#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 HeuristicLab.Core;
using HeuristicLab.Encodings.PermutationEncoding;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Data;
using System.Collections.Generic;
using HeuristicLab.Problems.VehicleRouting.Variants;
using HeuristicLab.Common;
namespace HeuristicLab.Problems.VehicleRouting.Encodings.Zhu {
[Item("ZhuMergeCrossover2", "The Zhu Merge Crossover (Version 2). It is implemented as described in Zhu, K.Q. (2000). A New Genetic Algorithm For VRPTW. Proceedings of the International Conference on Artificial Intelligence.")]
[StorableClass]
public sealed class ZhuMergeCrossover2 : ZhuCrossover {
[StorableConstructor]
private ZhuMergeCrossover2(bool deserializing) : base(deserializing) { }
public ZhuMergeCrossover2()
: base() {
}
public override IDeepCloneable Clone(Cloner cloner) {
return new ZhuMergeCrossover2(this, cloner);
}
private ZhuMergeCrossover2(ZhuMergeCrossover2 original, Cloner cloner)
: base(original, cloner) {
}
protected override ZhuEncoding Crossover(IRandom random, ZhuEncoding parent1, ZhuEncoding parent2) {
List p1 = new List(parent1);
List p2 = new List(parent2);
ZhuEncoding child = parent2.Clone() as ZhuEncoding;
if (parent1.Length != parent2.Length)
return child;
int breakPoint = random.Next(child.Length);
int i = breakPoint;
int parent1Index = i;
int parent2Index = i;
DoubleArray dueTime = null;
if (ProblemInstance is ITimeWindowedProblemInstance) {
dueTime = (ProblemInstance as ITimeWindowedProblemInstance).DueTime;
}
do {
if (i == breakPoint) {
child[i] = p1[parent1Index];
} else {
if (dueTime != null &&
(dueTime[p1[parent1Index] + 1] <
dueTime[p2[parent2Index] + 1])) {
child[i] = p1[parent1Index];
} else {
child[i] = p2[parent2Index];
}
}
p1.Remove(child[i]);
if (parent1Index >= p1.Count)
parent1Index = 0;
p2.Remove(child[i]);
if (parent2Index >= p2.Count)
parent2Index = 0;
i = (i + 1) % child.Length;
} while (i != breakPoint);
return child;
}
}
}