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source: branches/ProblemRefactoring/HeuristicLab.Encodings.LinearLinkageEncoding/3.3/Crossovers/GroupCrossover.cs @ 14778

Last change on this file since 14778 was 12650, checked in by abeham, 9 years ago

#2319: integrated into trunk

File size: 2.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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 System;
23using System.Collections.Generic;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27
28namespace HeuristicLab.Encodings.LinearLinkageEncoding {
29  [Item("Group Crossover", "The Group Crossover is implemented as described in Korkmaz, E.E. 2010. Multi-objective Genetic Algorithms for grouping problems. Applied Intelligence 33(2), pp. 179-192.")]
30  [StorableClass]
31  public sealed class GroupCrossover : LinearLinkageCrossover {
32
33    [StorableConstructor]
34    private GroupCrossover(bool deserializing) : base(deserializing) { }
35    private GroupCrossover(GroupCrossover original, Cloner cloner) : base(original, cloner) { }
36    public GroupCrossover() { }
37
38    public override IDeepCloneable Clone(Cloner cloner) {
39      return new GroupCrossover(this, cloner);
40    }
41
42    public static LinearLinkage Apply(IRandom random, LinearLinkage p1, LinearLinkage p2) {
43      var length = p1.Length;
44      var child = new LinearLinkage(length);
45      var endNodes = new HashSet<int>();
46      for (var i = 0; i < length; i++) {
47        if ((p1[i] == i && p2[i] == i)
48          || ((p1[i] == i || p2[i] == i) && random.NextDouble() < 0.5)) {
49          child[i] = i;
50          endNodes.Add(i);
51        }
52      }
53      for (var i = 0; i < length; i++) {
54        if (endNodes.Contains(i)) continue;
55        var p1End = endNodes.Contains(p1[i]);
56        var p2End = endNodes.Contains(p2[i]);
57        if ((p1End && p2End) || (!p1End && !p2End)) {
58          child[i] = random.NextDouble() < 0.5 ? p1[i] : p2[i];
59        } else if (p1End) {
60          child[i] = p1[i];
61        } else {
62          child[i] = p2[i];
63        }
64      }
65      child.LinearizeTreeStructures();
66      return child;
67    }
68
69    protected override LinearLinkage Cross(IRandom random, ItemArray<LinearLinkage> parents) {
70      if (parents.Length != 2) throw new InvalidOperationException(Name + ": Can only cross exactly two parents.");
71      return Apply(random, parents[0], parents[1]);
72    }
73  }
74}
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