source: branches/FitnessLandscapeAnalysis/HeuristicLab.Analysis.FitnessLandscape.VRP/Manipulators/RelocateManipulator.cs @ 8191

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2011 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 <http://www.gnu.org/licenses/>.
 */
#endregion

using System.Collections.Generic;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
using HeuristicLab.Problems.VehicleRouting.Encodings.Potvin;
using HeuristicLab.Problems.VehicleRouting.Encodings;
using HeuristicLab.Problems.VehicleRouting;

namespace HeuristicLab.Analysis.FitnessLandscape.VRP {
  [Item("RelocateManipulator", "Relocate manipulation")]
  [StorableClass]
  public sealed class RelocateManipulator : PotvinManipulator {
    [StorableConstructor]
    private RelocateManipulator(bool deserializing) : base(deserializing) { }
    private RelocateManipulator(RelocateManipulator original, Cloner cloner)
      : base(original, cloner) {
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new RelocateManipulator(this, cloner);
    }
    public RelocateManipulator()
      : base() {
    }

    private static bool RouteFeasible(Tour tour, DoubleArray demand, DoubleValue capacity) {
      double routeLoad = 0;
      for (int i = 0; i < tour.Cities.Count; i++) {
        routeLoad += demand[tour.Cities[i]];
      }

      return routeLoad <= capacity.Value;
    }

    public static void Apply(IRandom random, PotvinEncoding individual, DoubleArray demand, DoubleValue capacity, bool allowInfeasible) {
      bool feasible;

      do {
        feasible = true;

        int cities = individual.Cities;
        int city = 1 + random.Next(cities);
        Tour originalTour = individual.Tours.Find(t => t.Cities.Contains(city));
        //consider creating new route
        individual.Tours.Add(new Tour());

        int position = 1 + random.Next(cities + individual.Tours.Count - 1);
        if (position >= city) {
          position++;
        }

        int originalPosition = originalTour.Cities.IndexOf(city);
        originalTour.Cities.RemoveAt(originalPosition);

        Tour insertionTour;
        int insertionPosition;
        if (position <= cities) {
          insertionTour = individual.Tours.Find(t => t.Cities.Contains(position));
          insertionPosition = insertionTour.Cities.IndexOf(position) + 1;
        } else {
          insertionTour = individual.Tours[position - cities - 1];
          insertionPosition = 0;
        }

        if (!allowInfeasible && insertionTour != originalTour) {
          bool originalFeasible = RouteFeasible(insertionTour, demand, capacity);

          if (originalFeasible) {
            double routeLoad = 0;
            for (int i = 0; i < insertionTour.Cities.Count; i++) {
              routeLoad += demand[insertionTour.Cities[i]];
            }
            routeLoad += demand[city];

            feasible = routeLoad <= capacity.Value;
          }
        }

        if (feasible) {
          insertionTour.Cities.Insert(insertionPosition, city);
        } else {
          originalTour.Cities.Insert(originalPosition, city);
        }

        individual.Tours.RemoveAll(t => t.Cities.Count == 0);
      } while (!feasible);
    }

    protected override void Manipulate(IRandom random, PotvinEncoding individual) {
      BoolValue useDistanceMatrix = UseDistanceMatrixParameter.ActualValue;
      DoubleMatrix coordinates = CoordinatesParameter.ActualValue;
      DistanceMatrix distMatrix = VRPUtilities.GetDistanceMatrix(coordinates, DistanceMatrixParameter, useDistanceMatrix);
      DoubleArray demand = DemandParameter.ActualValue;
      DoubleValue capacity = CapacityParameter.ActualValue;

      bool allowInfeasible = AllowInfeasibleSolutions.Value.Value;
      Apply(random, individual, demand, capacity, allowInfeasible);
    }
  }
}