[3150] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[16565] | 3 | * Copyright (C) 2002-2019 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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| 25 | using HeuristicLab.Data;
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[3154] | 26 | using HeuristicLab.Encodings.RealVectorEncoding;
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[16565] | 27 | using HEAL.Attic;
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[3150] | 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 Schwefel function (sine root) is implemented as described in Affenzeller, M. and Wagner, S. 2005. Offspring Selection: A New Self-Adaptive Selection Scheme for Genetic Algorithms. Ribeiro, B., Albrecht, R. F., Dobnikar, A., Pearson, D. W., and Steele, N. C. (eds.). Adaptive and Natural Computing Algorithms, pp. 218-221, Springer.
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[3150] | 32 | /// </summary>
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[3781] | 33 | [Item("SchwefelEvaluator", "Evaluates the Schwefel function (sine root) on a given point. In the given bounds [-500;500] the optimum of this function is close to 0 at (420.968746453712,420.968746453712,...,420.968746453712). It is implemented as described in Affenzeller, M. and Wagner, S. 2005. Offspring Selection: A New Self-Adaptive Selection Scheme for Genetic Algorithms. Ribeiro, B., Albrecht, R. F., Dobnikar, A., Pearson, D. W., and Steele, N. C. (eds.). Adaptive and Natural Computing Algorithms, pp. 218-221, Springer.")]
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[16565] | 34 | [StorableType("06AC1E53-E26F-4A41-9B4B-2EDC0B02B358")]
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[3170] | 35 | public class SchwefelEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
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[9980] | 36 | public override string FunctionName { get { return "Schwefel"; } }
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[3154] | 37 | /// <summary>
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[3318] | 38 | /// Returns false as the Schwefel (sine root) function is a minimization problem.
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[3154] | 39 | /// </summary>
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| 40 | public override bool Maximization {
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| 41 | get { return false; }
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[3150] | 42 | }
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[3154] | 43 | /// <summary>
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| 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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| 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[,] { { -500, 500 } }); }
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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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[3150] | 67 |
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[4722] | 68 | [StorableConstructor]
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[16565] | 69 | protected SchwefelEvaluator(StorableConstructorFlag _) : base(_) { }
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[4722] | 70 | protected SchwefelEvaluator(SchwefelEvaluator original, Cloner cloner) : base(original, cloner) { }
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| 71 | public SchwefelEvaluator() : base() { }
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| 72 |
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| 73 | public override IDeepCloneable Clone(Cloner cloner) {
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| 74 | return new SchwefelEvaluator(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 null;
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| 79 | }
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| 80 |
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[3150] | 81 | /// <summary>
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| 82 | /// Evaluates the test 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 Schwefel function at the given point.</returns>
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[3154] | 86 | public static double Apply(RealVector point) {
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[3150] | 87 | double result = 418.982887272433 * point.Length;
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| 88 | for (int i = 0; i < point.Length; i++)
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| 89 | result -= point[i] * Math.Sin(Math.Sqrt(Math.Abs(point[i])));
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| 90 | return (result);
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| 91 | }
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| 92 |
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| 93 | /// <summary>
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| 94 | /// Evaluates the test function for a specific <paramref name="point"/>.
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| 95 | /// </summary>
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| 96 | /// <remarks>Calls <see cref="Apply"/>.</remarks>
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| 97 | /// <param name="point">N-dimensional point for which the test function should be evaluated.</param>
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| 98 | /// <returns>The result value of the Schwefel function at the given point.</returns>
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[9407] | 99 | public override double Evaluate(RealVector point) {
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[3150] | 100 | return Apply(point);
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| 101 | }
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| 102 | }
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| 103 | }
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