#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 Booth function is implemented as described on http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page816.htm, last accessed April 12th, 2010. /// [Item("BoothEvaluator", "Evaluates the Booth function on a given point. The optimum of this function is 0 at (1,3). It is implemented as described on http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page816.htm, last accessed April 12th, 2010.")] [StorableClass] public class BoothEvaluator : SingleObjectiveTestFunctionProblemEvaluator { public override string FunctionName { get { return "Booth"; } } /// /// Returns false as the Booth 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 maximum problem size (2). /// public override int MaximumProblemSize { get { return 2; } } [StorableConstructor] protected BoothEvaluator(bool deserializing) : base(deserializing) { } protected BoothEvaluator(BoothEvaluator original, Cloner cloner) : base(original, cloner) { } public BoothEvaluator() : base() { } public override IDeepCloneable Clone(Cloner cloner) { return new BoothEvaluator(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[] { 1, 3 }); } /// /// Evaluates the test function for a specific . /// /// N-dimensional point for which the test function should be evaluated. /// The result value of the Booth function at the given point. public static double Apply(RealVector point) { return (point[0] + 2 * point[1] - 7) * (point[0] + 2 * point[1] - 7) + (2 * point[0] + point[1] - 5) * (2 * point[0] + point[1] - 5); } /// /// Evaluates the test function for a specific . /// /// Calls . /// N-dimensional point for which the test function should be evaluated. /// The result value of the Booth function at the given point. public override double Evaluate(RealVector point) { return Apply(point); } } }