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source: branches/VRP/HeuristicLab.Problems.VehicleRouting/3.4/Encodings/Potvin/Crossovers/PotvinInsertionBasedCrossover.cs @ 6752

Last change on this file since 6752 was 6752, checked in by svonolfe, 13 years ago

Added support for incremental evaluation to improve performance (#1177)

File size: 9.4 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
25using System.Collections.Generic;
26using HeuristicLab.Data;
27using System;
28using HeuristicLab.Parameters;
29using HeuristicLab.Problems.VehicleRouting.ProblemInstances;
30
31namespace HeuristicLab.Problems.VehicleRouting.Encodings.Potvin {
32  [Item("PotvinInsertionBasedCrossover", "The IBX crossover for VRP representations. It is implemented as described in Berger, J and Solois, M and Begin, R (1998). A hybrid genetic algorithm for the vehicle routing problem with time windows. LNCS 1418. Springer, London 114-127.")]
33  [StorableClass]
34  public sealed class PotvinInsertionBasedCrossover : PotvinCrossover {
35    public IValueParameter<IntValue> Length {
36      get { return (IValueParameter<IntValue>)Parameters["Length"]; }
37    }
38
39    [StorableConstructor]
40    private PotvinInsertionBasedCrossover(bool deserializing) : base(deserializing) { }
41    private PotvinInsertionBasedCrossover(PotvinInsertionBasedCrossover original, Cloner cloner)
42      : base(original, cloner) {
43    }
44    public override IDeepCloneable Clone(Cloner cloner) {
45      return new PotvinInsertionBasedCrossover(this, cloner);
46    }
47    public PotvinInsertionBasedCrossover()
48      : base() {
49      Parameters.Add(new ValueParameter<IntValue>("Length", "The maximum length of the replaced route.", new IntValue(1)));
50    }
51
52    private static int SelectRandomTourBiasedByLength(IRandom random, PotvinEncoding individual) {
53      int tourIndex = -1;
54
55      double sum = 0.0;
56      double[] probabilities = new double[individual.Tours.Count];
57      for (int i = 0; i < individual.Tours.Count; i++) {
58        probabilities[i] = 1.0 / ((double)individual.Tours[i].Stops.Count / (double)individual.Cities);
59        sum += probabilities[i];
60      }
61
62      double rand = random.NextDouble() * sum;
63      double cumulatedProbabilities = 0.0;
64      int index = 0;
65      while (tourIndex == -1 && index < probabilities.Length) {
66        if (cumulatedProbabilities <= rand && rand <= cumulatedProbabilities + probabilities[index])
67          tourIndex = index;
68
69        cumulatedProbabilities += probabilities[index];
70        index++;
71      }
72
73      return tourIndex;
74    }
75
76    private double CalculateCentroidDistance(Tour t1, Tour t2, DoubleMatrix coordinates) {
77      double xSum = 0;
78      double ySum = 0;
79      double c1X, c1Y, c2X, c2Y;
80
81      for (int i = 0; i < t1.Stops.Count; i++) {
82        xSum += coordinates[t1.Stops[i], 0];
83        ySum += coordinates[t1.Stops[i], 1];
84      }
85      c1X = xSum / t1.Stops.Count;
86      c1Y = ySum / t1.Stops.Count;
87
88      for (int i = 0; i < t2.Stops.Count; i++) {
89        xSum += coordinates[t2.Stops[i], 0];
90        ySum += coordinates[t2.Stops[i], 1];
91      }
92      c2X = xSum / t1.Stops.Count;
93      c2Y = ySum / t1.Stops.Count;
94
95      return Math.Sqrt(
96           (c1X - c2X) * (c1X - c2X) +
97           (c1Y - c2Y) * (c1Y - c2Y));
98    }
99
100    private double CalculateMeanCentroidDistance(Tour t1, IList<Tour> tours, DoubleMatrix coordinates) {
101      double sum = 0;
102
103      for (int i = 0; i < tours.Count; i++) {
104        sum += CalculateCentroidDistance(t1, tours[i], coordinates);
105      }
106
107      return sum / tours.Count;
108    }
109
110    private int SelectCityBiasedByNeighborDistance(IRandom random, Tour tour) {
111      int cityIndex = -1;
112
113      double sum = 0.0;
114      double[] probabilities = new double[tour.Stops.Count];
115      for (int i = 0; i < tour.Stops.Count; i++) {
116        int next;
117        if (i + 1 >= tour.Stops.Count)
118          next = 0;
119        else
120          next = tour.Stops[i + 1];
121        double distance = ProblemInstance.GetDistance(
122          tour.Stops[i], next);
123
124        int prev;
125        if (i - 1 < 0)
126          prev = 0;
127        else
128          prev = tour.Stops[i - 1];
129        distance += ProblemInstance.GetDistance(
130          tour.Stops[i], prev);
131
132        probabilities[i] = distance;
133        sum += probabilities[i];
134      }
135
136      double rand = random.NextDouble() * sum;
137      double cumulatedProbabilities = 0.0;
138      int index = 0;
139      while (cityIndex == -1 && index < probabilities.Length) {
140        if (cumulatedProbabilities <= rand && rand <= cumulatedProbabilities + probabilities[index])
141          cityIndex = index;
142
143        cumulatedProbabilities += probabilities[index];
144        index++;
145      }
146
147      return cityIndex;
148    }
149
150    private bool FindRouteInsertionPlace(
151      Tour tour,
152      int city, bool allowInfeasible, out int place) {
153      place = -1;
154
155      if (tour.Stops.Contains(city))
156        return false;
157
158      if (tour.Stops.Count == 0) {
159        place = 0;
160        return true;
161      }
162
163      double minDetour = 0;
164      VRPEvaluation eval = ProblemInstance.Evaluate(tour);
165      bool originalFeasible = ProblemInstance.Feasible(eval);
166
167      for (int i = 0; i <= tour.Stops.Count; i++) {
168        bool feasible;
169        double detour = ProblemInstance.GetInsertionCosts(eval, city, 0, i, out feasible);
170        if (feasible || allowInfeasible) {
171          if (place < 0 || detour < minDetour) {
172            place = i;
173            minDetour = detour;
174          }
175        }
176      }
177
178      return place >= 0;
179    }
180
181    private ICollection<int> GetUnrouted(PotvinEncoding solution, int cities) {
182      HashSet<int> undiscovered = new HashSet<int>();
183      for (int i = 1; i <= cities; i++) {
184        undiscovered.Add(i);
185      }
186
187      foreach (Tour tour in solution.Tours) {
188        foreach (int city in tour.Stops)
189          undiscovered.Remove(city);
190      }
191
192      return undiscovered;
193    }
194
195    protected override PotvinEncoding Crossover(IRandom random, PotvinEncoding parent1, PotvinEncoding parent2) {
196      PotvinEncoding child = new PotvinEncoding(ProblemInstance);
197
198      bool allowInfeasible = AllowInfeasibleSolutions.Value.Value;
199
200      List<Tour> R1 = new List<Tour>();
201      PotvinEncoding p1Clone = parent1.Clone() as PotvinEncoding;
202
203      int length = Math.Min(Length.Value.Value, parent1.Tours.Count) + 1;
204      int k = random.Next(1, length);
205      for (int i = 0; i < k; i++) {
206        int index = SelectRandomTourBiasedByLength(random, p1Clone);
207        R1.Add(p1Clone.Tours[index]);
208        p1Clone.Tours.RemoveAt(index);
209      }
210
211      foreach (Tour r1 in R1) {
212        List<int> R2 = new List<int>();
213
214        double r = CalculateMeanCentroidDistance(r1, parent2.Tours, ProblemInstance.Coordinates);
215        foreach (Tour tour in parent2.Tours) {
216          if (CalculateCentroidDistance(r1, tour, ProblemInstance.Coordinates) <= r) {
217            R2.AddRange(tour.Stops);
218          }
219        }
220
221        Tour childTour = new Tour();
222        childTour.Stops.AddRange(r1.Stops);
223
224        //DESTROY - remove cities from r1
225        int removed = random.Next(1, r1.Stops.Count + 1);
226        for (int i = 0; i < removed; i++) {
227          childTour.Stops.RemoveAt(SelectCityBiasedByNeighborDistance(random, childTour));
228        }
229
230        //REPAIR - add cities from R2
231        int maxCount = random.Next(1, Math.Min(5, R2.Count));
232        int count = 0;
233
234        while (count < maxCount && R2.Count != 0) {
235          PotvinEncoding newChild = child.Clone() as PotvinEncoding;
236          newChild.Tours.Add(childTour);
237
238          int index = random.Next(R2.Count);
239          int city = R2[index];
240          R2.RemoveAt(index);
241
242          int place = -1;
243          bool found = FindRouteInsertionPlace(childTour, city, allowInfeasible, out place);
244          if (found) {
245            childTour.Stops.Insert(place, city);
246
247            if (!Repair(random, child, childTour, ProblemInstance, allowInfeasible)) {
248              childTour.Stops.RemoveAt(place);
249            } else {
250              count++;
251            }
252          }
253        }
254
255        child.Tours.Add(childTour);
256        Repair(random, child, childTour, ProblemInstance, allowInfeasible);
257      }
258
259      for (int i = 0; i < p1Clone.Tours.Count; i++) {
260        Tour childTour = p1Clone.Tours[i].Clone() as Tour;
261        child.Tours.Add(childTour);
262        Repair(random, child, childTour, ProblemInstance, allowInfeasible);
263      }
264
265      //route unrouted customers
266      child.Unrouted.AddRange(GetUnrouted(child, ProblemInstance.Cities.Value));
267      bool success = RouteUnrouted(child, allowInfeasible);
268
269      if (success || allowInfeasible)
270        return child;
271      else {
272        if (random.NextDouble() < 0.5)
273          return parent1.Clone() as PotvinEncoding;
274        else
275          return parent2.Clone() as PotvinEncoding;
276      }
277    }
278  }
279}
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