#region License Information /* HeuristicLab * Copyright (C) 2002-2016 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 HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Problems.TestFunctions.MultiObjective { [Item("CIGTAB", "to be aded")] [StorableClass] public class CIGTAB : MultiObjectiveTestFunction { protected override double[,] GetBounds(int objectives) { return new double[,] { { -10, 10 } }; } protected override bool[] GetMaximization(int objecitves) { return new bool[2]; } protected override double[] GetReferencePoint(int objecitves) { return new double[] { 11, 11 }; } protected override IEnumerable GetOptimalParetoFront(int objecitves) { List res = new List(); for (int i = 0; i <= 500; i++) { RealVector r = new RealVector(2); r[0] = 2 / 500.0 * i; r[1] = 2 / 500.0 * i; res.Add(this.Evaluate(r, 2)); } return res; } protected override double GetBestKnownHypervolume(int objectives) { return Hypervolume.Calculate(GetOptimalParetoFront(objectives), GetReferencePoint(objectives), GetMaximization(objectives)); } [StorableConstructor] protected CIGTAB(bool deserializing) : base(deserializing) { } protected CIGTAB(CIGTAB original, Cloner cloner) : base(original, cloner) { } public override IDeepCloneable Clone(Cloner cloner) { return new CIGTAB(this, cloner); } public CIGTAB() : base(minimumObjectives: 2, maximumObjectives: 2, minimumSolutionLength: 1, maximumSolutionLength: int.MaxValue) { } public override double[] Evaluate(RealVector r, int objectives) { if (objectives != 2) throw new ArgumentException("The CIGTAB problem must always have 2 objectives"); double x = r[0]; double a = 1000; double sum = x * x; for (int i = 1; i < r.Length - 1; i++) { sum += a * r[i] * r[i]; } sum += a * a * r[r.Length - 1] * r[r.Length - 1]; //objective1 double f0 = 1 / (a * a * r.Length) * sum; x = x - 2; sum = x * x; for (int i = 1; i < r.Length - 1; i++) { sum += a * (r[i] - 2) * (r[i] - 2); } sum += a * a * (r[r.Length - 1] - 2) * (r[r.Length - 1] - 2); //objective0 double f1 = 1 / (a * a * r.Length) * sum; return new double[] { f0, f1 }; } } }