[13672] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[16057] | 3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[13672] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 | using System;
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[13620] | 22 | using System.Collections.Generic;
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[14018] | 23 | using System.Linq;
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[13562] | 24 |
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[14111] | 25 | namespace HeuristicLab.Problems.TestFunctions.MultiObjective {
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[13562] | 26 |
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| 27 | /// <summary>
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[14030] | 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
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[13562] | 29 | /// where d[i] is the minimal distance the ith point of the evaluated front has to any point in the optimal pareto front.
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[14030] | 30 | /// p is a dampening factor and is normally set to 1.
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| 31 | /// http://shodhganga.inflibnet.ac.in/bitstream/10603/15070/28/28_appendix_h.pdf
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[13562] | 32 | /// </summary>
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[14018] | 33 | public static class GenerationalDistance {
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[13562] | 34 |
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[13672] | 35 | public static double Calculate(IEnumerable<double[]> front, IEnumerable<double[]> optimalFront, double p) {
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[14018] | 36 | if (front == null || optimalFront == null) throw new ArgumentNullException("Fronts must not be null.");
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| 37 | if (!front.Any()) throw new ArgumentException("Front must not be empty.");
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| 38 | if (p == 0.0) throw new ArgumentException("p must not be 0.0.");
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| 39 |
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| 40 |
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[14030] | 41 | double sum = front.Select(r => Math.Pow(Utilities.MinimumDistance(r, optimalFront), p)).Sum();
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| 42 | return Math.Pow(sum, 1 / p) / front.Count();
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[13562] | 43 | }
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| 44 |
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| 45 | }
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| 46 | }
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