1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using HeuristicLab.Common;
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25 | using HeuristicLab.Core;
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26 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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27 |
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28 | namespace HeuristicLab.Encodings.LinearLinkageEncoding {
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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.")]
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30 | [StorableClass]
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31 | public sealed class GroupCrossover : LinearLinkageCrossover {
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32 |
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33 | [StorableConstructor]
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34 | private GroupCrossover(bool deserializing) : base(deserializing) { }
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35 | private GroupCrossover(GroupCrossover original, Cloner cloner) : base(original, cloner) { }
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36 | public GroupCrossover() { }
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37 |
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38 | public override IDeepCloneable Clone(Cloner cloner) {
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39 | return new GroupCrossover(this, cloner);
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40 | }
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41 |
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42 | public static LinearLinkage Apply(IRandom random, LinearLinkage p1, LinearLinkage p2) {
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43 | var length = p1.Length;
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44 | var child = new LinearLinkage(length);
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45 | var endNodes = new HashSet<int>();
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46 | for (var i = 0; i < length; i++) {
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47 | if ((p1[i] == i && p2[i] == i)
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48 | || ((p1[i] == i || p2[i] == i) && random.NextDouble() < 0.5)) {
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49 | child[i] = i;
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50 | endNodes.Add(i);
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51 | }
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52 | }
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53 | for (var i = 0; i < length; i++) {
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54 | if (endNodes.Contains(i)) continue;
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55 | var p1End = endNodes.Contains(p1[i]);
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56 | var p2End = endNodes.Contains(p2[i]);
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57 | if ((p1End && p2End) || (!p1End && !p2End)) {
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58 | child[i] = random.NextDouble() < 0.5 ? p1[i] : p2[i];
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59 | } else if (p1End) {
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60 | child[i] = p1[i];
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61 | } else {
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62 | child[i] = p2[i];
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63 | }
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64 | }
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65 | child.LinearizeTreeStructures();
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66 | return child;
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67 | }
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68 |
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69 | protected override LinearLinkage Cross(IRandom random, ItemArray<LinearLinkage> parents) {
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70 | if (parents.Length != 2) throw new InvalidOperationException(Name + ": Can only cross exactly two parents.");
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71 | return Apply(random, parents[0], parents[1]);
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72 | }
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73 | }
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74 | }
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