#region License Information
/* HeuristicLab
* Copyright (C) 2002-2015 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 HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Encodings.MoveVectorEncoding;
using HeuristicLab.Data.MoveVectorData;
namespace HeuristicLab.Encodings.BinaryVectorEncoding {
///
/// N point crossover for move vectors.
///
///
/// It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg..
///
[Item("NPointCrossover", "N point crossover for move vectors. It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg.")]
[StorableClass]
public sealed class NPointCrossover : MoveVectorCrossover
{
///
/// Number of crossover points.
///
public IValueLookupParameter NParameter {
get { return (IValueLookupParameter)Parameters["N"]; }
}
[StorableConstructor]
private NPointCrossover(bool deserializing) : base(deserializing) { }
private NPointCrossover(NPointCrossover original, Cloner cloner) : base(original, cloner) { }
///
/// Initializes a new instance of
///
public NPointCrossover()
: base() {
Parameters.Add(new ValueLookupParameter("N", "Number of crossover points", new IntValue(2)));
}
public override IDeepCloneable Clone(Cloner cloner) {
return new NPointCrossover(this, cloner);
}
public static MoveVector Apply(IRandom random, MoveVector parent1, MoveVector parent2, IntValue n) {
if (parent1.Length != parent2.Length)
throw new ArgumentException("NPointCrossover: The parents are of different length.");
if (n.Value > parent1.Length)
throw new ArgumentException("NPointCrossover: There cannot be more breakpoints than the size of the parents.");
if (n.Value < 1)
throw new ArgumentException("NPointCrossover: N cannot be < 1.");
int length = parent1.Length;
MoveVector result = new MoveVector(length, parent1.MoveTypes);
int[] breakpoints = new int[n.Value];
//choose break points
List breakpointPool = new List();
for (int i = 0; i < length; i++)
breakpointPool.Add(i);
for (int i = 0; i < n.Value; i++) {
int index = random.Next(breakpointPool.Count);
breakpoints[i] = breakpointPool[index];
breakpointPool.RemoveAt(index);
}
Array.Sort(breakpoints);
//perform crossover
int arrayIndex = 0;
int breakPointIndex = 0;
bool firstParent = true;
while (arrayIndex < length) {
if (breakPointIndex < breakpoints.Length &&
arrayIndex == breakpoints[breakPointIndex]) {
breakPointIndex++;
firstParent = !firstParent;
}
if (firstParent)
result[arrayIndex] = parent1[arrayIndex];
else
result[arrayIndex] = parent2[arrayIndex];
arrayIndex++;
}
return result;
}
protected override MoveVector Cross(IRandom random, ItemArray parents) {
if (parents.Length != 2) throw new ArgumentException("ERROR in NPointCrossover: The number of parents is not equal to 2");
if (NParameter.ActualValue == null) throw new InvalidOperationException("NPointCrossover: Parameter " + NParameter.ActualName + " could not be found.");
return Apply(random, parents[0], parents[1], NParameter.ActualValue);
}
}
}