#region License Information
/* HeuristicLab
* Copyright (C) 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 System.Collections.Generic;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Encodings.RealVectorEncoding;
using HEAL.Attic;
namespace HeuristicLab.Problems.TestFunctions.MultiObjective {
[Item("Kursawe", "Kursawe function from // http://darwin.di.uminho.pt/jecoli/index.php/Multiobjective_example [30.11.2015]")]
[StorableType("9D38092B-2C55-450E-A27A-2C28714745ED")]
public class Kursawe : MultiObjectiveTestFunction {
protected override double[,] GetBounds(int objectives) {
return new double[,] { { -5, 5 } };
}
protected override bool[] GetMaximization(int objecitves) {
return new bool[2];
}
protected override IEnumerable GetOptimalParetoFront(int objecitves) {
return ParetoFrontStore.GetParetoFront("Misc.ParetoFronts." + this.ItemName);
}
protected override double GetBestKnownHypervolume(int objectives) {
return Hypervolume.Calculate(GetOptimalParetoFront(objectives), GetReferencePoint(objectives), GetMaximization(objectives));
}
protected override double[] GetReferencePoint(int objectives) {
return new double[] { 11, 11 };
}
[StorableConstructor]
protected Kursawe(StorableConstructorFlag _) : base(_) { }
protected Kursawe(Kursawe original, Cloner cloner) : base(original, cloner) { }
public override IDeepCloneable Clone(Cloner cloner) {
return new Kursawe(this, cloner);
}
public Kursawe() : base(minimumObjectives: 2, maximumObjectives: 2, minimumSolutionLength: 3, maximumSolutionLength: int.MaxValue) { }
public override double[] Evaluate(RealVector r, int objectives) {
if (objectives != 2) throw new ArgumentException("The Kursawe problem must always have 2 objectives");
//objective 1
double f0 = 0.0;
for (int i = 0; i < r.Length - 1; i++) {
f0 += -10 * Math.Exp(-0.2 * Math.Sqrt(r[i] * r[i] + r[i + 1] * r[i + 1]));
}
//objective2
double f1 = 0.0;
for (int i = 0; i < r.Length; i++) {
f1 += Math.Pow(Math.Abs(r[i]), 0.8) + 5 * Math.Sin(Math.Pow(r[i], 3));
}
return new double[] { f0, f1 };
}
}
}