#region License Information
/* HeuristicLab
* Copyright (C) 2002-2018 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);
}
}
}