#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);
}
}
}