#region License Information /* HeuristicLab * Copyright (C) 2002-2012 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 Levy function is implemented as described on http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page2056.htm, last accessed April 12th, 2010. /// [Item("LevyEvaluator", "Evaluates the Levy function on a given point. The optimum of this function is 0 at (1,1,...,1). It is implemented as described on http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page2056.htm, last accessed April 12th, 2010.")] [StorableClass] public class LevyEvaluator : SingleObjectiveTestFunctionProblemEvaluator { /// /// Returns false as the Levy 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[,] { { -10, 10 } }); } } /// /// Gets the minimum problem size (2). /// public override int MinimumProblemSize { get { return 2; } } /// /// Gets the (theoretical) maximum problem size (2^31 - 1). /// public override int MaximumProblemSize { get { return int.MaxValue; } } [StorableConstructor] protected LevyEvaluator(bool deserializing) : base(deserializing) { } protected LevyEvaluator(LevyEvaluator original, Cloner cloner) : base(original, cloner) { } public LevyEvaluator() : base() { } public override IDeepCloneable Clone(Cloner cloner) { return new LevyEvaluator(this, cloner); } public override RealVector GetBestKnownSolution(int dimension) { if (dimension < 2) throw new ArgumentException(Name + ": This function is not defined for 1 dimension."); RealVector result = new RealVector(dimension); for (int i = 0; i < dimension; i++) result[i] = 1; return result; } /// /// Evaluates the test function for a specific . /// /// N-dimensional point for which the test function should be evaluated. /// The result value of the Levy function at the given point. public static double Apply(RealVector point) { int length = point.Length; double[] z = new double[length]; double s; for (int i = 0; i < length; i++) { z[i] = 1 + (point[i] - 1) / 4; } s = Math.Sin(Math.PI * z[0]); if (Math.Abs(s) < 1e-15) s = 0; // Math.Sin(Math.PI) == 0.00000000000000012246063538223773 s *= s; for (int i = 0; i < length - 1; i++) { s += (z[i] - 1) * (z[i] - 1) * (1 + 10 * Math.Pow(Math.Sin(Math.PI * z[i] + 1), 2)); } return s + Math.Pow(z[length - 1] - 1, 2) * (1 + Math.Pow(Math.Sin(2 * Math.PI * z[length - 1]), 2)); } /// /// Evaluates the test function for a specific . /// /// Calls . /// N-dimensional point for which the test function should be evaluated. /// The result value of the Levy function at the given point. public override double EvaluateFunction(RealVector point) { return Apply(point); } } }