1 | #region License Information
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2 |
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3 | /* HeuristicLab
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4 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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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 |
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22 | #endregion
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23 |
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24 | using System;
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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.Problems.Binary {
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31 | [Item("Hierararchical If and only If problem (HIFF)", "Genome evaluated in nested subsets to see if each subset contains either all 0s or all 1s.")]
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32 | [StorableClass]
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33 | [Creatable(CreatableAttribute.Categories.CombinatorialProblems, Priority = 220)]
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34 | public class HIFFProblem : BinaryProblem {
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35 | [StorableConstructor]
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36 | protected HIFFProblem(bool deserializing) : base(deserializing) { }
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37 | protected HIFFProblem(HIFFProblem original, Cloner cloner)
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38 | : base(original, cloner) {
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39 | }
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40 | public override IDeepCloneable Clone(Cloner cloner) {
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41 | return new HIFFProblem(this, cloner);
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42 | }
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43 |
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44 | public override bool Maximization {
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45 | get { return true; }
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46 | }
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47 |
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48 | public HIFFProblem()
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49 | : base() {
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50 | Encoding.Length = 64;
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51 | }
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52 | // In the GECCO paper, Section 4.1
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53 | public override double Evaluate(BinaryVector individual, IRandom random) {
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54 | int[] level = new int[individual.Length];
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55 | int levelLength = individual.Length;
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56 |
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57 | // Initialize the level to the current solution
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58 | for (int i = 0; i < levelLength; i++) {
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59 | level[i] = Convert.ToInt32(individual[i]);
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60 | }
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61 | int power = 1;
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62 | int nextLength = levelLength / 2;
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63 | int total = 0;
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64 | int maximum = 0;
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65 |
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66 | // Keep going while the next level actual has bits in it
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67 | while (nextLength > 0) {
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68 | int[] nextLevel = new int[nextLength];
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69 | // Construct the next level using the current level
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70 | for (int i = 0; i + 1 < levelLength; i += 2) {
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71 | if (level[i] == level[i + 1] && level[i] != -1) {
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72 | // Score points for a correct setting at this level
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73 | total += power;
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74 | nextLevel[i / 2] = level[i];
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75 | } else {
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76 | nextLevel[i / 2] = -1;
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77 | }
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78 | // Keep track of the maximum possible score
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79 | maximum += power;
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80 | }
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81 | level = nextLevel;
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82 | levelLength = nextLength;
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83 | nextLength = levelLength / 2;
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84 | power *= 2;
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85 | }
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86 |
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87 | // Convert to percentage of total
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88 | return (double)total / maximum;
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89 | }
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90 | }
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91 | }
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