[3150] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[7259] | 3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[3150] | 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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[4722] | 23 | using HeuristicLab.Common;
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[3150] | 24 | using HeuristicLab.Core;
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[3154] | 25 | using HeuristicLab.Data;
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[3150] | 26 | using HeuristicLab.Encodings.RealVectorEncoding;
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| 27 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 28 |
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[3170] | 29 | namespace HeuristicLab.Problems.TestFunctions {
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[3150] | 30 | /// <summary>
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[3315] | 31 | /// The Ackley function as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg
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| 32 | /// is highly multimodal. It has a single global minimum at the origin with value 0.
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[3150] | 33 | /// </summary
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[3315] | 34 | [Item("AckleyEvaluator", "Evaluates the Ackley function on a given point. The optimum of this function is 0 at the origin. It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg.")]
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[3150] | 35 | [StorableClass]
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[3170] | 36 | public class AckleyEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
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[3150] | 37 | /// <summary>
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| 38 | /// Returns false as the Ackley function is a minimization problem.
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| 39 | /// </summary>
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| 40 | public override bool Maximization {
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| 41 | get { return false; }
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| 42 | }
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| 43 | /// <summary>
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[3154] | 44 | /// Gets the optimum function value (0).
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| 45 | /// </summary>
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| 46 | public override double BestKnownQuality {
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| 47 | get { return 0; }
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| 48 | }
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| 49 | /// <summary>
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[3150] | 50 | /// Gets the lower and upper bound of the function.
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| 51 | /// </summary>
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| 52 | public override DoubleMatrix Bounds {
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| 53 | get { return new DoubleMatrix(new double[,] { { -32.768, 32.768 } }); }
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| 54 | }
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| 55 | /// <summary>
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| 56 | /// Gets the minimum problem size (1).
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| 57 | /// </summary>
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| 58 | public override int MinimumProblemSize {
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| 59 | get { return 1; }
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| 60 | }
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| 61 | /// <summary>
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| 62 | /// Gets the (theoretical) maximum problem size (2^31 - 1).
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| 63 | /// </summary>
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| 64 | public override int MaximumProblemSize {
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| 65 | get { return int.MaxValue; }
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| 66 | }
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| 67 |
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[4722] | 68 | [StorableConstructor]
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| 69 | protected AckleyEvaluator(bool deserializing) : base(deserializing) { }
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| 70 | protected AckleyEvaluator(AckleyEvaluator original, Cloner cloner) : base(original, cloner) { }
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| 71 | public AckleyEvaluator() : base() { }
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| 72 |
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| 73 | public override IDeepCloneable Clone(Cloner cloner) {
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| 74 | return new AckleyEvaluator(this, cloner);
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| 75 | }
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| 76 |
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[3781] | 77 | public override RealVector GetBestKnownSolution(int dimension) {
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| 78 | return new RealVector(dimension);
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| 79 | }
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| 80 |
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[3150] | 81 | /// <summary>
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| 82 | /// Evaluates the Ackley function for a specific <paramref name="point"/>.
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| 83 | /// </summary>
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| 84 | /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
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| 85 | /// <returns>The result value of the Ackley function at the given point.</returns>
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| 86 | public static double Apply(RealVector point) {
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[3450] | 87 | double result;
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[3150] | 88 | double val;
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| 89 |
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| 90 | val = 0;
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| 91 | for (int i = 0; i < point.Length; i++)
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| 92 | val += point[i] * point[i];
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[3315] | 93 | val /= point.Length;
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| 94 | val = -0.2 * Math.Sqrt(val);
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[3450] | 95 | result = 20 - 20 * Math.Exp(val);
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[3150] | 96 |
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| 97 | val = 0;
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| 98 | for (int i = 0; i < point.Length; i++)
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| 99 | val += Math.Cos(2 * Math.PI * point[i]);
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[3315] | 100 | val /= point.Length;
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[3450] | 101 | result += Math.E - Math.Exp(val);
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[3150] | 102 | return (result);
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| 103 | }
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| 104 |
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| 105 | /// <summary>
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| 106 | /// Evaluates the test function for a specific <paramref name="point"/>.
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| 107 | /// </summary>
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| 108 | /// <remarks>Calls <see cref="Apply"/>.</remarks>
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| 109 | /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
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| 110 | /// <returns>The result value of the Ackley function at the given point.</returns>
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[9363] | 111 | public override double EvaluateFunction(RealVector point) {
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[3150] | 112 | return Apply(point);
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| 113 | }
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| 114 | }
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| 115 | }
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