#region License Information /* HeuristicLab * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Encodings.RealVectorEncoding; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Problems.TestFunctions { /// /// 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. /// [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.")] [StorableClass] public class SchwefelEvaluator : SingleObjectiveTestFunctionProblemEvaluator { public override string FunctionName { get { return "Schwefel"; } } /// /// Returns false as the Schwefel (sine root) function is a minimization problem. /// public override bool Maximization { get { return false; } } /// /// Gets the optimum function value (0). /// public override double BestKnownQuality { get { return 0; } } /// /// Gets the lower and upper bound of the function. /// public override DoubleMatrix Bounds { get { return new DoubleMatrix(new double[,] { { -500, 500 } }); } } /// /// Gets the minimum problem size (1). /// public override int MinimumProblemSize { get { return 1; } } /// /// Gets the (theoretical) maximum problem size (2^31 - 1). /// public override int MaximumProblemSize { get { return int.MaxValue; } } [StorableConstructor] protected SchwefelEvaluator(bool deserializing) : base(deserializing) { } protected SchwefelEvaluator(SchwefelEvaluator original, Cloner cloner) : base(original, cloner) { } public SchwefelEvaluator() : base() { } public override IDeepCloneable Clone(Cloner cloner) { return new SchwefelEvaluator(this, cloner); } public override RealVector GetBestKnownSolution(int dimension) { return null; } /// /// Evaluates the test function for a specific . /// /// N-dimensional point for which the test function should be evaluated. /// The result value of the Schwefel function at the given point. public static double Apply(RealVector point) { double result = 418.982887272433 * point.Length; for (int i = 0; i < point.Length; i++) result -= point[i] * Math.Sin(Math.Sqrt(Math.Abs(point[i]))); return (result); } /// /// Evaluates the test function for a specific . /// /// Calls . /// N-dimensional point for which the test function should be evaluated. /// The result value of the Schwefel function at the given point. public override double Evaluate(RealVector point) { return Apply(point); } } }