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[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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[13620] | 21 | using System.Collections.Generic;
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[13562] | 22 |
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[14111] | 23 | namespace HeuristicLab.Problems.TestFunctions.MultiObjective {
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[13672] | 24 |
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[13562] | 25 | /// <summary>
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| 26 | /// The inverted generational Distance is defined as the mean of a all d[i]^(1/p),
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| 27 | /// where d[i] is the minimal distance the ith point of the optimal pareto front has to any point in the evaluated front.
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| 28 | /// </summary>
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[14018] | 29 | public static class InvertedGenerationalDistance {
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[13672] | 30 | public static double Calculate(IEnumerable<double[]> front, IEnumerable<double[]> optimalFront, double p) {
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| 31 | return GenerationalDistance.Calculate(optimalFront, front, p);
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[13562] | 32 | }
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| 33 | }
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| 34 | }
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