#region License Information /* HeuristicLab * Copyright (C) 2002-2012 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 HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Operators; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Encodings.ParameterConfigurationEncoding { /// /// An operator which crosses two sets of parameters. /// [Item("ParameterConfigurationCrossover", "An operator which crosses two sets of parameters.")] [StorableClass] public class ParameterConfigurationCrossover : SingleSuccessorOperator, IParameterConfigurationCrossover { public override bool CanChangeName { get { return false; } } public ILookupParameter RandomParameter { get { return (LookupParameter)Parameters["Random"]; } } public ILookupParameter> ParentsParameter { get { return (ScopeTreeLookupParameter)Parameters["Parents"]; } } public ILookupParameter ChildParameter { get { return (ILookupParameter)Parameters["Child"]; } } public IValueLookupParameter IntValueCrossoverParameter { get { return (IValueLookupParameter)Parameters["IntValueCrossover"]; } } public IValueLookupParameter DoubleValueCrossoverParameter { get { return (IValueLookupParameter)Parameters["DoubleValueCrossover"]; } } /// /// Whether the problem is a maximization or minimization problem. /// public ValueLookupParameter MaximizationParameter { get { return (ValueLookupParameter)Parameters["Maximization"]; } } /// /// The quality of the parents. /// public ScopeTreeLookupParameter QualityParameter { get { return (ScopeTreeLookupParameter)Parameters["Quality"]; } } #region Constructors and Cloning public ParameterConfigurationCrossover() : base() { Parameters.Add(new LookupParameter("Random", "The pseudo random number generator which should be used for stochastic crossover operators.")); Parameters.Add(new ScopeTreeLookupParameter("Parents", "The parent vectors which should be crossed.")); Parameters.Add(new LookupParameter("Child", "The child vector resulting from the crossover.")); Parameters.Add(new ValueLookupParameter("Maximization", "Whether the problem is a maximization problem or not.")); Parameters.Add(new ScopeTreeLookupParameter("Quality", "The quality values of the parents.")); Parameters.Add(new ValueLookupParameter("IntValueCrossover", "")); Parameters.Add(new ValueLookupParameter("DoubleValueCrossover", "")); } [StorableConstructor] protected ParameterConfigurationCrossover(bool deserializing) : base(deserializing) { } protected ParameterConfigurationCrossover(ParameterConfigurationCrossover original, Cloner cloner) : base(original, cloner) { } public override IDeepCloneable Clone(Cloner cloner) { return new ParameterConfigurationCrossover(this, cloner); } #endregion public override IOperation Apply() { if (MaximizationParameter.ActualValue == null) throw new InvalidOperationException("ParameterConfigurationCrossover: Parameter " + MaximizationParameter.ActualName + " could not be found."); if (QualityParameter.ActualValue == null || QualityParameter.ActualValue.Length != 2) throw new InvalidOperationException("ParameterConfigurationCrossover: Parameter " + QualityParameter.ActualName + " could not be found, or not in the same quantity as there are parents."); ItemArray qualities = QualityParameter.ActualValue; bool maximization = MaximizationParameter.ActualValue.Value; ParameterConfigurationTree child1; ParameterConfigurationTree child2; if (maximization && qualities[0].Value >= qualities[1].Value || !maximization && qualities[0].Value <= qualities[1].Value) { child1 = (ParameterConfigurationTree)ParentsParameter.ActualValue[0].Clone(); child2 = ParentsParameter.ActualValue[1]; } else { child1 = (ParameterConfigurationTree)ParentsParameter.ActualValue[1].Clone(); child2 = ParentsParameter.ActualValue[0]; } Cross(RandomParameter.ActualValue, child1, child2, IntValueCrossoverParameter.ActualValue, DoubleValueCrossoverParameter.ActualValue); ChildParameter.ActualValue = child1; return base.Apply(); } public static void Apply(IRandom random, IOptimizable configuartion, IOptimizable other, IIntValueCrossover intValueCrossover, IDoubleValueCrossover doubleValueCrossover) { Cross(random, configuartion, other, intValueCrossover, doubleValueCrossover); } public static void Cross(IRandom random, IOptimizable configuration, IOptimizable other, IIntValueCrossover intValueCrossover, IDoubleValueCrossover doubleValueCrossover) { var vc = configuration as RangeValueConfiguration; var pc = configuration as IParameterConfiguration; if (vc != null) { var value = vc.ActualValue.Value; var range = vc.RangeConstraint; if (value is IntValue) { intValueCrossover.Apply(random, (IntValue)value, (IntValue)other.ActualValue.Value, (IntValueRange)range); } else if (value is PercentValue) { doubleValueCrossover.Apply(random, (PercentValue)value, (DoubleValue)other.ActualValue.Value, ((PercentValueRange)range).AsDoubleValueRange()); } else if (value is DoubleValue) { doubleValueCrossover.Apply(random, (DoubleValue)value, (DoubleValue)other.ActualValue.Value, (DoubleValueRange)range); } } else if (pc != null) { if (random.NextDouble() > 0.5) { pc.ActualValueConfigurationIndex = ((ParameterConfiguration)other).ActualValueConfigurationIndex; } pc.ActualValue = pc.ValueConfigurations[pc.ActualValueConfigurationIndex].ActualValue; } } } }