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source: branches/HeuristicLab.Problems.Orienteering/HeuristicLab.Encodings.RealVectorEncoding/3.3/Crossovers/BlendAlphaBetaCrossover.cs @ 11185

Last change on this file since 11185 was 11185, checked in by pfleck, 10 years ago

#2208 merged trunk and updated version info

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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2014 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
22using System;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Parameters;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28
29namespace HeuristicLab.Encodings.RealVectorEncoding {
30  /// <summary>
31  /// Blend alpha-beta crossover for real vectors (BLX-a-b). Creates a new offspring by selecting a
32  /// random value from the interval between the two alleles of the parent solutions.
33  /// The interval is increased in both directions as follows: Into the direction of the 'better'
34  /// solution by the factor alpha, into the direction of the 'worse' solution by the factor beta.
35  /// </summary>
36  /// <remarks>
37  /// It is implemented as described in Takahashi, M. and Kita, H. 2001. A crossover operator using independent component analysis for real-coded genetic algorithms Proceedings of the 2001 Congress on Evolutionary Computation, pp. 643-649.<br/>
38  /// The default value for alpha is 0.75, the default value for beta is 0.25.
39  /// </remarks>
40  [Item("BlendAlphaBetaCrossover", "The blend alpha beta crossover (BLX-a-b) for real vectors is similar to the blend alpha crossover (BLX-a), but distinguishes between the better and worse of the parents. The interval from which to choose the new offspring can be extended beyond the better parent by specifying a higher alpha value, and beyond the worse parent by specifying a higher beta value. The new offspring is sampled uniformly in the extended range. It is implemented as described in Takahashi, M. and Kita, H. 2001. A crossover operator using independent component analysis for real-coded genetic algorithms Proceedings of the 2001 Congress on Evolutionary Computation, pp. 643-649.")]
41  [StorableClass]
42  public class BlendAlphaBetaCrossover : RealVectorCrossover {
43    /// <summary>
44    /// Whether the problem is a maximization or minimization problem.
45    /// </summary>
46    public ValueLookupParameter<BoolValue> MaximizationParameter {
47      get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
48    }
49    /// <summary>
50    /// The quality of the parents.
51    /// </summary>
52    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
53      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
54    }
55    /// <summary>
56    /// The Alpha parameter controls the extension of the range beyond the better parent. The value must be >= 0 and does not depend on Beta.
57    /// </summary>
58    public ValueLookupParameter<DoubleValue> AlphaParameter {
59      get { return (ValueLookupParameter<DoubleValue>)Parameters["Alpha"]; }
60    }
61    /// <summary>
62    /// The Beta parameter controls the extension of the range beyond the worse parent. The value must be >= 0 and does not depend on Alpha.
63    /// </summary>
64    public ValueLookupParameter<DoubleValue> BetaParameter {
65      get { return (ValueLookupParameter<DoubleValue>)Parameters["Beta"]; }
66    }
67
68    [StorableConstructor]
69    protected BlendAlphaBetaCrossover(bool deserializing) : base(deserializing) { }
70    protected BlendAlphaBetaCrossover(BlendAlphaBetaCrossover original, Cloner cloner) : base(original, cloner) { }
71    /// <summary>
72    /// Initializes a new instance of <see cref="BlendAlphaBetaCrossover"/> with four additional parameters
73    /// (<c>Maximization</c>, <c>Quality</c>, <c>Alpha</c> and <c>Beta</c>).
74    /// </summary>
75    public BlendAlphaBetaCrossover()
76      : base() {
77      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "Whether the problem is a maximization problem or not."));
78      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The quality values of the parents."));
79      Parameters.Add(new ValueLookupParameter<DoubleValue>("Alpha", "The Alpha parameter controls the extension of the range beyond the better parent. The value must be >= 0 and does not depend on Beta.", new DoubleValue(0.75)));
80      Parameters.Add(new ValueLookupParameter<DoubleValue>("Beta", "The Beta parameter controls the extension of the range beyond the worse parent. The value must be >= 0 and does not depend on Alpha.", new DoubleValue(0.25)));
81    }
82
83    public override IDeepCloneable Clone(Cloner cloner) {
84      return new BlendAlphaBetaCrossover(this, cloner);
85    }
86
87    /// <summary>
88    /// Performs the blend alpha beta crossover (BLX-a-b) on two parent vectors.
89    /// </summary>
90    /// <exception cref="ArgumentException">
91    /// Thrown when either:<br/>
92    /// <list type="bullet">
93    /// <item><description>The length of <paramref name="betterParent"/> and <paramref name="worseParent"/> is not equal.</description></item>
94    /// <item><description>The parameter <paramref name="alpha"/> is smaller than 0.</description></item>
95    /// <item><description>The parameter <paramref name="beta"/> is smaller than 0.</description></item>
96    /// </list>
97    /// </exception>
98    /// <param name="random">The random number generator to use.</param>
99    /// <param name="betterParent">The better of the two parents with regard to their fitness.</param>
100    /// <param name="worseParent">The worse of the two parents with regard to their fitness.</param>
101    /// <param name="alpha">The parameter alpha.</param>
102    /// <param name="beta">The parameter beta.</param>
103    /// <returns>The real vector that results from the crossover.</returns>
104    public static RealVector Apply(IRandom random, RealVector betterParent, RealVector worseParent, DoubleValue alpha, DoubleValue beta) {
105      if (betterParent.Length != worseParent.Length) throw new ArgumentException("BlendAlphaBetaCrossover: The parents' vectors are of different length.", "betterParent");
106      if (alpha.Value < 0) throw new ArgumentException("BlendAlphaBetaCrossover: Parameter alpha must be greater or equal to 0.", "alpha");
107      if (beta.Value < 0) throw new ArgumentException("BlendAlphaBetaCrossover: Parameter beta must be greater or equal to 0.", "beta");
108      int length = betterParent.Length;
109      double min, max, d;
110      RealVector result = new RealVector(length);
111
112      for (int i = 0; i < length; i++) {
113        d = Math.Abs(betterParent[i] - worseParent[i]);
114        if (betterParent[i] <= worseParent[i]) {
115          min = betterParent[i] - d * alpha.Value;
116          max = worseParent[i] + d * beta.Value;
117        } else {
118          min = worseParent[i] - d * beta.Value;
119          max = betterParent[i] + d * alpha.Value;
120        }
121        result[i] = min + random.NextDouble() * (max - min);
122      }
123      return result;
124    }
125
126    /// <summary>
127    /// Checks if the number of parents is equal to 2, if all parameters are available and forwards the call to <see cref="Apply(IRandom, RealVector, RealVector, DoubleValue, DoubleValue)"/>.
128    /// </summary>
129    /// <exception cref="ArgumentException">Thrown when the number of parents is not equal to 2.</exception>
130    /// <exception cref="InvalidOperationException">
131    /// Thrown when either:<br/>
132    /// <list type="bullet">
133    /// <item><description>Maximization parameter could not be found.</description></item>
134    /// <item><description>Quality parameter could not be found or the number of quality values is not equal to the number of parents.</description></item>
135    /// <item><description>Alpha parameter could not be found.</description></item>
136    /// <item><description>Beta parameter could not be found.</description></item>
137    /// </list>
138    /// </exception>
139    /// <param name="random">The random number generator to use.</param>
140    /// <param name="parents">The collection of parents (must be of size 2).</param>
141    /// <returns>The real vector that results from the crossover.</returns>
142    protected override RealVector Cross(IRandom random, ItemArray<RealVector> parents) {
143      if (parents.Length != 2) throw new ArgumentException("BlendAlphaBetaCrossover: Number of parents is not equal to 2.", "parents");
144      if (MaximizationParameter.ActualValue == null) throw new InvalidOperationException("BlendAlphaBetaCrossover: Parameter " + MaximizationParameter.ActualName + " could not be found.");
145      if (QualityParameter.ActualValue == null || QualityParameter.ActualValue.Length != parents.Length) throw new InvalidOperationException("BlendAlphaBetaCrossover: Parameter " + QualityParameter.ActualName + " could not be found, or not in the same quantity as there are parents.");
146      if (AlphaParameter.ActualValue == null || BetaParameter.ActualValue == null) throw new InvalidOperationException("BlendAlphaBetaCrossover: Parameter " + AlphaParameter.ActualName + " or paramter " + BetaParameter.ActualName + " could not be found.");
147
148      ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;
149      bool maximization = MaximizationParameter.ActualValue.Value;
150      if (maximization && qualities[0].Value >= qualities[1].Value || !maximization && qualities[0].Value <= qualities[1].Value)
151        return Apply(random, parents[0], parents[1], AlphaParameter.ActualValue, BetaParameter.ActualValue);
152      else {
153        return Apply(random, parents[1], parents[0], AlphaParameter.ActualValue, BetaParameter.ActualValue);
154      }
155    }
156  }
157}
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