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source: branches/2839_HiveProjectManagement/HeuristicLab.Problems.TestFunctions.MultiObjective/3.3/Calculators/GenerationalDistance.cs @ 15761

Last change on this file since 15761 was 14111, checked in by mkommend, 8 years ago

#1087: Change plugin and folder name from HeuristicLab.Problems.MultiObjectiveTestFunctions to HeuristicLab.Problems.Testfunctions.MultiObjective and adapted namespaces and projects accordingly.

File size: 2.0 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 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
21using System;
22using System.Collections.Generic;
23using System.Linq;
24
25namespace HeuristicLab.Problems.TestFunctions.MultiObjective {
26
27  /// <summary>
28  /// The generational Distance is defined as the pth-root of the sum of all d[i]^(p) divided by the size of the front
29  ///  where d[i] is the minimal distance the ith point of the evaluated front has to any point in the optimal pareto front.   
30  ///  p is a dampening factor and is normally set to 1.
31  ///  http://shodhganga.inflibnet.ac.in/bitstream/10603/15070/28/28_appendix_h.pdf
32  /// </summary>
33  public static class GenerationalDistance {
34
35    public static double Calculate(IEnumerable<double[]> front, IEnumerable<double[]> optimalFront, double p) {
36      if (front == null || optimalFront == null) throw new ArgumentNullException("Fronts must not be null.");
37      if (!front.Any()) throw new ArgumentException("Front must not be empty.");
38      if (p == 0.0) throw new ArgumentException("p must not be 0.0.");
39
40
41      double sum = front.Select(r => Math.Pow(Utilities.MinimumDistance(r, optimalFront), p)).Sum();
42      return Math.Pow(sum, 1 / p) / front.Count();
43    }
44
45  }
46}
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