1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2016 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.Core;
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25 | using HeuristicLab.Encodings.PermutationEncoding;
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26 | using HeuristicLab.Optimization;
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27 |
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28 | namespace HeuristicLab.Algorithms.MemPR.Permutation.SolutionModel.Univariate {
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29 | public enum ModelBiasOptions { Rank, Fitness }
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30 |
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31 | public static class Trainer {
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32 | public static ISolutionModel<Encodings.PermutationEncoding.Permutation> TrainUnbiased(IRandom random, IList<Encodings.PermutationEncoding.Permutation> pop, int N) {
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33 | ISolutionModel<Encodings.PermutationEncoding.Permutation> model;
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34 | switch (pop[0].PermutationType) {
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35 | case PermutationTypes.Absolute:
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36 | model = UnivariateAbsoluteModel.CreateUnbiased(random, pop, N);
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37 | break;
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38 | case PermutationTypes.RelativeDirected:
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39 | model = UnivariateRelativeModel.CreateDirected(random, pop, N);
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40 | break;
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41 | case PermutationTypes.RelativeUndirected:
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42 | model = UnivariateRelativeModel.CreateUndirected(random, pop, N);
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43 | break;
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44 | default: throw new ArgumentException(string.Format("unknown permutation type {0}", pop[0].PermutationType));
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45 | }
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46 | return model;
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47 | }
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48 |
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49 | public static ISolutionModel<Encodings.PermutationEncoding.Permutation> TrainBiased(ModelBiasOptions modelBias, IRandom random, bool maximization, IList<Encodings.PermutationEncoding.Permutation> pop, IList<double> qualities, int N) {
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50 | if (pop.Count != qualities.Count) throw new ArgumentException("Unequal length of population and qualities list.");
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51 | ISolutionModel<Encodings.PermutationEncoding.Permutation> model;
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52 | switch (pop[0].PermutationType) {
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53 | case PermutationTypes.Absolute:
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54 | if (modelBias == ModelBiasOptions.Rank)
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55 | model = UnivariateAbsoluteModel.CreateWithRankBias(random, maximization, pop, qualities, N);
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56 | else if (modelBias == ModelBiasOptions.Fitness)
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57 | model = UnivariateAbsoluteModel.CreateWithFitnessBias(random, maximization, pop, qualities, N);
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58 | else throw new ArgumentException(string.Format("Bias type {0} is not supported.", modelBias));
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59 | break;
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60 | case PermutationTypes.RelativeDirected:
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61 | if (modelBias == ModelBiasOptions.Rank)
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62 | model = UnivariateRelativeModel.CreateDirectedWithRankBias(random, maximization, pop, qualities, N);
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63 | else if (modelBias == ModelBiasOptions.Fitness)
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64 | model = UnivariateRelativeModel.CreateDirectedWithFitnessBias(random, maximization, pop, qualities, N);
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65 | else throw new ArgumentException(string.Format("Bias type {0} is not supported.", modelBias));
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66 | break;
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67 | case PermutationTypes.RelativeUndirected:
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68 | if (modelBias == ModelBiasOptions.Rank)
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69 | model = UnivariateRelativeModel.CreateUndirectedWithRankBias(random, maximization, pop, qualities, N);
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70 | else if (modelBias == ModelBiasOptions.Fitness)
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71 | model = UnivariateRelativeModel.CreateUndirectedWithFitnessBias(random, maximization, pop, qualities, N);
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72 | else throw new ArgumentException(string.Format("Bias type {0} is not supported.", modelBias));
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73 | break;
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74 | default: throw new ArgumentException(string.Format("unknown permutation type {0}", pop[0].PermutationType));
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75 | }
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76 | return model;
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77 | }
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78 | }
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79 | }
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