#region License Information
/* HeuristicLab
* Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using HeuristicLab.Core;
using HeuristicLab.Encodings.PermutationEncoding;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Data;
using System.Collections.Generic;
namespace HeuristicLab.Problems.VehicleRouting.Encodings.Potvin {
[Item("LocalSearchManipulator", "The LSM operator which manipulates a Potvin VRP representation. It is implemented as described in Potvin, J.-Y. and Bengio, S. (1996). The Vehicle Routing Problem with Time Windows - Part II: Genetic Search. INFORMS Journal of Computing, 8:165–172.")]
[StorableClass]
public sealed class LocalSearchManipulator : PotvinManipulator {
[StorableConstructor]
private LocalSearchManipulator(bool deserializing) : base(deserializing) { }
public LocalSearchManipulator() : base() { }
private bool FindBetterInsertionPlace(
PotvinEncoding individual, int tour, int city, int length,
out int insertionTour, out int insertionPlace) {
bool insertionFound = false;
insertionTour = -1;
insertionPlace = 1;
List toBeDeleted = individual.Tours[tour].Cities.GetRange(city, length);
double distance = GetLength(individual.Tours[tour]);
individual.Tours[tour].Cities.RemoveRange(city, length);
double removalBenefit = distance - GetLength(individual.Tours[tour]);
int currentTour = 0;
while (currentTour < individual.Tours.Count && !insertionFound) {
int currentCity = 0;
while (currentCity <= individual.Tours[currentTour].Cities.Count && !insertionFound) {
distance = GetLength(individual.Tours[currentTour]);
individual.Tours[currentTour].Cities.InsertRange(currentCity, toBeDeleted);
if (Feasible(individual.Tours[currentTour])) {
double lengthIncrease =
GetLength(individual.Tours[currentTour]) - distance;
if (removalBenefit > lengthIncrease) {
insertionTour = currentTour;
insertionPlace = currentCity;
insertionFound = true;
}
}
individual.Tours[currentTour].Cities.RemoveRange(currentCity, length);
currentCity++;
}
currentTour++;
}
individual.Tours[tour].Cities.InsertRange(city, toBeDeleted);
return insertionFound;
}
protected override void Manipulate(IRandom random, PotvinEncoding individual) {
//only apply to feasible individuals
if (Feasible(individual)) {
bool insertionFound;
do {
insertionFound = false;
int length = 3;
while (length > 0 && !insertionFound) {
int tour = 0;
while (tour < individual.Tours.Count && !insertionFound) {
int city = 0;
while (city <= individual.Tours[tour].Cities.Count - length && !insertionFound) {
int insertionTour, insertionPlace;
if (FindBetterInsertionPlace(individual, tour, city, length,
out insertionTour, out insertionPlace)) {
insertionFound = true;
List toBeInserted = individual.Tours[tour].Cities.GetRange(city, length);
individual.Tours[tour].Cities.RemoveRange(city, length);
individual.Tours[insertionTour].Cities.InsertRange(
insertionPlace,
toBeInserted);
}
city++;
}
tour++;
}
length--;
}
} while (insertionFound);
}
}
}
}