#region License Information
/* HeuristicLab
* Copyright (C) 2002-2010 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 Levy function is implemented as described on http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page2056.htm, last accessed April 12th, 2010.
///
[Item("LevyEvaluator", "Evaluates the Levy function on a given point. The optimum of this function is 0 at (1,1,...,1). It is implemented as described on http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page2056.htm, last accessed April 12th, 2010.")]
[StorableClass]
public class LevyEvaluator : SingleObjectiveTestFunctionProblemEvaluator {
///
/// Returns false as the Levy 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 (theoretical) maximum problem size (2^31 - 1).
///
public override int MaximumProblemSize {
get { return int.MaxValue; }
}
[StorableConstructor]
protected LevyEvaluator(bool deserializing) : base(deserializing) { }
protected LevyEvaluator(LevyEvaluator original, Cloner cloner) : base(original, cloner) { }
public LevyEvaluator() : base() { }
public override IDeepCloneable Clone(Cloner cloner) {
return new LevyEvaluator(this, cloner);
}
public override RealVector GetBestKnownSolution(int dimension) {
if (dimension < 2) throw new ArgumentException(Name + ": This function is not defined for 1 dimension.");
RealVector result = new RealVector(dimension);
for (int i = 0; i < dimension; i++) result[i] = 1;
return result;
}
///
/// Evaluates the test function for a specific .
///
/// N-dimensional point for which the test function should be evaluated.
/// The result value of the Levy function at the given point.
public static double Apply(RealVector point) {
int length = point.Length;
double[] z = new double[length];
double s;
for (int i = 0; i < length; i++) {
z[i] = 1 + (point[i] - 1) / 4;
}
s = Math.Sin(Math.PI * z[0]);
if (Math.Abs(s) < 1e-15) s = 0; // Math.Sin(Math.PI) == 0.00000000000000012246063538223773
s *= s;
for (int i = 0; i < length - 1; i++) {
s += (z[i] - 1) * (z[i] - 1) * (1 + 10 * Math.Pow(Math.Sin(Math.PI * z[i] + 1), 2));
}
return s + Math.Pow(z[length - 1] - 1, 2) * (1 + Math.Pow(Math.Sin(2 * Math.PI * z[length - 1]), 2));
}
///
/// Evaluates the test function for a specific .
///
/// Calls .
/// N-dimensional point for which the test function should be evaluated.
/// The result value of the Levy function at the given point.
protected override double EvaluateFunction(RealVector point) {
return Apply(point);
}
}
}