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source: branches/2520_PersistenceReintegration/HeuristicLab.Encodings.IntegerVectorEncoding/3.3/Crossovers/RoundedHeuristicCrossover.cs @ 16462

Last change on this file since 16462 was 16462, checked in by jkarder, 5 years ago

#2520: worked on reintegration of new persistence

  • added nuget references to HEAL.Fossil
  • added StorableType attributes to many classes
  • changed signature of StorableConstructors
  • removed some classes in old persistence
  • removed some unnecessary usings
File size: 6.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2019 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.Optimization;
27using HeuristicLab.Parameters;
28using HEAL.Fossil;
29
30namespace HeuristicLab.Encodings.IntegerVectorEncoding {
31  /// <summary>
32  /// Heuristic crossover for integer vectors: Calculates the vector from the worse to the better parent and adds that to the better parent weighted with a factor in the interval [0;1).
33  /// The result is then rounded to the next feasible integer.
34  /// The idea is that going further in direction from the worse to the better leads to even better solutions (naturally this depends on the fitness landscape).
35  /// </summary>
36  [Item("RoundedHeuristicCrossover", "The heuristic crossover produces offspring that extend the better parent in direction from the worse to the better parent.")]
37  [StorableType("94963FD3-4092-4B76-88E0-5FE5AC2DA9E2")]
38  public class RoundedHeuristicCrossover : BoundedIntegerVectorCrossover, ISingleObjectiveOperator {
39    /// <summary>
40    /// Whether the problem is a maximization or minimization problem.
41    /// </summary>
42    public ValueLookupParameter<BoolValue> MaximizationParameter {
43      get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
44    }
45    /// <summary>
46    /// The quality of the parents.
47    /// </summary>
48    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
49      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
50    }
51
52    [StorableConstructor]
53    protected RoundedHeuristicCrossover(StorableConstructorFlag _) : base(_) { }
54    protected RoundedHeuristicCrossover(RoundedHeuristicCrossover original, Cloner cloner) : base(original, cloner) { }
55    /// <summary>
56    /// Initializes a new instance of <see cref="RoundedHeuristicCrossover"/> with two variable infos
57    /// (<c>Maximization</c> and <c>Quality</c>).
58    /// </summary>
59    public RoundedHeuristicCrossover()
60      : base() {
61      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "Whether the problem is a maximization problem or not."));
62      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The quality values of the parents."));
63    }
64
65    public override IDeepCloneable Clone(Cloner cloner) {
66      return new RoundedHeuristicCrossover(this, cloner);
67    }
68
69    /// <summary>
70    /// Perfomrs a heuristic crossover on the two given parents.
71    /// </summary>
72    /// <exception cref="ArgumentException">Thrown when two parents are not of the same length.</exception>
73    /// <param name="random">The random number generator.</param>
74    /// <param name="betterParent">The first parent for the crossover operation.</param>
75    /// <param name="worseParent">The second parent for the crossover operation.</param>
76    /// <param name="bounds">The bounds and step size for each dimension (will be cycled in case there are less rows than elements in the parent vectors).</param>
77    /// <returns>The newly created integer vector, resulting from the heuristic crossover.</returns>
78    public static IntegerVector Apply(IRandom random, IntegerVector betterParent, IntegerVector worseParent, IntMatrix bounds) {
79      if (betterParent.Length != worseParent.Length)
80        throw new ArgumentException("HeuristicCrossover: the two parents are not of the same length");
81
82      int length = betterParent.Length;
83      var result = new IntegerVector(length);
84      double factor = random.NextDouble();
85
86      int min, max, step = 1;
87      for (int i = 0; i < length; i++) {
88        min = bounds[i % bounds.Rows, 0];
89        max = bounds[i % bounds.Rows, 1];
90        if (bounds.Columns > 2) step = bounds[i % bounds.Rows, 2];
91        max = FloorFeasible(min, max, step, max - 1);
92        result[i] = RoundFeasible(min, max, step, betterParent[i] + factor * (betterParent[i] - worseParent[i]));
93      }
94      return result;
95    }
96
97    /// <summary>
98    /// Performs a heuristic crossover operation for two given parent integer vectors.
99    /// </summary>
100    /// <exception cref="ArgumentException">Thrown when the number of parents is not equal to 2.</exception>
101    /// <exception cref="InvalidOperationException">
102    /// Thrown when either:<br/>
103    /// <list type="bullet">
104    /// <item><description>Maximization parameter could not be found.</description></item>
105    /// <item><description>Quality parameter could not be found or the number of quality values is not equal to the number of parents.</description></item>
106    /// </list>
107    /// </exception>
108    /// <param name="random">A random number generator.</param>
109    /// <param name="parents">An array containing the two real vectors that should be crossed.</param>
110    /// /// <param name="bounds">The bounds and step size for each dimension (will be cycled in case there are less rows than elements in the parent vectors).</param>
111    /// <returns>The newly created integer vector, resulting from the crossover operation.</returns>
112    protected override IntegerVector CrossBounded(IRandom random, ItemArray<IntegerVector> parents, IntMatrix bounds) {
113      if (parents.Length != 2) throw new ArgumentException("RoundedHeuristicCrossover: The number of parents is not equal to 2");
114
115      if (MaximizationParameter.ActualValue == null) throw new InvalidOperationException("RoundedHeuristicCrossover: Parameter " + MaximizationParameter.ActualName + " could not be found.");
116      if (QualityParameter.ActualValue == null || QualityParameter.ActualValue.Length != parents.Length) throw new InvalidOperationException("RoundedHeuristicCrossover: Parameter " + QualityParameter.ActualName + " could not be found, or not in the same quantity as there are parents.");
117
118      ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;
119      bool maximization = MaximizationParameter.ActualValue.Value;
120
121      if (maximization && qualities[0].Value >= qualities[1].Value || !maximization && qualities[0].Value <= qualities[1].Value)
122        return Apply(random, parents[0], parents[1], bounds);
123      else
124        return Apply(random, parents[1], parents[0], bounds);
125    }
126  }
127}
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