source: branches/FitnessLandscapeAnalysis/HeuristicLab.Analysis.FitnessLandscape.VRP/Manipulators/TwoOptStarManipulator.cs @ 7145

#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.Anaylsis.FitnessLandscape.VRP {
  [Item("TwoOptStarMainpulator", "Two opt star manipulation")]
  [StorableClass]
  public sealed class TwoOptStarMainpulator : PotvinManipulator {
    [StorableConstructor]
    private TwoOptStarMainpulator(bool deserializing) : base(deserializing) { }
    private TwoOptStarMainpulator(TwoOptStarMainpulator original, Cloner cloner)
      : base(original, cloner) {
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new TwoOptStarMainpulator(this, cloner);
    }
    public TwoOptStarMainpulator()
      : 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 route1Idx = random.Next(individual.Tours.Count);
          int route2Idx = random.Next(individual.Tours.Count - 1);
          if (route2Idx >= route1Idx)
            route2Idx++;

          Tour route1 = individual.Tours[route1Idx];
          Tour route2 = individual.Tours[route2Idx];

          int x1 = random.Next(route1.Cities.Count + 1);
          int x2 = random.Next(route2.Cities.Count + 1);

          if (!allowInfeasible) {
            bool originalFeasible =
              RouteFeasible(route1, demand, capacity) &&
              RouteFeasible(route2, demand, capacity);

            if (originalFeasible) {
              double routeLoad = 0;
              for (int i = 0; i < x1; i++)
                routeLoad += demand[route1.Cities[i]];
              for (int i = x2; i < route2.Cities.Count; i++)
                routeLoad += demand[route2.Cities[i]];

              if (routeLoad > capacity.Value) {
                feasible = false;
              } else {
                routeLoad = 0;
                for (int i = 0; i < x2; i++)
                  routeLoad += demand[route2.Cities[i]];
                for (int i = x1; i < route1.Cities.Count; i++)
                  routeLoad += demand[route1.Cities[i]];

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

          if (feasible) {
            int count = route1.Cities.Count - x1;
            List<int> segmentX1 = new List<int>();
            if (count > 0) {
              segmentX1 = route1.Cities.GetRange(x1, count);
              route1.Cities.RemoveRange(x1, count);
            }

            count = route2.Cities.Count - x2;
            List<int> segmentX2 = new List<int>();
            if (count > 0) {
              segmentX2 = route2.Cities.GetRange(x2, count);
              route2.Cities.RemoveRange(x2, count);
            }

            route1.Cities.AddRange(segmentX2);
            route2.Cities.AddRange(segmentX1);

            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);
    }
  }
}