1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | * and the BEACON Center for the Study of Evolution in Action.
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5 | *
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6 | * This file is part of HeuristicLab.
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7 | *
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8 | * HeuristicLab is free software: you can redistribute it and/or modify
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9 | * it under the terms of the GNU General Public License as published by
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10 | * the Free Software Foundation, either version 3 of the License, or
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11 | * (at your option) any later version.
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12 | *
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13 | * HeuristicLab is distributed in the hope that it will be useful,
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14 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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15 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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16 | * GNU General Public License for more details.
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17 | *
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18 | * You should have received a copy of the GNU General Public License
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19 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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20 | */
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21 | #endregion
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22 |
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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.Encodings.BinaryVectorEncoding;
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28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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29 |
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30 | namespace HeuristicLab.Algorithms.ParameterlessPopulationPyramid {
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31 | // This code is based off the publication
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32 | // B. W. Goldman and W. F. Punch, "Parameter-less Population Pyramid," GECCO, pp. 785–792, 2014
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33 | // and the original source code in C++11 available from: https://github.com/brianwgoldman/Parameter-less_Population_Pyramid
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34 | [StorableClass]
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35 | public class Population : DeepCloneable {
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36 | [Storable]
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37 | public List<BinaryVector> Solutions {
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38 | get;
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39 | private set;
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40 | }
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41 | [Storable]
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42 | public LinkageTree Tree {
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43 | get;
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44 | private set;
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45 | }
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46 |
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47 |
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48 | [StorableConstructor]
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49 | protected Population(bool deserializing) : base() { }
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50 |
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51 |
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52 | protected Population(Population original, Cloner cloner) : base(original, cloner) {
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53 | Solutions = original.Solutions.Select(cloner.Clone).ToList();
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54 | Tree = cloner.Clone(original.Tree);
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55 | }
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56 |
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57 | public override IDeepCloneable Clone(Cloner cloner) {
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58 | return new Population(this, cloner);
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59 | }
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60 |
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61 | public Population(int length, IRandom rand) {
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62 | Solutions = new List<BinaryVector>();
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63 | Tree = new LinkageTree(length, rand);
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64 | }
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65 | public void Add(BinaryVector solution) {
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66 | Solutions.Add(solution);
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67 | Tree.Add(solution);
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68 | }
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69 | }
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70 | }
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