#region License Information /* HeuristicLab * Copyright (C) 2002-2019 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.Encodings.RealVectorEncoding; using HEAL.Attic; namespace HeuristicLab.Problems.TestFunctions.MultiObjective { [Item("DTLZ4", "Testfunction as defined as DTLZ4 in http://repository.ias.ac.in/81671/ [30.11.15]")] [StorableType("2222AE43-E24A-4D30-93F3-496A1FE79B29")] public class DTLZ4 : DTLZ { protected override double GetBestKnownHypervolume(int objectives) { if (objectives == 2) return 121.0 - 1.0 / 4.0 * Math.PI; return -1; } [StorableConstructor] protected DTLZ4(StorableConstructorFlag _) : base(_) { } protected DTLZ4(DTLZ4 original, Cloner cloner) : base(original, cloner) { } public DTLZ4() : base() { } public override IDeepCloneable Clone(Cloner cloner) { return new DTLZ4(this, cloner); } public override double[] Evaluate(RealVector r, int objectives) { if (r.Length < objectives) { throw new ArgumentException("The dimensionality of the problem(ProblemSize) must be larger than or equal to the number of objectives"); } double[] res = new double[objectives]; //calculate g(Xm) double g = 0; for (int i = objectives; i < r.Length; i++) { double d = r[i] - 0.5; g += d * d; } //calculating f0...fM-1 for (int i = 0; i < objectives; i++) { double f = i == 0 ? 1 : (Math.Sin(Math.Pow(r[objectives - i - 1], 100) * Math.PI / 2)) * (1 + g); for (int j = 0; j < objectives - i - 1; j++) { f *= Math.Cos(Math.Pow(r[j], 100) * Math.PI / 2); } res[i] = f; } return res; } } }