#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);
}
}
}