1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 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 HeuristicLab.Common;
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23 | using HeuristicLab.Core;
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24 | using HeuristicLab.Data;
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25 | using HeuristicLab.Encodings.RealVectorEncoding;
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26 | using HeuristicLab.Optimization;
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27 | using HeuristicLab.Parameters;
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28 | using HEAL.Attic;
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29 |
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30 | namespace HeuristicLab.Problems.TestFunctions {
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31 | /// <summary>
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32 | /// A function that returns a random variable in [0;1) independent of the inputs.
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33 | /// </summary
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34 | [Item("RandomEvaluator", "Returns a random value in [0;1) that is independent of the inputs.")]
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35 | [StorableType("8D56248E-D85B-49C0-92C1-E1D53F729202")]
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36 | public class RandomEvaluator : SingleObjectiveTestFunctionProblemEvaluator, IStochasticOperator {
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37 | public override string FunctionName { get { return "Random"; } }
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38 | /// <summary>
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39 | /// It does not really matter.
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40 | /// </summary>
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41 | public override bool Maximization {
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42 | get { return false; }
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43 | }
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44 | /// <summary>
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45 | /// The minimum value that can be "found" is 0.
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46 | /// </summary>
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47 | public override double BestKnownQuality {
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48 | get { return 0; }
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49 | }
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50 | /// <summary>
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51 | /// Gets the lower and upper bound of the function.
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52 | /// </summary>
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53 | public override DoubleMatrix Bounds {
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54 | get { return new DoubleMatrix(new double[,] { { -100, 100 } }); }
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55 | }
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56 | /// <summary>
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57 | /// Gets the minimum problem size (1).
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58 | /// </summary>
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59 | public override int MinimumProblemSize {
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60 | get { return 1; }
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61 | }
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62 | /// <summary>
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63 | /// Gets the (theoretical) maximum problem size (2^31 - 1).
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64 | /// </summary>
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65 | public override int MaximumProblemSize {
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66 | get { return int.MaxValue; }
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67 | }
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68 |
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69 | public ILookupParameter<IRandom> RandomParameter {
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70 | get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
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71 | }
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72 |
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73 | [StorableConstructor]
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74 | protected RandomEvaluator(StorableConstructorFlag _) : base(_) { }
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75 | protected RandomEvaluator(RandomEvaluator original, Cloner cloner) : base(original, cloner) { }
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76 | public RandomEvaluator()
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77 | : base() {
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78 | Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));
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79 | }
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80 |
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81 | public override IDeepCloneable Clone(Cloner cloner) {
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82 | return new RandomEvaluator(this, cloner);
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83 | }
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84 |
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85 | public override RealVector GetBestKnownSolution(int dimension) {
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86 | return new RealVector(dimension);
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87 | }
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88 |
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89 | public override double Evaluate(RealVector point) {
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90 | return ExecutionContext == null ? new System.Random().NextDouble() : RandomParameter.ActualValue.NextDouble();
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91 | }
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92 | }
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93 | }
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