#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 }; } } }