1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)


4  *


5  * This file is part of HeuristicLab.


6  *


7  * HeuristicLab is free software: you can redistribute it and/or modify


8  * it under the terms of the GNU General Public License as published by


9  * the Free Software Foundation, either version 3 of the License, or


10  * (at your option) any later version.


11  *


12  * HeuristicLab is distributed in the hope that it will be useful,


13  * but WITHOUT ANY WARRANTY; without even the implied warranty of


14  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the


15  * GNU General Public License for more details.


16  *


17  * You should have received a copy of the GNU General Public License


18  * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.


19  */


20  #endregion


21  using System;


22  using System.Collections.Generic;


23  using HeuristicLab.Common;


24  using HeuristicLab.Core;


25  using HeuristicLab.Encodings.RealVectorEncoding;


26  using HEAL.Fossil;


27 


28  namespace HeuristicLab.Problems.TestFunctions.MultiObjective {


29  [Item("CIGTAB", "to be aded")]


30  [StorableType("1D78E29D469744A18A533909E3B7D57D")]


31  public class CIGTAB : MultiObjectiveTestFunction {


32  protected override double[,] GetBounds(int objectives) {


33  return new double[,] { { 10, 10 } };


34  }


35 


36  protected override bool[] GetMaximization(int objecitves) {


37  return new bool[2];


38  }


39 


40  protected override double[] GetReferencePoint(int objecitves) {


41  return new double[] { 11, 11 };


42  }


43 


44  protected override IEnumerable<double[]> GetOptimalParetoFront(int objecitves) {


45  List<double[]> res = new List<double[]>();


46  for (int i = 0; i <= 500; i++) {


47  RealVector r = new RealVector(2);


48  r[0] = 2 / 500.0 * i;


49  r[1] = 2 / 500.0 * i;


50  res.Add(this.Evaluate(r, 2));


51  }


52  return res;


53  }


54 


55  protected override double GetBestKnownHypervolume(int objectives) {


56  return Hypervolume.Calculate(GetOptimalParetoFront(objectives), GetReferencePoint(objectives), GetMaximization(objectives));


57  }


58 


59  [StorableConstructor]


60  protected CIGTAB(StorableConstructorFlag _) : base(_) { }


61  protected CIGTAB(CIGTAB original, Cloner cloner) : base(original, cloner) { }


62  public override IDeepCloneable Clone(Cloner cloner) {


63  return new CIGTAB(this, cloner);


64  }


65 


66  public CIGTAB() : base(minimumObjectives: 2, maximumObjectives: 2, minimumSolutionLength: 1, maximumSolutionLength: int.MaxValue) { }


67 


68  public override double[] Evaluate(RealVector r, int objectives) {


69  if (objectives != 2) throw new ArgumentException("The CIGTAB problem must always have 2 objectives");


70  double x = r[0];


71  double a = 1000;


72  double sum = x * x;


73  for (int i = 1; i < r.Length  1; i++) {


74  sum += a * r[i] * r[i];


75  }


76  sum += a * a * r[r.Length  1] * r[r.Length  1];


77 


78  //objective1


79  double f0 = 1 / (a * a * r.Length) * sum;


80 


81  x = x  2;


82  sum = x * x;


83  for (int i = 1; i < r.Length  1; i++) {


84  sum += a * (r[i]  2) * (r[i]  2);


85  }


86 


87  sum += a * a * (r[r.Length  1]  2) * (r[r.Length  1]  2);


88  //objective0


89  double f1 = 1 / (a * a * r.Length) * sum;


90 


91  return new double[] { f0, f1 };


92  }


93  }


94  }

