#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 HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Selection;
using HeuristicLab.Common;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Algorithms.NSGA2 {
public class RankAndCrowdingSorter : AlgorithmOperator {
public ValueLookupParameter MaximizationParameter {
get { return (ValueLookupParameter)Parameters["Maximization"]; }
}
public ScopeTreeLookupParameter QualitiesParameter {
get { return (ScopeTreeLookupParameter)Parameters["Qualities"]; }
}
public ScopeTreeLookupParameter RankParameter {
get { return (ScopeTreeLookupParameter)Parameters["Rank"]; }
}
public ScopeTreeLookupParameter CrowdingDistanceParameter {
get { return (ScopeTreeLookupParameter)Parameters["CrowdingDistance"]; }
}
[StorableConstructor]
protected RankAndCrowdingSorter(bool deserializing) : base(deserializing) { }
protected RankAndCrowdingSorter(RankAndCrowdingSorter original, Cloner cloner) : base(original, cloner) { }
public RankAndCrowdingSorter()
: base() {
Parameters.Add(new ValueLookupParameter("Maximization", "For each objective a value that is true if that objective should be maximized, or false if it should be minimized."));
Parameters.Add(new ScopeTreeLookupParameter("Qualities", "The vector of quality values."));
Parameters.Add(new ScopeTreeLookupParameter("Rank", "The rank of a solution (to which front it belongs)."));
Parameters.Add(new ScopeTreeLookupParameter("CrowdingDistance", "The crowding distance of a solution in a population."));
FastNonDominatedSort fastNonDominatedSort = new FastNonDominatedSort();
UniformSubScopesProcessor subScopesProcessor = new UniformSubScopesProcessor();
CrowdingDistanceAssignment crowdingDistanceAssignment = new CrowdingDistanceAssignment();
CrowdedComparisonSorter crowdedComparisonSorter = new CrowdedComparisonSorter();
MergingReducer mergingReducer = new MergingReducer();
fastNonDominatedSort.MaximizationParameter.ActualName = MaximizationParameter.Name;
fastNonDominatedSort.QualitiesParameter.ActualName = QualitiesParameter.Name;
fastNonDominatedSort.RankParameter.ActualName = RankParameter.Name;
crowdingDistanceAssignment.CrowdingDistanceParameter.ActualName = CrowdingDistanceParameter.Name;
crowdingDistanceAssignment.QualitiesParameter.ActualName = QualitiesParameter.Name;
crowdedComparisonSorter.CrowdingDistanceParameter.ActualName = CrowdingDistanceParameter.Name;
crowdedComparisonSorter.RankParameter.ActualName = RankParameter.Name;
OperatorGraph.InitialOperator = fastNonDominatedSort;
fastNonDominatedSort.Successor = subScopesProcessor;
subScopesProcessor.Operator = crowdingDistanceAssignment;
crowdingDistanceAssignment.Successor = crowdedComparisonSorter;
crowdedComparisonSorter.Successor = null;
subScopesProcessor.Successor = mergingReducer;
mergingReducer.Successor = null;
}
public override IDeepCloneable Clone(Cloner cloner) {
return new RankAndCrowdingSorter(this, cloner);
}
}
}