#region License Information /* HeuristicLab * Copyright (C) 2002-2018 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 HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Problems.TestFunctions.MultiObjective { [Item("DTLZ8", "Testfunction as defined as DTLZ7 in http://repository.ias.ac.in/81671/ [30.11.15]. There has been a renumbering therefore the numbers do not match")] [StorableClass] public class DTLZ8 : DTLZ, IConstrainedTestFunction { public static double[] IllegalValue(int size, bool[] maximization) { double[] res = new double[size]; for (int i = 0; i < size; i++) { res[i] = maximization[i] ? Double.MinValue : Double.MaxValue; } return res; } [StorableConstructor] protected DTLZ8(bool deserializing) : base(deserializing) { } protected DTLZ8(DTLZ8 original, Cloner cloner) : base(original, cloner) { } public override IDeepCloneable Clone(Cloner cloner) { return new DTLZ8(this, cloner); } public DTLZ8() : base() { } public override double[] Evaluate(RealVector r, int objectives) { if (r.Length < 10 * objectives) throw new Exception("The dimensionality of the problem(ProblemSize) must be larger than ten times the number of objectives "); double n = r.Length; double M = objectives; double ratio = n / M; double[] res = new double[objectives]; for (int j = 0; j < objectives; j++) { double sum = 0; for (int i = (int)(j * ratio); i < (j + 1) + ratio; i++) { sum += r[i]; } sum /= (int)ratio; res[j] = sum; } for (int j = 0; j < M - 1; j++) { if (res[objectives - 1] + 4 * res[j] - 1 < 0) return IllegalValue(objectives, GetMaximization(objectives)); } double min = Double.PositiveInfinity; for (int i = 0; i < res.Length - 1; i++) { for (int j = 0; j < i; j++) { double d = res[i] + res[j]; if (min < d) min = d; } } if (2 * res[objectives - 1] + min - 1 < 0) return IllegalValue(objectives, GetMaximization(objectives)); return res; } public double[] CheckConstraints(RealVector r, int objectives) { if (r.Length < 10 * objectives) throw new Exception("The dimensionality of the problem(ProblemSize) must be larger than ten times the number of objectives "); double n = r.Length; double M = objectives; double ratio = n / M; double[] res = new double[objectives]; double[] constraints = new double[objectives]; for (int j = 0; j < objectives; j++) { double sum = 0; for (int i = (int)(j * ratio); i < (j + 1) + ratio; i++) { sum += r[i]; } sum /= (int)ratio; res[j] = sum; } for (int j = 0; j < M - 1; j++) { double d1 = res[objectives - 1] + 4 * res[j] - 1; constraints[j] = d1 < 0 ? -d1 : 0; } double min = Double.PositiveInfinity; for (int i = 0; i < res.Length - 1; i++) { for (int j = 0; j < i; j++) { double d2 = res[i] + res[j]; if (min < d2) min = d2; } } double d = 2 * res[objectives - 1] + min - 1; constraints[constraints.Length - 1] = d < 0 ? -d : 0; return constraints; } } }