#region License Information /* HeuristicLab * Copyright (C) 2002-2018 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.Collections.Generic; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Optimization; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Selection { [Item("CrowdedTournamentSelector", "Selects solutions using tournament selection by using the partial order defined in Deb et al. 2002. A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), pp. 182-197.")] [StorableClass] public class CrowdedTournamentSelector : Selector, IMultiObjectiveSelector, IStochasticOperator { public ILookupParameter MaximizationParameter { get { return (ILookupParameter)Parameters["Maximization"]; } } public IValueLookupParameter NumberOfSelectedSubScopesParameter { get { return (IValueLookupParameter)Parameters["NumberOfSelectedSubScopes"]; } } protected IValueParameter CopySelectedParameter { get { return (IValueParameter)Parameters["CopySelected"]; } } public ILookupParameter RandomParameter { get { return (ILookupParameter)Parameters["Random"]; } } public ILookupParameter> QualitiesParameter { get { return (ILookupParameter>)Parameters["Qualities"]; } } public IScopeTreeLookupParameter RankParameter { get { return (IScopeTreeLookupParameter)Parameters["Rank"]; } } public IScopeTreeLookupParameter CrowdingDistanceParameter { get { return (IScopeTreeLookupParameter)Parameters["CrowdingDistance"]; } } public IValueLookupParameter GroupSizeParameter { get { return (IValueLookupParameter)Parameters["GroupSize"]; } } public BoolValue CopySelected { get { return CopySelectedParameter.Value; } set { CopySelectedParameter.Value = value; } } [StorableConstructor] protected CrowdedTournamentSelector(bool deserializing) : base(deserializing) { } protected CrowdedTournamentSelector(CrowdedTournamentSelector original, Cloner cloner) : base(original, cloner) { } public CrowdedTournamentSelector() : base() { Parameters.Add(new LookupParameter("Maximization", "For each objective determines whether it should be maximized or minimized.")); Parameters.Add(new ValueLookupParameter("NumberOfSelectedSubScopes", "The number of sub-scopes that should be selected.")); Parameters.Add(new ValueParameter("CopySelected", "True if the selected scopes are to be copied (cloned) otherwise they're moved.")); Parameters.Add(new LookupParameter("Random", "The random number generator.")); Parameters.Add(new ScopeTreeLookupParameter("Qualities", "The solutions' qualities vector.")); Parameters.Add(new ScopeTreeLookupParameter("Rank", "The solutions' domination rank.")); Parameters.Add(new ScopeTreeLookupParameter("CrowdingDistance", "The solutions' crowding distance values.")); Parameters.Add(new ValueLookupParameter("GroupSize", "The size of the group from which the best will be chosen.", new IntValue(2))); CopySelectedParameter.Hidden = true; } protected override IScope[] Select(List scopes) { IRandom random = RandomParameter.ActualValue; List ranks = RankParameter.ActualValue.Select(x => x.Value).ToList(); List crowdingDistance = CrowdingDistanceParameter.ActualValue.Select(x => x.Value).ToList(); int count = NumberOfSelectedSubScopesParameter.ActualValue.Value; int groupSize = GroupSizeParameter.ActualValue.Value; bool copy = CopySelected.Value; IScope[] selected = new IScope[count]; for (int i = 0; i < count; i++) { int best = random.Next(scopes.Count); int index; for (int j = 1; j < groupSize; j++) { index = random.Next(scopes.Count); if (ranks[best] > ranks[index] || ranks[best] == ranks[index] && crowdingDistance[best] < crowdingDistance[index]) { best = index; } } if (copy) selected[i] = (IScope)scopes[best].Clone(); else { selected[i] = scopes[best]; scopes.RemoveAt(best); ranks.RemoveAt(best); crowdingDistance.RemoveAt(best); } } return selected; } public override IDeepCloneable Clone(Cloner cloner) { return new CrowdedTournamentSelector(this, cloner); } } }