[14278] | 1 | #region License Information
|
---|
| 2 | /* HeuristicLab
|
---|
| 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
|
---|
| 4 | *
|
---|
| 5 | * This file is part of HeuristicLab.
|
---|
| 6 | *
|
---|
| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
|
---|
| 8 | * it under the terms of the GNU General Public License as published by
|
---|
| 9 | * the Free Software Foundation, either version 3 of the License, or
|
---|
| 10 | * (at your option) any later version.
|
---|
| 11 | *
|
---|
| 12 | * HeuristicLab is distributed in the hope that it will be useful,
|
---|
| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
|
---|
| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
---|
| 15 | * GNU General Public License for more details.
|
---|
| 16 | *
|
---|
| 17 | * You should have received a copy of the GNU General Public License
|
---|
| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
|
---|
| 19 | */
|
---|
| 20 | #endregion
|
---|
| 21 |
|
---|
| 22 | using System;
|
---|
| 23 | using System.Collections.Generic;
|
---|
| 24 | using HeuristicLab.Common;
|
---|
| 25 | using HeuristicLab.Core;
|
---|
| 26 | using HeuristicLab.Data;
|
---|
| 27 | using HeuristicLab.Parameters;
|
---|
| 28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
|
---|
| 29 | using HeuristicLab.Encodings.MoveVectorEncoding;
|
---|
| 30 | using HeuristicLab.Data.MoveVectorData;
|
---|
| 31 |
|
---|
| 32 | namespace HeuristicLab.Encodings.BinaryVectorEncoding {
|
---|
| 33 | /// <summary>
|
---|
| 34 | /// N point crossover for move vectors.
|
---|
| 35 | /// </summary>
|
---|
| 36 | /// <remarks>
|
---|
| 37 | /// 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..
|
---|
| 38 | /// </remarks>
|
---|
| 39 | [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.")]
|
---|
| 40 | [StorableClass]
|
---|
| 41 | public sealed class NPointCrossover : MoveVectorCrossover
|
---|
| 42 | {
|
---|
| 43 | /// <summary>
|
---|
| 44 | /// Number of crossover points.
|
---|
| 45 | /// </summary>
|
---|
| 46 | public IValueLookupParameter<IntValue> NParameter {
|
---|
| 47 | get { return (IValueLookupParameter<IntValue>)Parameters["N"]; }
|
---|
| 48 | }
|
---|
| 49 |
|
---|
| 50 | [StorableConstructor]
|
---|
| 51 | private NPointCrossover(bool deserializing) : base(deserializing) { }
|
---|
| 52 | private NPointCrossover(NPointCrossover original, Cloner cloner) : base(original, cloner) { }
|
---|
| 53 | /// <summary>
|
---|
| 54 | /// Initializes a new instance of <see cref="NPointCrossover"/>
|
---|
| 55 | /// </summary>
|
---|
| 56 | public NPointCrossover()
|
---|
| 57 | : base() {
|
---|
| 58 | Parameters.Add(new ValueLookupParameter<IntValue>("N", "Number of crossover points", new IntValue(2)));
|
---|
| 59 | }
|
---|
| 60 |
|
---|
| 61 | public override IDeepCloneable Clone(Cloner cloner) {
|
---|
| 62 | return new NPointCrossover(this, cloner);
|
---|
| 63 | }
|
---|
| 64 |
|
---|
| 65 | public static MoveVector Apply(IRandom random, MoveVector parent1, MoveVector parent2, IntValue n) {
|
---|
| 66 | if (parent1.Length != parent2.Length)
|
---|
| 67 | throw new ArgumentException("NPointCrossover: The parents are of different length.");
|
---|
| 68 |
|
---|
| 69 | if (n.Value > parent1.Length)
|
---|
| 70 | throw new ArgumentException("NPointCrossover: There cannot be more breakpoints than the size of the parents.");
|
---|
| 71 |
|
---|
| 72 | if (n.Value < 1)
|
---|
| 73 | throw new ArgumentException("NPointCrossover: N cannot be < 1.");
|
---|
| 74 |
|
---|
| 75 | int length = parent1.Length;
|
---|
| 76 | MoveVector result = new MoveVector(length, parent1.MoveTypes);
|
---|
| 77 | int[] breakpoints = new int[n.Value];
|
---|
| 78 |
|
---|
| 79 | //choose break points
|
---|
| 80 | List<int> breakpointPool = new List<int>();
|
---|
| 81 |
|
---|
| 82 | for (int i = 0; i < length; i++)
|
---|
| 83 | breakpointPool.Add(i);
|
---|
| 84 |
|
---|
| 85 | for (int i = 0; i < n.Value; i++) {
|
---|
| 86 | int index = random.Next(breakpointPool.Count);
|
---|
| 87 | breakpoints[i] = breakpointPool[index];
|
---|
| 88 | breakpointPool.RemoveAt(index);
|
---|
| 89 | }
|
---|
| 90 |
|
---|
| 91 | Array.Sort(breakpoints);
|
---|
| 92 |
|
---|
| 93 | //perform crossover
|
---|
| 94 | int arrayIndex = 0;
|
---|
| 95 | int breakPointIndex = 0;
|
---|
| 96 | bool firstParent = true;
|
---|
| 97 |
|
---|
| 98 | while (arrayIndex < length) {
|
---|
| 99 | if (breakPointIndex < breakpoints.Length &&
|
---|
| 100 | arrayIndex == breakpoints[breakPointIndex]) {
|
---|
| 101 | breakPointIndex++;
|
---|
| 102 | firstParent = !firstParent;
|
---|
| 103 | }
|
---|
| 104 |
|
---|
| 105 | if (firstParent)
|
---|
| 106 | result[arrayIndex] = parent1[arrayIndex];
|
---|
| 107 | else
|
---|
| 108 | result[arrayIndex] = parent2[arrayIndex];
|
---|
| 109 |
|
---|
| 110 | arrayIndex++;
|
---|
| 111 | }
|
---|
| 112 |
|
---|
| 113 | return result;
|
---|
| 114 | }
|
---|
| 115 |
|
---|
| 116 | protected override MoveVector Cross(IRandom random, ItemArray<MoveVector> parents) {
|
---|
| 117 | if (parents.Length != 2) throw new ArgumentException("ERROR in NPointCrossover: The number of parents is not equal to 2");
|
---|
| 118 |
|
---|
| 119 | if (NParameter.ActualValue == null) throw new InvalidOperationException("NPointCrossover: Parameter " + NParameter.ActualName + " could not be found.");
|
---|
| 120 |
|
---|
| 121 | return Apply(random, parents[0], parents[1], NParameter.ActualValue);
|
---|
| 122 | }
|
---|
| 123 | }
|
---|
| 124 | }
|
---|