#region License Information
/* HeuristicLab
* Copyright (C) 2002-2015 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 HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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("65537F31-1671-453F-B79D-4DCEE40D0E4A")]
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(bool deserializing) : base(deserializing) { }
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;
}
}
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);
}
}
}