#region License Information /* HeuristicLab * Copyright (C) 2002-2011 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 HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Problems.VehicleRouting.Encodings.Prins { [Item("PrinsStochasticLSManipulator", "An operator which manipulates a VRP representation by using the stochastic version of the Prins local search. It is implemented as described in Prins, C. (2004). A simple and effective evolutionary algorithm for the vehicle routing problem. Computers & Operations Research, 12:1985-2002.")] [StorableClass] public sealed class PrinsStochasticLSManipulator : PrinsLSManipulator { public IValueParameter SampleSize { get { return (IValueParameter)Parameters["SampleSize"]; } } [StorableConstructor] private PrinsStochasticLSManipulator(bool deserializing) : base(deserializing) { } private PrinsStochasticLSManipulator(PrinsStochasticLSManipulator original, Cloner cloner) : base(original, cloner) { } public override IDeepCloneable Clone(Cloner cloner) { return new PrinsStochasticLSManipulator(this, cloner); } public PrinsStochasticLSManipulator() : base() { Parameters.Add(new ValueParameter("SampleSize", "The sample size.", new IntValue(200))); } protected override void Manipulate(IRandom random, PrinsEncoding individual) { List tours = individual.GetTours(DistanceMatrixParameter); bool improvement = false; int iterations = 0; do { improvement = false; double originalQuality = GetQuality(individual); PrinsEncoding child = null; int samples = 0; while (!improvement && samples < SampleSize.Value.Value) { int u = random.Next(Cities); int v = random.Next(Cities); child = Manipulate(individual, originalQuality, u, v); improvement = child != null; samples++; } if (improvement) { for (int i = 0; i < child.Length; i++) { individual[i] = child[i]; } } iterations++; } while (improvement && iterations < Iterations.Value.Value); } } }