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 System.Linq;
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25 | using HeuristicLab.Common;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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28 | using HeuristicLab.Random;
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29 |
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30 | namespace HeuristicLab.Encodings.LinearLinkageEncoding {
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31 | [Item("Lowest Index Max Crossover", "The Lowest Index Max Crossover (LIMX) is implemented as described in Ãlker, Ã., Ãzcan, E., Korkmaz, E. E. 2007. Linear linkage encoding in grouping problems: applications on graph coloring and timetabling. In Practice and Theory of Automated Timetabling VI, pp. 347-363. Springer Berlin Heidelberg.")]
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32 | [StorableType("3BA37E74-9FCE-4CB8-AA7C-5F6FC948D260")]
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33 | public sealed class LowestIndexMaxCrossover : LinearLinkageCrossover {
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34 |
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35 | [StorableConstructor]
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36 | private LowestIndexMaxCrossover(bool deserializing) : base(deserializing) { }
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37 | private LowestIndexMaxCrossover(LowestIndexMaxCrossover original, Cloner cloner) : base(original, cloner) { }
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38 | public LowestIndexMaxCrossover() { }
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39 |
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40 | public override IDeepCloneable Clone(Cloner cloner) {
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41 | return new LowestIndexMaxCrossover(this, cloner);
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42 | }
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43 |
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44 | public static LinearLinkage Apply(IRandom random, ItemArray<LinearLinkage> parents) {
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45 | var len = parents[0].Length;
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46 | var child = new LinearLinkage(len);
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47 | var remaining = new SortedSet<int>(Enumerable.Range(0, len));
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48 | do {
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49 | var groups = parents.Select(x => x.GetGroupForward(remaining.Min).Where(y => remaining.Contains(y)).ToList()).ToList();
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50 | var max = groups.Select((v, idx) => Tuple.Create(idx, v.Count)).MaxItems(x => x.Item2).SampleRandom(random).Item1;
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51 | var i = groups[max][0];
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52 | for (var k = 1; k < groups[max].Count; k++) {
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53 | child[i] = groups[max][k];
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54 | remaining.Remove(i);
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55 | i = child[i];
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56 | }
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57 | child[i] = i;
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58 | remaining.Remove(i);
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59 | } while (remaining.Count > 0);
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60 |
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61 | return child;
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62 | }
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63 |
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64 | protected override LinearLinkage Cross(IRandom random, ItemArray<LinearLinkage> parents) {
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65 | return Apply(random, parents);
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66 | }
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67 | }
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68 | }
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