#region License Information /* HeuristicLab * Copyright (C) 2002-2013 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 Ackley function as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg /// is highly multimodal. It has a single global minimum at the origin with value 0. /// /// Returns false as the Ackley 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[,] { { -32.768, 32.768 } }); } } /// /// 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 AckleyEvaluator(bool deserializing) : base(deserializing) { } protected AckleyEvaluator(AckleyEvaluator original, Cloner cloner) : base(original, cloner) { } public AckleyEvaluator() : base() { } public override IDeepCloneable Clone(Cloner cloner) { return new AckleyEvaluator(this, cloner); } public override RealVector GetBestKnownSolution(int dimension) { return new RealVector(dimension); } /// /// Evaluates the Ackley function for a specific . /// /// N-dimensional point for which the test function should be evaluated. /// The result value of the Ackley function at the given point. public static double Apply(RealVector point) { double result; double val; val = 0; for (int i = 0; i < point.Length; i++) val += point[i] * point[i]; val /= point.Length; val = -0.2 * Math.Sqrt(val); result = 20 - 20 * Math.Exp(val); val = 0; for (int i = 0; i < point.Length; i++) val += Math.Cos(2 * Math.PI * point[i]); val /= point.Length; result += Math.E - Math.Exp(val); 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 Ackley function at the given point. public override double Evaluate(RealVector point) { return Apply(point); } } }