1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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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 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using System.Linq;
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25 |
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26 | namespace HeuristicLab.Problems.MultiObjectiveTestFunctions {
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27 |
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28 | /// <summary>
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29 | /// Crowding distance d(x,A) is usually defined between a point x and a set of points A
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30 | /// d(x,A) is then a weighted sum over all dimensions where for each dimension the next larger and the next smaller Point to x are subtracted
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31 | /// I extended the concept and defined the Crowding distance of a front A as the mean of the crowding distances of every point x in A
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32 | /// C(A) = mean(d(x,A)) where x in A and d(x,A) is not infinite
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33 | /// </summary>
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34 | public static class Crowding {
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35 |
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36 | public static double Calculate(IEnumerable<double[]> front, double[,] bounds) {
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37 |
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38 | double[] pointsums = new double[front.Count()];
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39 |
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40 | for (int dim = 0; dim < front.First().Length; dim++) {
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41 |
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42 | double[] arr = front.Select(x => x[dim]).ToArray();
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43 | Array.Sort(arr);
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44 |
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45 | double fmax = bounds[dim % bounds.GetLength(0), 1];
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46 | double fmin = bounds[dim % bounds.GetLength(0), 0];
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47 |
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48 | int pointIdx = 0;
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49 | foreach (double[] point in front) {
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50 | double d = 0;
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51 | int pos = Array.BinarySearch(arr, point[dim]);
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52 | if (pos != 0 && pos != arr.Count() - 1) {
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53 | d = (arr[pos + 1] - arr[pos - 1]) / (fmax - fmin);
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54 | pointsums[pointIdx++] += d;
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55 | }
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56 | }
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57 | }
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58 |
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59 | double sum = 0;
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60 | int c = 0;
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61 | foreach (double d in pointsums) {
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62 | if (!Double.IsInfinity(d)) {
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63 | sum += d;
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64 | c++;
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65 | }
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66 | }
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67 |
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68 | return c == 0 ? Double.PositiveInfinity : sum / c;
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69 | }
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70 |
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71 | }
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72 | }
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