source: branches/FitnessLandscapeAnalysis/HeuristicLab.Analysis.FitnessLandscape.VRP/Manipulators/ExchangeManipulator.cs @ 7624

#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("ExchangeManipulator", "Exchange manipulation")]
  [StorableClass]
  public sealed class ExchangeManipulator : PotvinManipulator {
    [StorableConstructor]
    private ExchangeManipulator(bool deserializing) : base(deserializing) { }
    private ExchangeManipulator(ExchangeManipulator original, Cloner cloner)
      : base(original, cloner) {
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new ExchangeManipulator(this, cloner);
    }
    public ExchangeManipulator()
      : 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;

        if (individual.Tours.Count > 1) {
          int tour1Idx = random.Next(individual.Tours.Count);
          int tour2Idx = random.Next(individual.Tours.Count - 1);
          if (tour2Idx >= tour1Idx)
            tour2Idx++;

          Tour tour1 = individual.Tours[tour1Idx];
          Tour tour2 = individual.Tours[tour2Idx];

          int index1 = random.Next(tour1.Cities.Count);
          int city1 = tour1.Cities[index1];

          int index2 = random.Next(tour2.Cities.Count);
          int city2 = tour2.Cities[index2];

          if (!allowInfeasible) {
            bool originalFeasible =
              RouteFeasible(tour1, demand, capacity) &&
              RouteFeasible(tour2, demand, capacity);

            if (originalFeasible) {
              double routeLoad = 0;
              for (int i = 0; i < tour1.Cities.Count; i++) {
                if (i != index1)
                  routeLoad += demand[tour1.Cities[i]];
              }
              routeLoad += demand[city2];

              if (routeLoad > capacity.Value) {
                feasible = false;
              } else {
                routeLoad = 0;
                for (int i = 0; i < tour2.Cities.Count; i++) {
                  if (i != index2)
                    routeLoad += demand[tour2.Cities[i]];
                }
                routeLoad += demand[city1];

                if (routeLoad > capacity.Value) {
                  feasible = false;
                }
              }

            }
          }

          if (feasible) {
            tour1.Cities.RemoveAt(index1);
            tour1.Cities.Insert(index1, city2);

            tour2.Cities.RemoveAt(index2);
            tour2.Cities.Insert(index2, city1);
          }
        }
      } 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);
    }
  }
}