#region License Information /* HeuristicLab * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System; using System.Collections.Generic; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Operators; using HeuristicLab.Parameters; using HEAL.Attic; namespace HeuristicLab.Optimization.Operators { [Item("CrowdingDistanceAssignment", "Calculates the crowding distances for each sub-scope as described in Deb et al. 2002. A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), pp. 182-197.")] [StorableType("F7DF8B74-F1E6-45D6-A1A8-5D381F20B382")] public class CrowdingDistanceAssignment : SingleSuccessorOperator, IMultiObjectiveOperator { public ScopeTreeLookupParameter QualitiesParameter { get { return (ScopeTreeLookupParameter)Parameters["Qualities"]; } } public ScopeTreeLookupParameter CrowdingDistanceParameter { get { return (ScopeTreeLookupParameter)Parameters["CrowdingDistance"]; } } private void QualitiesParameter_DepthChanged(object sender, EventArgs e) { CrowdingDistanceParameter.Depth = QualitiesParameter.Depth; } [StorableConstructor] protected CrowdingDistanceAssignment(StorableConstructorFlag _) : base(_) { } protected CrowdingDistanceAssignment(CrowdingDistanceAssignment original, Cloner cloner) : base(original, cloner) { } public CrowdingDistanceAssignment() { Parameters.Add(new ScopeTreeLookupParameter("Qualities", "The vector of quality values.")); Parameters.Add(new ScopeTreeLookupParameter("CrowdingDistance", "Sets the crowding distance in each sub-scope.")); RegisterEventHandlers(); } [StorableHook(HookType.AfterDeserialization)] private void AfterDeserialization() { RegisterEventHandlers(); } private void RegisterEventHandlers() { QualitiesParameter.DepthChanged += new EventHandler(QualitiesParameter_DepthChanged); } public static void Apply(DoubleArray[] qualities, DoubleValue[] distances) { int populationSize = qualities.Length; int objectiveCount = qualities[0].Length; for (int m = 0; m < objectiveCount; m++) { Array.Sort(qualities, distances, new QualitiesComparer(m)); distances[0].Value = double.MaxValue; distances[populationSize - 1].Value = double.MaxValue; double minQuality = qualities[0][m]; double maxQuality = qualities[populationSize - 1][m]; for (int i = 1; i < populationSize - 1; i++) { distances[i].Value += (qualities[i + 1][m] - qualities[i - 1][m]) / (maxQuality - minQuality); } } } public override IOperation Apply() { DoubleArray[] qualities = QualitiesParameter.ActualValue.ToArray(); int populationSize = qualities.Length; DoubleValue[] distances = new DoubleValue[populationSize]; for (int i = 0; i < populationSize; i++) distances[i] = new DoubleValue(0); CrowdingDistanceParameter.ActualValue = new ItemArray(distances); Apply(qualities, distances); return base.Apply(); } private void Initialize(ItemArray distances) { for (int i = 0; i < distances.Length; i++) { if (distances[i] == null) distances[i] = new DoubleValue(0); else distances[i].Value = 0; } } [StorableType("30fd1927-b268-4ce7-8960-b04bfa83f1e6")] private class QualitiesComparer : IComparer { private int index; public QualitiesComparer(int index) { this.index = index; } #region IComparer Members public int Compare(DoubleArray x, DoubleArray y) { if (x[index] < y[index]) return -1; else if (x[index] > y[index]) return +1; else return 0; } #endregion } public override IDeepCloneable Clone(Cloner cloner) { return new CrowdingDistanceAssignment(this, cloner); } } }