problem);
}
solution.TotalDuration = solution.Vehicles.Sum(t => t.VehicleDuration);
solution.TimeWindowViolation = solution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
solution.RideTimeViolation = solution.Vehicles.Sum(r => r.TotalRideTimeViolation);
solution.DurationViolation = solution.Vehicles.Sum(d => d.TotalDurationViolation);
solution.LoadViolation = solution.Vehicles.Sum(l => l.TotalLoadViolation);
solution.TotalWaitingTime = solution.Vehicles.Sum(t => t.TotalWaitingTime);
DARPAlgorithms.UpdateConstraintsSolution(ref solution, _problem);
solution.Fitness = Costs.EvaluationSolution(solution, _problem);
try
{
Validator.Positions(ref solution, _problem);
Validation.Validator.ValidateSolution(ref solution, _problem);
}
catch (Exception ex)
{
Console.WriteLine();
}
}
private void ChainPerturbation(ref Solution solution)
{
try
{
//marcar todos los vehículos como no perturbados.
solution.Vehicles = solution.Vehicles.Select(t => { t.Perturbed = false; return(t); }).ToList();
//Seleccionar el primer vehículo.
int v1 = _random.Next(0, PerturbationMechanism.Keys.Count);
if (PerturbationMechanism[v1].Count == 0)
{
ResetPerturbationMechanism(false, v1);
}
int v2;
do
{
v2 = PerturbationMechanism[v1][_random.Next(0, PerturbationMechanism[v1].Count)];
}while (v1 == v2);
//routes.Remove(v2);
PerturbationMechanism[v1].Remove(v2);
PerturbationMechanism[v2].Remove(v1);
//Seleccionar el tamaño de la cadena
int maxSizeR1 = Math.Min(2, solution.Vehicles[v1].Requests.Count - 2);
int maxSizeR2 = Math.Min(2, solution.Vehicles[v2].Requests.Count - 2);
if (maxSizeR1 == 0)
{
maxSizeR1 = 1;
}
if (maxSizeR2 == 0)
{
maxSizeR2 = 1;
}
int size_R1 = _random.Next(1, maxSizeR1);
int size_R2 = _random.Next(1, maxSizeR2);
//Posición inicial desde la que coger elementos.
int init_PosR1 = _random.Next(1, solution.Vehicles[v1].Requests.Count - 1);
int init_PosR2 = _random.Next(1, solution.Vehicles[v2].Requests.Count - 1);
if (init_PosR1 <= 0)
{
init_PosR1 = 1;
}
if (init_PosR2 <= 0)
{
init_PosR2 = 1;
}
//Obtener los elementos seleccionados en cada rango.
var elementsR1 = solution.Vehicles[v1].Requests.GetRange(init_PosR1, size_R1);
var elementsR2 = solution.Vehicles[v2].Requests.GetRange(init_PosR2, size_R2);
foreach (var element in elementsR1)
{
solution.Vehicles[v1].Requests.RemoveAll(t => t.PairID == element.ID_Unique);
}
foreach (var element in elementsR2)
{
solution.Vehicles[v2].Requests.RemoveAll(t => t.PairID == element.ID_Unique);
}
//Marcar ambas rutas como perturbadas.
solution.Vehicles[v1].Perturbed = true;
solution.Vehicles[v2].Perturbed = true;
List <Node> chainR1ToR2 = new List <Node>();
List <Node> chainR2ToR1 = new List <Node>();
List <int> tabu = new List <int>();
foreach (var node in elementsR1)
{
if (tabu.Contains(node.PairID))
{
continue;
}
tabu.Add(node.PairID);
var secondNode = _problem.Requests.Find(t => t.PairID == node.PairID && t.Origin != node.Origin);
//solution.Vehicles[v1].Requests.RemoveAll(t => t.PairID.Equals(node.PairID)); //Eliminar el destino y el origen
Request criticalNode;
Request notCriticalNode;
if (node.IsCritical)
{
criticalNode = node;
notCriticalNode = secondNode;
}
else
{
criticalNode = secondNode;
notCriticalNode = node;
}
double min_Dif = double.MaxValue;
int bestCriticalPos = -1;
//Si el nodo actual es crítico, insertarlo en su primera posición válida respecto a TW.
for (int i = 1; i < solution.Vehicles[v2].Requests.Count; i++)
{
//if (!_problem.FeasibleTravel[solution.Vehicles[v2].Requests[i].ID_Unique][criticalNode.ID_Unique]) continue;
double twDist = 0.0;
if (i == 1)
{
if ((criticalNode.TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v2].Requests[i].ID_Unique]) > solution.Vehicles[v2].Requests[i].TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(criticalNode, v2, i, solution);
}
else if (i == solution.Vehicles[v2].Requests.Count - 1)
{
if ((solution.Vehicles[v2].Requests[i - 1].TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v2].Requests[i - 1].ID_Unique]) > criticalNode.TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(criticalNode, v2, i - 1, solution);
}
else
{
if (((solution.Vehicles[v2].Requests[i - 1].TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v2].Requests[i - 1].ID_Unique]) > criticalNode.TimeWindow.UpperBound) ||
(criticalNode.TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v2].Requests[i].ID_Unique]) > solution.Vehicles[v2].Requests[i].TimeWindow.UpperBound)
{
continue;
}
twDist = (CalculateDistance(criticalNode, v2, i, solution) + CalculateDistance(criticalNode, v2, i - 1, solution)) / 2.0;
}
if (twDist < min_Dif)
{
min_Dif = twDist;
bestCriticalPos = i;
}
}
if (bestCriticalPos == -1)
{
bestCriticalPos = 1;
solution.Vehicles[v2].Requests.Insert(1, criticalNode);
}
else
{
solution.Vehicles[v2].Requests.Insert(bestCriticalPos, criticalNode);
}
//La posición actual es válida para insertar el nodo crítico. Insertar el no crítico en su mejor posición
if (criticalNode.Origin)
{
double bestCost = double.PositiveInfinity;
int bestPos = bestCriticalPos + 1;
//Insertar el nodo no crítico después.
for (int j = bestCriticalPos + 1; j < solution.Vehicles[v2].Requests.Count; j++)
{
if (!_problem.FeasibleTravel[notCriticalNode.ID_Unique][solution.Vehicles[v2].Requests[j].ID_Unique])
{
continue;
}
//var diff = Problem.EuclideanDistance(notCriticalNode.TimeWindow.LowerBound, notCriticalNode.TimeWindow.UpperBound, solution.Vehicles[v2].Requests[j + 1].TimeWindow.LowerBound, solution.Vehicles[v2].Requests[j + 1].TimeWindow.UpperBound);
double twDist = 0.0;
if (j == solution.Vehicles[v2].Requests.Count - 1)
{
if ((solution.Vehicles[v2].Requests[j - 1].TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v2].Requests[j - 1].ID_Unique]) > criticalNode.TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(notCriticalNode, v2, j - 1, solution);
}
else
{
if (((solution.Vehicles[v2].Requests[j - 1].TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v2].Requests[j - 1].ID_Unique]) > criticalNode.TimeWindow.UpperBound) ||
(criticalNode.TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v2].Requests[j].ID_Unique]) > solution.Vehicles[v2].Requests[j].TimeWindow.UpperBound)
{
continue;
}
twDist = (CalculateDistance(notCriticalNode, v2, j, solution) + CalculateDistance(notCriticalNode, v2, j - 1, solution)) / 2.0;
}
if (twDist < bestCost)
{
bestPos = j;
bestCost = twDist;
}
}
//Insertar en la mejor posición declarada.
solution.Vehicles[v2].Requests.Insert(bestPos, notCriticalNode);
}
else //El nodo no crítico es el origen.
{
double bestCost = double.PositiveInfinity;
int bestPos = bestCriticalPos;
//Insertar el nodo no crítico después.
//Insertar el nodo no crítico antes.
for (int j = bestCriticalPos; j > 0; j--)
{
if (!_problem.FeasibleTravel[solution.Vehicles[v2].Requests[j - 1].ID_Unique][notCriticalNode.ID_Unique])
{
continue;
}
//var diff = Problem.EuclideanDistance(notCriticalNode.TimeWindow.LowerBound, notCriticalNode.TimeWindow.UpperBound, solution.Vehicles[v2].Requests[j + 1].TimeWindow.LowerBound, solution.Vehicles[v2].Requests[j + 1].TimeWindow.UpperBound);
double twDist = 0.0;
if (j == 1)
{
if ((criticalNode.TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v2].Requests[j].ID_Unique]) > solution.Vehicles[v2].Requests[j].TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(notCriticalNode, v2, j, solution);
}
else
{
if (((solution.Vehicles[v2].Requests[j - 1].TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v2].Requests[j - 1].ID_Unique]) > criticalNode.TimeWindow.UpperBound) ||
(criticalNode.TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v2].Requests[j].ID_Unique]) > solution.Vehicles[v2].Requests[j].TimeWindow.UpperBound)
{
continue;
}
twDist = (CalculateDistance(notCriticalNode, v2, j, solution) + CalculateDistance(notCriticalNode, v2, j - 1, solution)) / 2.0;
}
if (twDist < bestCost)
{
bestPos = j;
bestCost = twDist;
}
}
//Insertar en la mejor posición declarada.
solution.Vehicles[v2].Requests.Insert(bestPos, notCriticalNode);
//break; //terminamos.
}
}
//Mismo proceso para los elementos de R2.
tabu.Clear();
foreach (var node in elementsR2)
{
if (tabu.Contains(node.PairID))
{
continue;
}
tabu.Add(node.PairID);
var secondNode = _problem.Requests.Find(t => t.PairID == node.PairID && t.Origin != node.Origin); //solution.Vehicles[v2].Requests.Find(t => t.PairID == node.PairID && t.Origin != node.Origin);
//solution.Vehicles[v2].Requests.RemoveAll(t => t.PairID.Equals(node.PairID)); //Eliminar el destino y el origen
Request criticalNode;
Request notCriticalNode;
if (node.IsCritical)
{
criticalNode = node;
notCriticalNode = secondNode;
}
else
{
criticalNode = secondNode;
notCriticalNode = node;
}
double min_Dif = double.MaxValue;
int bestCriticalPos = -1;
//Si el nodo actual es crítico, insertarlo en su primera posición válida respecto a TW.
for (int i = 1; i < solution.Vehicles[v1].Requests.Count; i++)
{
double twDist = 0.0;
if (i == 1)
{
if ((criticalNode.TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v1].Requests[i].ID_Unique]) > solution.Vehicles[v1].Requests[i].TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(criticalNode, v1, i, solution);
}
else if (i == solution.Vehicles[v1].Requests.Count - 1)
{
if ((solution.Vehicles[v1].Requests[i - 1].TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v1].Requests[i - 1].ID_Unique]) > criticalNode.TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(criticalNode, v1, i - 1, solution);
}
else
{
if (((solution.Vehicles[v1].Requests[i - 1].TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v1].Requests[i - 1].ID_Unique]) > criticalNode.TimeWindow.UpperBound) ||
(criticalNode.TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v1].Requests[i].ID_Unique]) > solution.Vehicles[v1].Requests[i].TimeWindow.UpperBound)
{
continue;
}
twDist = (CalculateDistance(criticalNode, v1, i, solution) + CalculateDistance(criticalNode, v1, i - 1, solution)) / 2.0;
}
if (twDist < min_Dif)
{
min_Dif = twDist;
bestCriticalPos = i;
}
}
if (bestCriticalPos == -1)
{
bestCriticalPos = 1;
solution.Vehicles[v1].Requests.Insert(1, criticalNode);
}
else
{
solution.Vehicles[v1].Requests.Insert(bestCriticalPos, criticalNode);
}
//La posición actual es válida para insertar el nodo crítico. Insertar el no crítico en su mejor posición
if (criticalNode.Origin)
{
double bestCost = double.PositiveInfinity;
int bestPos = bestCriticalPos + 1;
//Insertar el nodo no crítico después.
for (int j = bestCriticalPos + 1; j < solution.Vehicles[v1].Requests.Count; j++)
{
if (!_problem.FeasibleTravel[notCriticalNode.ID_Unique][solution.Vehicles[v1].Requests[j].ID_Unique])
{
continue;
}
//var diff = Problem.EuclideanDistance(notCriticalNode.TimeWindow.LowerBound, notCriticalNode.TimeWindow.UpperBound, solution.Vehicles[v2].Requests[j + 1].TimeWindow.LowerBound, solution.Vehicles[v2].Requests[j + 1].TimeWindow.UpperBound);
double twDist = 0.0;
if (j == solution.Vehicles[v1].Requests.Count - 1)
{
if ((solution.Vehicles[v1].Requests[j - 1].TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v1].Requests[j - 1].ID_Unique]) > criticalNode.TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(notCriticalNode, v1, j - 1, solution);
}
else
{
if (((solution.Vehicles[v1].Requests[j - 1].TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v1].Requests[j - 1].ID_Unique]) > criticalNode.TimeWindow.UpperBound) ||
(criticalNode.TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v1].Requests[j].ID_Unique]) > solution.Vehicles[v1].Requests[j].TimeWindow.UpperBound)
{
continue;
}
twDist = (CalculateDistance(notCriticalNode, v1, j, solution) + CalculateDistance(notCriticalNode, v1, j - 1, solution)) / 2.0;
}
if (twDist < bestCost)
{
bestPos = j;
bestCost = twDist;
}
}
//Insertar en la mejor posición declarada.
solution.Vehicles[v1].Requests.Insert(bestPos, notCriticalNode);
//break; //terminamos.
}
else //El nodo no crítico es el origen.
{
double bestCost = double.PositiveInfinity;
int bestPos = bestCriticalPos;
//Insertar el nodo no crítico después.
//Insertar el nodo no crítico antes.
for (int j = bestCriticalPos; j > 0; j--)
{
if (!_problem.FeasibleTravel[solution.Vehicles[v1].Requests[j - 1].ID_Unique][notCriticalNode.ID_Unique])
{
continue;
}
//var diff = Problem.EuclideanDistance(notCriticalNode.TimeWindow.LowerBound, notCriticalNode.TimeWindow.UpperBound, solution.Vehicles[v2].Requests[j + 1].TimeWindow.LowerBound, solution.Vehicles[v2].Requests[j + 1].TimeWindow.UpperBound);
double twDist = 0.0;
if (j == 1)
{
if ((criticalNode.TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v1].Requests[j].ID_Unique]) > solution.Vehicles[v1].Requests[j].TimeWindow.UpperBound)
{
continue;
}
twDist = CalculateDistance(notCriticalNode, v1, j, solution);
}
else
{
if (((solution.Vehicles[v1].Requests[j - 1].TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v1].Requests[j - 1].ID_Unique]) > criticalNode.TimeWindow.UpperBound) ||
(criticalNode.TimeWindow.LowerBound + _problem.Distances[criticalNode.ID_Unique][solution.Vehicles[v1].Requests[j].ID_Unique]) > solution.Vehicles[v1].Requests[j].TimeWindow.UpperBound)
{
continue;
}
twDist = (CalculateDistance(notCriticalNode, v1, j, solution) + CalculateDistance(notCriticalNode, v1, j - 1, solution)) / 2.0;
}
if (twDist < bestCost)
{
bestPos = j;
bestCost = twDist;
}
}
//Insertar en la mejor posición declarada.
solution.Vehicles[v1].Requests.Insert(bestPos, notCriticalNode);
//break; //terminamos.
}
}
//CorrectPositions(solution.Vehicles);
//Recalcular con el proceso de 8 pasos y actualizar el coste.
foreach (var vehicle in solution.Vehicles)
{
DARPAlgorithms.EightStepsEvaluationProcedure(ref solution, vehicle, _problem);
}
solution.TotalDuration = solution.Vehicles.Sum(t => t.VehicleDuration);
solution.TimeWindowViolation = solution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
solution.RideTimeViolation = solution.Vehicles.Sum(r => r.TotalRideTimeViolation);
solution.DurationViolation = solution.Vehicles.Sum(d => d.TotalDurationViolation);
solution.LoadViolation = solution.Vehicles.Sum(l => l.TotalLoadViolation);
solution.TotalWaitingTime = solution.Vehicles.Sum(t => t.TotalWaitingTime);
solution.Fitness = Costs.EvaluationSolution(solution, _problem);
Validator.ValidateSolution(ref solution, _problem);
}
catch (Exception ex)
{
Console.WriteLine();
}
}
private void SpecialPerturbation(ref Solution solution)
{
solution.Vehicles = solution.Vehicles.Select(t => { t.Perturbed = true; return(t); }).ToList();
//1. Sacar un vehículo aleatorio.
var vehicle = solution.Vehicles[_random.Next(0, solution.Vehicles.Count - 1)];
List <int> numbers = new List <int>();
//2. Sacar un cliente crítico.
var client = vehicle.Requests[_random.Next(1, vehicle.Requests.Count - 1)];
List <Tuple <Request, Tuple <int, int> > > data = new List <Tuple <Request, Tuple <int, int> > >();
if (!client.Origin)
{
client = vehicle.Requests.Find(t => t.Origin && t.PairID == client.PairID);
}
var vehicle_pos = solution.Vehicles.IndexOf(vehicle);
var client_pos = vehicle.Requests.IndexOf(client);
numbers.Add(client.PairID);
data.Add(new Tuple <Request, Tuple <int, int> >(client, new Tuple <int, int>(vehicle_pos, client_pos)));
//3. Sacar sus N vecinos críticos.
var neighbours = _problem.CloseTWMatrix[client.ID_Unique];
List <Request> vecinos = new List <Request>();
for (int i = 0; vecinos.Count < Convert.ToInt32(Math.Sqrt(_problem.NumRequests)) && i < neighbours.Count; i++)
{
if (_problem.Requests.Find(t => t.ID_Unique == neighbours[i]).Origin)
{
vecinos.Add(_problem.Requests.Find(t => t.ID_Unique == neighbours[i]));
numbers.Add(vecinos[vecinos.Count - 1].PairID);
}
}
//4. Sacar vehículo y posición de cada uno
foreach (var v in vecinos)
{
for (int i = 0; i < solution.Vehicles.Count; i++)
{
if (solution.Vehicles[i].Requests.Find(t => t.ID_Unique == v.ID_Unique) != null)
{
data.Add(new Tuple <Request, Tuple <int, int> >(v, new Tuple <int, int>(i, solution.Vehicles[i].Requests.IndexOf(solution.Vehicles[i].Requests.Find(t => t.ID_Unique == v.ID_Unique)))));
}
}
}
List <Tuple <Request, Tuple <int, int> > > movements = new List <Tuple <Request, Tuple <int, int> > >();
foreach (var element in data)
{
var request = element.Item1;
int selected = -1;
if (numbers.Count == 1 && numbers.First() == element.Item1.PairID)
{
break;
}
//5. Mezclarlos.
do
{
selected = numbers[_random.Next(0, numbers.Count)];
}while (selected == request.ID_Unique);
numbers.Remove(selected); //eliminarlo.
var posInterchange = data.Find(t => t.Item1.ID_Unique == selected);
//solution.Vehicles[element.Item2.Item1].Requests[element.Item2.Item2] = posInterchange.Item1;
//solution.Vehicles[posInterchange.Item2.Item1].Requests[posInterchange.Item2.Item2] = element.Item1;
//los destinos.
var destinoElement = solution.Vehicles[element.Item2.Item1].Requests.Find(t => t.PairID == element.Item1.PairID && t.Origin == false);
var destinoInterchange = solution.Vehicles[posInterchange.Item2.Item1].Requests.Find(t => t.PairID == posInterchange.Item1.PairID && t.Origin == false);
//solution.Vehicles[element.Item2.Item1].Requests[solution.Vehicles[element.Item2.Item1].Requests.IndexOf(destinoElement)] = destinoInterchange;
//solution.Vehicles[posInterchange.Item2.Item1].Requests[solution.Vehicles[posInterchange.Item2.Item1].Requests.IndexOf(destinoInterchange)] = destinoElement;
movements.Add(new Tuple <Request, Tuple <int, int> >(element.Item1, new Tuple <int, int>(posInterchange.Item2.Item1, posInterchange.Item2.Item2)));
movements.Add(new Tuple <Request, Tuple <int, int> >(destinoElement, new Tuple <int, int>(posInterchange.Item2.Item1, solution.Vehicles[posInterchange.Item2.Item1].Requests.IndexOf(destinoInterchange))));
}
foreach (var entry in movements)
{
solution.Vehicles[entry.Item2.Item1].Requests[entry.Item2.Item2] = entry.Item1;
}
//Recalcular con el proceso de 8 pasos y actualizar el coste.
foreach (var veh in solution.Vehicles)
{
DARPAlgorithms.EightStepsEvaluationProcedure(ref solution, veh, _problem);
}
solution.TotalDuration = solution.Vehicles.Sum(t => t.VehicleDuration);
solution.TimeWindowViolation = solution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
solution.RideTimeViolation = solution.Vehicles.Sum(r => r.TotalRideTimeViolation);
solution.DurationViolation = solution.Vehicles.Sum(d => d.TotalDurationViolation);
solution.LoadViolation = solution.Vehicles.Sum(l => l.TotalLoadViolation);
solution.TotalWaitingTime = solution.Vehicles.Sum(t => t.TotalWaitingTime);
DARPAlgorithms.UpdateConstraintsSolution(ref solution, _problem);
solution.Fitness = Costs.EvaluationSolution(solution, _problem);
}
private void SwapPerturbation(ref Solution solution)
{
solution.Vehicles = solution.Vehicles.Select(t => { t.Perturbed = false; return(t); }).ToList();
//Seleccionar el primer vehículo.
int v1 = _random.Next(0, PerturbationMechanism.Keys.Count);
if (PerturbationMechanism[v1].Count == 0)
{
ResetPerturbationMechanism(false, v1);
}
int v2;
do
{
v2 = PerturbationMechanism[v1][_random.Next(0, PerturbationMechanism[v1].Count)];
}while (v1 == v2);
PerturbationMechanism[v1].Remove(v2);
PerturbationMechanism[v2].Remove(v1);
var posA = _random.Next(1, solution.Vehicles[v1].Requests.Count - 1);
var node1 = solution.Vehicles[v1].Requests[posA];
var node2 = solution.Vehicles[v1].Requests.Find(t => t.PairID == node1.PairID && t.Origin != node1.Origin);
var posB = solution.Vehicles[v1].Requests.IndexOf(node2);
//Determinamos nodo crítico (será el primero a insertar).
Request originA;
Request destinationA;
int posOriginA = -1;
int posDestinationA = -1;
if (node1.Origin)
{
originA = node1;
destinationA = node2;
posOriginA = posA;
posDestinationA = posB;
}
else
{
originA = node2;
destinationA = node1;
posOriginA = posB;
posDestinationA = posA;
}
int minPos = -1;
double min = Double.MaxValue;
for (int i = 1; i < solution.Vehicles[v2].Requests.Count - 1; i++)
{
//if (!ValidTimeWindow(solution, node1, _problem, i + 1, v2)) continue;
// var distance = Problem.EuclideanDistance(node1.TimeWindow.LowerBound, node1.TimeWindow.UpperBound, solution.Vehicles[v2].Requests[i].TimeWindow.LowerBound, solution.Vehicles[v2].Requests[i].TimeWindow.UpperBound);
double twDist = 0.0;
if (i == 1)
{
if (!ValidTimeWindow(solution, node1, _problem, i + 1, v2))
{
continue;
}
twDist = CalculateDistance(node1, v2, i - 1, solution);
}
else if (i == solution.Vehicles[v2].Requests.Count - 2)
{
if (!ValidTimeWindow(solution, node1, _problem, i - 1, v2))
{
continue;
}
twDist = CalculateDistance(node1, v2, i - 1, solution);
}
else
{
if (!ValidTimeWindow(solution, node1, _problem, i + 1, v2) || !ValidTimeWindow(solution, node1, _problem, i - 1, v2))
{
continue;
}
twDist = (CalculateDistance(node1, v2, i + 1, solution) + CalculateDistance(node1, v2, i - 1, solution)) / 2.0;
}
if (twDist < min)
{
minPos = i;
min = twDist;
}
}
if (minPos == -1)
{
return;
}
var nodeB1 = solution.Vehicles[v2].Requests[minPos];
var nodeB2 = solution.Vehicles[v2].Requests.Find(t => t.PairID == nodeB1.PairID && t.Origin != nodeB1.Origin);
var posNodeB2 = solution.Vehicles[v2].Requests.IndexOf(nodeB2);
//Determinamos nodo crítico (será el primero a insertar).
Request originB;
Request destinationB;
if (nodeB1.Origin)
{
originB = nodeB1;
destinationB = nodeB2;
}
else
{
originB = nodeB2;
destinationB = nodeB1;
var aux = minPos;
minPos = posNodeB2;
posNodeB2 = aux;
}
solution.Vehicles[v2].Requests[minPos] = originA;
solution.Vehicles[v2].Requests[posNodeB2] = destinationA;
solution.Vehicles[v1].Requests[posOriginA] = originB;
solution.Vehicles[v1].Requests[posDestinationA] = destinationB;
Validator.Positions(ref solution, _problem);
solution.Vehicles[v2].Perturbed = true;
solution.Vehicles[v1].Perturbed = true;
DARPAlgorithms.EightStepsEvaluationProcedure(ref solution, solution.Vehicles[v1], _problem);
DARPAlgorithms.EightStepsEvaluationProcedure(ref solution, solution.Vehicles[v2], _problem);
solution.TotalDuration = solution.Vehicles.Sum(t => t.VehicleDuration);
solution.TimeWindowViolation = solution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
solution.RideTimeViolation = solution.Vehicles.Sum(r => r.TotalRideTimeViolation);
solution.DurationViolation = solution.Vehicles.Sum(d => d.TotalDurationViolation);
solution.LoadViolation = solution.Vehicles.Sum(l => l.TotalLoadViolation);
solution.TotalWaitingTime = solution.Vehicles.Sum(t => t.TotalWaitingTime);
solution.Fitness = Costs.EvaluationSolution(solution, _problem);
Validator.Positions(ref solution, _problem);
}
private bool Shift1_0Inter(ref Solution solution)
{
Solution optSolution = solution;
bool improvement = false;
double bestCost = optSolution.Fitness;
bool exit = false;
int v1_aux;
Init:
var vehicle = optSolution.Vehicles;
for (int v1 = 0; v1 < optSolution.Vehicles.Count; v1++)
{
if (optSolution.Vehicles[v1].Requests.Count == 4)
{
continue;
}
for (int v2 = 0; v2 < optSolution.Vehicles.Count; v2++)
{
if (v1 == v2 || (!optSolution.Vehicles[v1].Perturbed || !optSolution.Vehicles[v2].Perturbed))
{
continue;
}
for (int i = 1; i < optSolution.Vehicles[v1].Requests.Count - 1; i++)
{
var critical = vehicle[v1].Requests[i];
var criticalPos = i;
if (!critical.IsCritical)
{
continue;
}
var notCritical = vehicle[v1].Requests.Find(t => t.PairID == critical.PairID && t.Origin != critical.Origin);
var notCriticalPos = vehicle[v1].Requests.IndexOf(notCritical);
var v1DurV = vehicle[v1].TotalDurationViolation;
var v1TWV = vehicle[v1].TotalTimeWindowViolation;
var v1RTV = vehicle[v1].TotalRideTimeViolation;
var v1LV = vehicle[v1].TotalLoadViolation;
var v1TWT = vehicle[v1].TotalWaitingTime;
var v1Dur = vehicle[v1].VehicleDuration;
vehicle[v1].Requests.RemoveAll(t => t.PairID == critical.PairID);
DARPAlgorithms.EightStepsEvaluationProcedure(ref optSolution, optSolution.Vehicles[v1], _problem);
for (int j = 1; j < vehicle[v2].Requests.Count - 1; j++)
{
if (_problem.FeasibleTravel[vehicle[v2].Requests[j - 1].ID_Unique][critical.ID_Unique] && _problem.FeasibleTravel[critical.ID_Unique][vehicle[v2].Requests[j].ID_Unique])
{
vehicle[v2].Requests.Insert(j, critical);
if (critical.Origin)
{
int index_Target = j + 1;
while (index_Target < vehicle[v2].Requests.Count) //Desde la posición actual a la primera posición.
{
if (_problem.FeasibleTravel[vehicle[v2].Requests[index_Target - 1].ID_Unique][notCritical.ID_Unique] && _problem.FeasibleTravel[notCritical.ID_Unique][vehicle[v2].Requests[index_Target].ID_Unique])
{
vehicle[v2].Requests.Insert(index_Target, notCritical);
//Salvar estados vehículo actuales.
var v2DurV = vehicle[v2].TotalDurationViolation;
var v2TWV = vehicle[v2].TotalTimeWindowViolation;
var v2RTV = vehicle[v2].TotalRideTimeViolation;
var v2LV = vehicle[v2].TotalLoadViolation;
var v2TWT = vehicle[v2].TotalWaitingTime;
var v2Dur = vehicle[v2].VehicleDuration;
DARPAlgorithms.EightStepsEvaluationProcedure(ref optSolution, optSolution.Vehicles[v2], _problem);
//Actualizar estado de la solución.
var vd = optSolution.Vehicles.Sum(t => t.VehicleDuration);
var twv = optSolution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
var rtv = optSolution.Vehicles.Sum(r => r.TotalRideTimeViolation);
var tdv = optSolution.Vehicles.Sum(d => d.TotalDurationViolation);
var lv = optSolution.Vehicles.Sum(l => l.TotalLoadViolation);
var wt = optSolution.Vehicles.Sum(t => t.TotalWaitingTime);
var cost = Costs.EvaluationSolution(ref optSolution, twv, rtv, tdv, lv, _problem);
if (Math.Round(cost, 2) < Math.Round(bestCost, 2))
{
bestCost = cost;
ShiftInter++;
optSolution.TotalDuration = vd;
optSolution.TimeWindowViolation = twv;
optSolution.RideTimeViolation = rtv;
optSolution.DurationViolation = tdv;
optSolution.LoadViolation = lv;
optSolution.TotalWaitingTime = wt;
improvement = true;
goto Init;
}
else
{
//Deshacer el movimiento de inserción.
vehicle[v2].Requests.Remove(notCritical);
//Copiar estados anteriores a las modificaciones.
optSolution.Vehicles[v2].TotalDurationViolation = v2DurV;
optSolution.Vehicles[v2].TotalTimeWindowViolation = v2TWV;
optSolution.Vehicles[v2].TotalRideTimeViolation = v2RTV;
optSolution.Vehicles[v2].TotalLoadViolation = v2LV;
optSolution.Vehicles[v2].TotalWaitingTime = v2TWT;
optSolution.Vehicles[v2].VehicleDuration = v2Dur;
}
}
index_Target++;
}
}
else
{
int index_Target = j;
while (index_Target > 0) //mientras no se llegue a la petición destino.
{
if (_problem.FeasibleTravel[vehicle[v2].Requests[index_Target - 1].ID_Unique][notCritical.ID_Unique] && _problem.FeasibleTravel[notCritical.ID_Unique][vehicle[v2].Requests[index_Target].ID_Unique])
{
vehicle[v2].Requests.Insert(index_Target, notCritical);
//Marcar rutas que han sido modificadas.
var v2DurV = optSolution.Vehicles[v2].TotalDurationViolation;
var v2TWV = optSolution.Vehicles[v2].TotalTimeWindowViolation;
var v2RTV = optSolution.Vehicles[v2].TotalRideTimeViolation;
var v2LV = optSolution.Vehicles[v2].TotalLoadViolation;
var v2TWT = optSolution.Vehicles[v2].TotalWaitingTime;
var v2Dur = optSolution.Vehicles[v2].VehicleDuration;
DARPAlgorithms.EightStepsEvaluationProcedure(ref optSolution, optSolution.Vehicles[v2], _problem);
//Actualizar estado de la solución.
var vd = optSolution.Vehicles.Sum(t => t.VehicleDuration);
var twv = optSolution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
var rtv = optSolution.Vehicles.Sum(r => r.TotalRideTimeViolation);
var tdv = optSolution.Vehicles.Sum(d => d.TotalDurationViolation);
var lv = optSolution.Vehicles.Sum(l => l.TotalLoadViolation);
var wt = optSolution.Vehicles.Sum(t => t.TotalWaitingTime);
var cost = Costs.EvaluationSolution(ref optSolution, twv, rtv, tdv, lv, _problem);
if (Math.Round(cost, 2) < Math.Round(bestCost, 2))
{
bestCost = cost;
ShiftInter++;
optSolution.TotalDuration = vd;
optSolution.TimeWindowViolation = twv;
optSolution.RideTimeViolation = rtv;
optSolution.DurationViolation = tdv;
optSolution.LoadViolation = lv;
optSolution.TotalWaitingTime = wt;
improvement = true;
goto Init;
}
else
{
//Deshacer el movimiento Swap1_1
vehicle[v2].Requests.Remove(notCritical);
//Copiar estados anteriores a las modificaciones.
optSolution.Vehicles[v2].TotalDurationViolation = v2DurV;
optSolution.Vehicles[v2].TotalTimeWindowViolation = v2TWV;
optSolution.Vehicles[v2].TotalRideTimeViolation = v2RTV;
optSolution.Vehicles[v2].TotalLoadViolation = v2LV;
optSolution.Vehicles[v2].TotalWaitingTime = v2TWT;
optSolution.Vehicles[v2].VehicleDuration = v2Dur;
}
}
index_Target--;
}
}
vehicle[v2].Requests.Remove(critical);
}
}
if (criticalPos < notCriticalPos)
{
vehicle[v1].Requests.Insert(criticalPos, critical);
vehicle[v1].Requests.Insert(notCriticalPos, notCritical);
exit = true;
}
else
{
vehicle[v1].Requests.Insert(notCriticalPos, notCritical);
vehicle[v1].Requests.Insert(criticalPos, critical);
exit = true;
v1_aux = v1;
}
vehicle[v1].TotalDurationViolation = v1DurV;
vehicle[v1].TotalTimeWindowViolation = v1TWV;
vehicle[v1].TotalRideTimeViolation = v1RTV;
vehicle[v1].TotalLoadViolation = v1LV;
vehicle[v1].TotalWaitingTime = v1TWT;
vehicle[v1].VehicleDuration = v1Dur;
}
}
}
optSolution.Fitness = bestCost;
return(improvement);
}
private bool Swap_Intra(ref Solution solution)
{
Solution optSolution = solution;
bool improvement = false;
double bestCost = optSolution.Fitness;
double parcCost = optSolution.Parc_Cost;
Init:
var vehicle = optSolution.Vehicles;
for (int v = 0; v < vehicle.Count; v++)
{
//Vehicle selection.
var requests = vehicle[v].Requests;
if (!vehicle[v].Perturbed)
{
continue; //NO hay sido modificado.
}
for (int i = 1; i < requests.Count - 1; i++)
{
var node1V1 = requests[i];
if (!node1V1.Origin)
{
continue;
}
var node2V1 = requests.Find(t => t.PairID == node1V1.PairID && t.Origin != node1V1.Origin);
var indexNode2V1 = requests.IndexOf(node2V1);
for (int j = 1; j < requests.Count - 1; j++)
{
var node1V2 = requests[j];
if (!node1V2.Origin)
{
continue;
}
if (i == j || node1V1.PairID == node1V2.PairID)
{
continue; //omitir mismas posiciones
}
var node2V2 = requests.Find(t => t.PairID == node1V2.PairID && t.Origin != node1V2.Origin);
var indexNode2V2 = requests.IndexOf(node2V2);
if (!CheckTimeWindowSwap1_1_Intra(ref optSolution, vehicle[v].Requests, i, j) && !_problem.NeighborhoodTW[node1V1.PairID][node1V2.PairID] && !_problem.NeighborhoodTW[node1V2.PairID][node1V1.PairID])
{
continue;
}
requests[i] = node1V2;
requests[j] = node1V1;
requests[indexNode2V1] = node2V2;
requests[indexNode2V2] = node2V1;
var v1DurV = optSolution.Vehicles[v].TotalDurationViolation;
var v1TWV = optSolution.Vehicles[v].TotalTimeWindowViolation;
var v1RTV = optSolution.Vehicles[v].TotalRideTimeViolation;
var v1LV = optSolution.Vehicles[v].TotalLoadViolation;
var v1TWT = optSolution.Vehicles[v].TotalWaitingTime;
var v1Dur = optSolution.Vehicles[v].VehicleDuration;
DARPAlgorithms.EightStepsEvaluationProcedure(ref optSolution, optSolution.Vehicles[v], _problem);
//Actualizar estado de la solución.
var vd = optSolution.Vehicles.Sum(t => t.VehicleDuration);
var twv = optSolution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
var rtv = optSolution.Vehicles.Sum(r => r.TotalRideTimeViolation);
var tdv = optSolution.Vehicles.Sum(d => d.TotalDurationViolation);
var lv = optSolution.Vehicles.Sum(l => l.TotalLoadViolation);
var wt = optSolution.Vehicles.Sum(t => t.TotalWaitingTime);
var cost = Costs.EvaluationSolution(ref optSolution, twv, rtv, tdv, lv, _problem);
if (Math.Round(cost, 2) < Math.Round(bestCost, 2))
{
bestCost = cost;
optSolution.TotalDuration = vd;
optSolution.TimeWindowViolation = twv;
optSolution.RideTimeViolation = rtv;
optSolution.DurationViolation = tdv;
optSolution.LoadViolation = lv;
optSolution.TotalWaitingTime = wt;
IntraSwap++;
improvement = true;
goto Init;
}
else
{
//Deshacer el movimiento de intercambio
requests[i] = node1V1;
requests[j] = node1V2;
requests[indexNode2V1] = node2V1;
requests[indexNode2V2] = node2V2;
//Copiar estados anteriores a las modificaciones.
optSolution.Vehicles[v].TotalDurationViolation = v1DurV;
optSolution.Vehicles[v].TotalTimeWindowViolation = v1TWV;
optSolution.Vehicles[v].TotalRideTimeViolation = v1RTV;
optSolution.Vehicles[v].TotalLoadViolation = v1LV;
optSolution.Vehicles[v].TotalWaitingTime = v1TWT;
optSolution.Vehicles[v].VehicleDuration = v1Dur;
}
}
}
}
optSolution.Fitness = bestCost;
optSolution.Parc_Cost = parcCost;
return(improvement);
}
private bool WRI_Intra(ref Solution solution)
{
bool improvement = false;
Solution optSolution = solution;
double bestCost = optSolution.Fitness;
double parcCost = optSolution.Parc_Cost;
Init:
var vehicle = optSolution.Vehicles;
for (int v = 0; v < vehicle.Count; v++)
{
if (!vehicle[v].Perturbed)
{
continue; //NO hay sido modificado.
}
//Vehicle selection.
var requests = vehicle[v].Requests;
for (int i = 1; i < requests.Count - 1; i++)
{
var node = requests[i];
requests.RemoveAt(i); //Eliminar de su posición de origen.
if (node.Origin)
{
var index_Destination = requests.IndexOf(requests.Find(t => t.PairID == node.PairID && t.Origin != node.Origin));
for (int j = 1; j <= index_Destination; j++)
{
if (!CheckTimeWindowShift1_0(ref optSolution, requests, node, j))
{
continue;
}
requests.Insert(j, node); //Insertar el nodo en su nueva posición.
var v1DurV = optSolution.Vehicles[v].TotalDurationViolation;
var v1TWV = optSolution.Vehicles[v].TotalTimeWindowViolation;
var v1RTV = optSolution.Vehicles[v].TotalRideTimeViolation;
var v1LV = optSolution.Vehicles[v].TotalLoadViolation;
var v1TWT = optSolution.Vehicles[v].TotalWaitingTime;
var v1Dur = optSolution.Vehicles[v].VehicleDuration;
DARPAlgorithms.EightStepsEvaluationProcedure(ref optSolution, optSolution.Vehicles[v], _problem);
//Actualizar estado de la solución.
var vd = optSolution.Vehicles.Sum(t => t.VehicleDuration);
var twv = optSolution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
var rtv = optSolution.Vehicles.Sum(r => r.TotalRideTimeViolation);
var tdv = optSolution.Vehicles.Sum(d => d.TotalDurationViolation);
var lv = optSolution.Vehicles.Sum(l => l.TotalLoadViolation);
var wt = optSolution.Vehicles.Sum(t => t.TotalWaitingTime);
var cost = Costs.EvaluationSolution(ref optSolution, twv, rtv, tdv, lv, _problem);
if (Math.Round(cost, 2) < Math.Round(bestCost, 2))
{
bestCost = cost;
optSolution.TotalDuration = vd;
optSolution.TimeWindowViolation = twv;
optSolution.RideTimeViolation = rtv;
optSolution.DurationViolation = tdv;
optSolution.LoadViolation = lv;
optSolution.TotalWaitingTime = wt;
WRI_IntraOP++;
improvement = true;
goto Init;
}
else
{
//Deshacer el movimiento SHIFT
requests.RemoveAt(j); //Eliminar de su posición de origen.
optSolution.Vehicles[v].TotalDurationViolation = v1DurV;
optSolution.Vehicles[v].TotalTimeWindowViolation = v1TWV;
optSolution.Vehicles[v].TotalRideTimeViolation = v1RTV;
optSolution.Vehicles[v].TotalLoadViolation = v1LV;
optSolution.Vehicles[v].TotalWaitingTime = v1TWT;
optSolution.Vehicles[v].VehicleDuration = v1Dur;
}
}
requests.Insert(i, node); //No ha habido cambios e insertarlo en su posición original
}
else
{
var index_Destination = requests.IndexOf(requests.Find(t => t.PairID == node.PairID && t.Origin != node.Origin));
for (int j = requests.Count - 1; j > index_Destination; j--)
{
if (!CheckTimeWindowShift1_0(ref optSolution, requests, node, j))
{
continue;
}
requests.Insert(j, node); //Insertar el nodo en su nueva posición.
var v1DurV = optSolution.Vehicles[v].TotalDurationViolation;
var v1TWV = optSolution.Vehicles[v].TotalTimeWindowViolation;
var v1RTV = optSolution.Vehicles[v].TotalRideTimeViolation;
var v1LV = optSolution.Vehicles[v].TotalLoadViolation;
var v1TWT = optSolution.Vehicles[v].TotalWaitingTime;
var v1Dur = optSolution.Vehicles[v].VehicleDuration;
DARPAlgorithms.EightStepsEvaluationProcedure(ref optSolution, optSolution.Vehicles[v], _problem);
//Actualizar estado de la solución.
var vd = optSolution.Vehicles.Sum(t => t.VehicleDuration);
var twv = optSolution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
var rtv = optSolution.Vehicles.Sum(r => r.TotalRideTimeViolation);
var tdv = optSolution.Vehicles.Sum(d => d.TotalDurationViolation);
var lv = optSolution.Vehicles.Sum(l => l.TotalLoadViolation);
var wt = optSolution.Vehicles.Sum(t => t.TotalWaitingTime);
var cost = Costs.EvaluationSolution(ref optSolution, twv, rtv, tdv, lv, _problem);
if (Math.Round(cost, 2) < Math.Round(bestCost, 2))
{
bestCost = cost;
optSolution.TotalDuration = vd;
optSolution.TimeWindowViolation = twv;
optSolution.RideTimeViolation = rtv;
optSolution.DurationViolation = tdv;
optSolution.LoadViolation = lv;
optSolution.TotalWaitingTime = wt;
WRI_IntraOP++;
improvement = true;
goto Init;
}
else
{
//Deshacer el movimiento SHIFT
requests.RemoveAt(j); //Eliminar de su posición de origen.
optSolution.Vehicles[v].TotalDurationViolation = v1DurV;
optSolution.Vehicles[v].TotalTimeWindowViolation = v1TWV;
optSolution.Vehicles[v].TotalRideTimeViolation = v1RTV;
optSolution.Vehicles[v].TotalLoadViolation = v1LV;
optSolution.Vehicles[v].TotalWaitingTime = v1TWT;
optSolution.Vehicles[v].VehicleDuration = v1Dur;
}
}
requests.Insert(i, node); //No ha habido cambios e insertarlo en su posición original
}
}
}
optSolution.Fitness = bestCost;
return(improvement);
}
private bool IntraRouteInsertion(ref Solution solution)
{
bool improvement = false;
Solution optSolution = solution;
double bestCost = optSolution.Fitness;
Init:
var vehicle = optSolution.Vehicles;
for (int v = 0; v < vehicle.Count; v++)
{
if (!vehicle[v].Perturbed)
{
continue;
}
//Vehicle selection.
for (int i = 1; i < vehicle[v].Requests.Count - 1; i++)
{
var critical = vehicle[v].Requests[i];
var criticalPos = i;
if (!critical.IsCritical)
{
continue;
}
var notCritical = vehicle[v].Requests.Find(t => t.PairID == critical.PairID && t.Origin != critical.Origin);
var notCriticalPos = vehicle[v].Requests.IndexOf(notCritical);
vehicle[v].Requests.RemoveAll(t => t.PairID == critical.PairID);
for (int j = 1; j < vehicle[v].Requests.Count - 1; j++)
{
if (CheckTimeWindowShift1_0(ref optSolution, vehicle[v].Requests, critical, j))
{
vehicle[v].Requests.Insert(j, critical);
if (critical.Origin)
{
int index_Target = j + 1;
while (index_Target < vehicle[v].Requests.Count) //Desde la posición actual a la primera posición.
{
if (CheckTimeWindowShift1_0(ref optSolution, vehicle[v].Requests, notCritical, index_Target))
{
vehicle[v].Requests.Insert(index_Target, notCritical);
//Salvar estados vehículo actuales.
var v1DurV = vehicle[v].TotalDurationViolation;
var v1TWV = vehicle[v].TotalTimeWindowViolation;
var v1RTV = vehicle[v].TotalRideTimeViolation;
var v1LV = vehicle[v].TotalLoadViolation;
var v1TWT = vehicle[v].TotalWaitingTime;
var v1Dur = vehicle[v].VehicleDuration;
DARPAlgorithms.EightStepsEvaluationProcedure(ref optSolution, optSolution.Vehicles[v], _problem);
//Actualizar estado de la solución.
var vd = optSolution.Vehicles.Sum(t => t.VehicleDuration);
var twv = optSolution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
var rtv = optSolution.Vehicles.Sum(r => r.TotalRideTimeViolation);
var tdv = optSolution.Vehicles.Sum(d => d.TotalDurationViolation);
var lv = optSolution.Vehicles.Sum(l => l.TotalLoadViolation);
var wt = optSolution.Vehicles.Sum(t => t.TotalWaitingTime);
var cost = Costs.EvaluationSolution(ref optSolution, twv, rtv, tdv, lv, _problem);
if (Math.Round(cost, 2) < Math.Round(bestCost, 2))
{
bestCost = cost;
IntraRouteInsertionOP++;
optSolution.TotalDuration = vd;
optSolution.TimeWindowViolation = twv;
optSolution.RideTimeViolation = rtv;
optSolution.DurationViolation = tdv;
optSolution.LoadViolation = lv;
optSolution.TotalWaitingTime = wt;
improvement = true;
goto Init;
}
else
{
//Deshacer el movimiento de inserción.
vehicle[v].Requests.Remove(notCritical);
//Copiar estados anteriores a las modificaciones.
optSolution.Vehicles[v].TotalDurationViolation = v1DurV;
optSolution.Vehicles[v].TotalTimeWindowViolation = v1TWV;
optSolution.Vehicles[v].TotalRideTimeViolation = v1RTV;
optSolution.Vehicles[v].TotalLoadViolation = v1LV;
optSolution.Vehicles[v].TotalWaitingTime = v1TWT;
optSolution.Vehicles[v].VehicleDuration = v1Dur;
//if (vehicle[v].Requests[index_Target - 1].DepartureTime - vehicle[v].Requests[index_Target - 1].SlackTime + _problem.Distances[vehicle[v].Requests[index_Target - 1].ID_Unique][notCritical.ID_Unique] > notCritical.TimeWindow.UpperBound)
// break;
}
}
index_Target++;
}
}
else
{
int index_Target = j;
while (index_Target > 0) //mientras no se llegue a la petición destino.
{
if (CheckTimeWindowShift1_0(ref optSolution, vehicle[v].Requests, notCritical, index_Target))
{
vehicle[v].Requests.Insert(index_Target, notCritical);
//Marcar rutas que han sido modificadas.
var v1DurV = optSolution.Vehicles[v].TotalDurationViolation;
var v1TWV = optSolution.Vehicles[v].TotalTimeWindowViolation;
var v1RTV = optSolution.Vehicles[v].TotalRideTimeViolation;
var v1LV = optSolution.Vehicles[v].TotalLoadViolation;
var v1TWT = optSolution.Vehicles[v].TotalWaitingTime;
var v1Dur = optSolution.Vehicles[v].VehicleDuration;
DARPAlgorithms.EightStepsEvaluationProcedure(ref optSolution, optSolution.Vehicles[v], _problem);
//Actualizar estado de la solución.
var vd = optSolution.Vehicles.Sum(t => t.VehicleDuration);
var twv = optSolution.Vehicles.Sum(t => t.TotalTimeWindowViolation);
var rtv = optSolution.Vehicles.Sum(r => r.TotalRideTimeViolation);
var tdv = optSolution.Vehicles.Sum(d => d.TotalDurationViolation);
var lv = optSolution.Vehicles.Sum(l => l.TotalLoadViolation);
var wt = optSolution.Vehicles.Sum(t => t.TotalWaitingTime);
var cost = Costs.EvaluationSolution(ref optSolution, twv, rtv, tdv, lv, _problem);
if (Math.Round(cost, 2) < Math.Round(bestCost, 2))
{
bestCost = cost;
IntraRouteInsertionOP++;
optSolution.TotalDuration = vd;
optSolution.TimeWindowViolation = twv;
optSolution.RideTimeViolation = rtv;
optSolution.DurationViolation = tdv;
optSolution.LoadViolation = lv;
optSolution.TotalWaitingTime = wt;
improvement = true;
goto Init;
}
else
{
//Deshacer el movimiento Swap1_1
vehicle[v].Requests.Remove(notCritical);
//Copiar estados anteriores a las modificaciones.
optSolution.Vehicles[v].TotalDurationViolation = v1DurV;
optSolution.Vehicles[v].TotalTimeWindowViolation = v1TWV;
optSolution.Vehicles[v].TotalRideTimeViolation = v1RTV;
optSolution.Vehicles[v].TotalLoadViolation = v1LV;
optSolution.Vehicles[v].TotalWaitingTime = v1TWT;
optSolution.Vehicles[v].VehicleDuration = v1Dur;
//if (vehicle[v].Requests[index_Target - 1].DepartureTime - vehicle[v].Requests[index_Target - 1].SlackTime + _problem.Distances[vehicle[v].Requests[index_Target - 1].ID_Unique][notCritical.ID_Unique] > notCritical.TimeWindow.UpperBound)
// break;
}
}
index_Target--;
}
}
vehicle[v].Requests.Remove(critical);
}
}
if (criticalPos < notCriticalPos)
{
vehicle[v].Requests.Insert(criticalPos, critical);
vehicle[v].Requests.Insert(notCriticalPos, notCritical);
}
else
{
vehicle[v].Requests.Insert(notCriticalPos, notCritical);
vehicle[v].Requests.Insert(criticalPos, critical);
}
}
}
optSolution.Fitness = bestCost;
return(improvement);
}
