#region License Information /* HeuristicLab * Copyright (C) 2002-2010 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.Collections.ObjectModel; using System.Linq; using HeuristicLab.Collections; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Optimization; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; using HeuristicLab.PluginInfrastructure; namespace HeuristicLab.Operators { /// /// Base class for multi crossover operators. /// [Item("MultiCrossover", "Base class for multi crossover operators.")] [StorableClass] public class MultiCrossover : MultiOperator, IStochasticOperator where T : class, ICrossover { public ValueLookupParameter ProbabilitiesParameter { get { return (ValueLookupParameter)Parameters["Probabilities"]; } } public ILookupParameter RandomParameter { get { return (ILookupParameter)Parameters["Random"]; } } public DoubleArray Probabilities { get { return ProbabilitiesParameter.Value; } set { ProbabilitiesParameter.Value = value; } } [StorableConstructor] protected MultiCrossover(bool deserializing) : base(deserializing) { } /// /// Initializes a new instance of with two parameters /// (Probabilities and Random). /// public MultiCrossover() : base() { Parameters.Add(new ValueLookupParameter("Probabilities", "The array of relative probabilities for each operator.", new DoubleArray())); Parameters.Add(new LookupParameter("Random", "The random number generator to use.")); Initialize(); } [StorableHook(HookType.AfterDeserialization)] private void Initialize() { Operators.ItemsAdded += new CollectionItemsChangedEventHandler>(Operators_ItemsAdded); Operators.ItemsRemoved += new CollectionItemsChangedEventHandler>(Operators_ItemsRemoved); Operators.ItemsMoved += new CollectionItemsChangedEventHandler>(Operators_ItemsMoved); IEnumerable types = ApplicationManager.Manager.GetTypes(typeof(T), true); foreach (Type type in types) { if (type != this.GetType()) Operators.Add((T)Activator.CreateInstance(type)); } } void Operators_ItemsMoved(object sender, CollectionItemsChangedEventArgs> e) { if (Probabilities != null) { DoubleArray oldProb = (DoubleArray)Probabilities.Clone(); foreach (IndexedItem old in e.OldItems) { foreach (IndexedItem item in e.Items) { if (old.Value == item.Value && item.Index < Probabilities.Length && old.Index < oldProb.Length) Probabilities[item.Index] = oldProb[old.Index]; } } } } void Operators_ItemsRemoved(object sender, CollectionItemsChangedEventArgs> e) { if (Probabilities != null && Probabilities.Length > Operators.Count) { List probs = new List(Probabilities.Cast()); var sorted = e.Items.OrderByDescending(x => x.Index); foreach (IndexedItem item in sorted) if (probs.Count > item.Index) probs.RemoveAt(item.Index); Probabilities = new DoubleArray(probs.ToArray()); } } private void Operators_ItemsAdded(object sender, HeuristicLab.Collections.CollectionItemsChangedEventArgs> e) { if (Probabilities != null && Probabilities.Length < Operators.Count) { DoubleArray probs = new DoubleArray(Operators.Count); double avg = 0; if (Probabilities.Length > 0) { for (int i = 0; i < Probabilities.Length; i++) avg += Probabilities[i]; avg /= (double)Probabilities.Length; } else avg = 1; var added = e.Items.OrderBy(x => x.Index).ToList(); int insertCount = 0; for (int i = 0; i < Operators.Count; i++) { if (insertCount < added.Count && i == added[insertCount].Index) { probs[i] = avg; insertCount++; } else if (i - insertCount < Probabilities.Length) { probs[i] = Probabilities[i - insertCount]; } else probs[i] = avg; } Probabilities = probs; } } /// /// Applies an operator of the branches to the current scope with a /// specific probability. /// /// Thrown when the list of probabilites does not /// match the number of operators. /// A new operation with the operator that was selected followed by the current operator's successor. public override IOperation Apply() { IRandom random = RandomParameter.ActualValue; DoubleArray probabilities = ProbabilitiesParameter.ActualValue; if(probabilities.Length != Operators.Count) { throw new InvalidOperationException("MultiCrossover: The list of probabilities has to match the number of operators"); } double sum = 0; for (int i = 0; i < Operators.Count; i++) { sum += probabilities[i]; } double r = random.NextDouble() * sum; sum = 0; IOperator successor = null; for(int i = 0; i < Operators.Count; i++) { sum += probabilities[i]; if(sum > r) { successor = Operators[i]; break; } } OperationCollection next = new OperationCollection(base.Apply()); if (successor != null) { next.Insert(0, ExecutionContext.CreateChildOperation(successor)); } return next; } } }