#region License Information /* HeuristicLab * Copyright (C) 2002-2019 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 HEAL.Attic; namespace HeuristicLab.Problems.TestFunctions { /// /// The Beale function is defined for 2 dimensions with an optimum of 0 at (3, 0.5). /// It is implemented as described in Moré, J.J., Garbow, B., and Hillstrom, K. 1981. Testing unconstrained optimization software. ACM Transactions on Mathematical Software 7, pp. 136-140, ACM. /// [Item("BealeEvaluator", "Evaluates the Beale function on a given point. The optimum of this function is 0 at (3,0.5). It is implemented as described in Moré, J.J., Garbow, B., and Hillstrom, K. 1981. Testing unconstrained optimization software. ACM Transactions on Mathematical Software 7, pp. 136-140, ACM.")] [StorableType("EC1E155C-65ED-4603-A442-357ECC1E8F3D")] public class BealeEvaluator : SingleObjectiveTestFunctionProblemEvaluator { public override string FunctionName { get { return "Beale"; } } /// /// Returns false as the Beale 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[,] { { -4.5, 4.5 } }); } } /// /// Gets the minimum problem size (2). /// public override int MinimumProblemSize { get { return 2; } } /// /// Gets the maximum problem size (2). /// public override int MaximumProblemSize { get { return 2; } } [StorableConstructor] protected BealeEvaluator(StorableConstructorFlag _) : base(_) { } protected BealeEvaluator(BealeEvaluator original, Cloner cloner) : base(original, cloner) { } public BealeEvaluator() : base() { } public override IDeepCloneable Clone(Cloner cloner) { return new BealeEvaluator(this, cloner); } public override RealVector GetBestKnownSolution(int dimension) { if (dimension != 2) throw new ArgumentException(Name + ": This function is only defined for 2 dimensions.", "dimension"); return new RealVector(new double[] { 3, 0.5 }); } /// /// Evaluates the test function for a specific . /// /// N-dimensional point for which the test function should be evaluated. /// The result value of the Beale function at the given point. public static double Apply(RealVector point) { double x1 = point[0], x2 = point[1]; double f1 = 1.5 - x1 * (1 - x2); double f2 = 2.25 - x1 * (1 - x2 * x2); double f3 = 2.625 - x1 * (1 - x2 * x2 * x2); return (f1 * f1) + (f2 * f2) + (f3 * f3); } /// /// Evaluates the test function for a specific . /// /// Calls . /// N-dimensional point for which the test function should be evaluated. /// The result value of the Beale function at the given point. public override double Evaluate(RealVector point) { return Apply(point); } } }