#region License Information
/* HeuristicLab
* Copyright (C) 2002-2016 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 Schwefel function (sine root) is implemented as described in Affenzeller, M. and Wagner, S. 2005. Offspring Selection: A New Self-Adaptive Selection Scheme for Genetic Algorithms. Ribeiro, B., Albrecht, R. F., Dobnikar, A., Pearson, D. W., and Steele, N. C. (eds.). Adaptive and Natural Computing Algorithms, pp. 218-221, Springer.
///
[Item("SchwefelEvaluator", "Evaluates the Schwefel function (sine root) on a given point. In the given bounds [-500;500] the optimum of this function is close to 0 at (420.968746453712,420.968746453712,...,420.968746453712). It is implemented as described in Affenzeller, M. and Wagner, S. 2005. Offspring Selection: A New Self-Adaptive Selection Scheme for Genetic Algorithms. Ribeiro, B., Albrecht, R. F., Dobnikar, A., Pearson, D. W., and Steele, N. C. (eds.). Adaptive and Natural Computing Algorithms, pp. 218-221, Springer.")]
[StorableClass]
public class SchwefelEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
public override string FunctionName { get { return "Schwefel"; } }
///
/// Returns false as the Schwefel (sine root) 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[,] { { -500, 500 } }); }
}
///
/// 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 SchwefelEvaluator(bool deserializing) : base(deserializing) { }
protected SchwefelEvaluator(SchwefelEvaluator original, Cloner cloner) : base(original, cloner) { }
public SchwefelEvaluator() : base() { }
public override IDeepCloneable Clone(Cloner cloner) {
return new SchwefelEvaluator(this, cloner);
}
public override RealVector GetBestKnownSolution(int dimension) {
return null;
}
///
/// Evaluates the test function for a specific .
///
/// N-dimensional point for which the test function should be evaluated.
/// The result value of the Schwefel function at the given point.
public static double Apply(RealVector point) {
double result = 418.982887272433 * point.Length;
for (int i = 0; i < point.Length; i++)
result -= point[i] * Math.Sin(Math.Sqrt(Math.Abs(point[i])));
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 Schwefel function at the given point.
public override double Evaluate(RealVector point) {
return Apply(point);
}
}
}