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source: trunk/sources/HeuristicLab.GP/Recombination/SizeConstrictedGPCrossoverBase.cs @ 835

Last change on this file since 835 was 835, checked in by gkronber, 16 years ago
  • added another abstract base class for GP crossover operators with maxsize and maxheight constraints
  • changed StandardCrossOver to inherit from SizeConstrictedGPCrossoverBase
  • changed SizeFairCrossOver to inherit from SizeConstrictedGPCrossoverBase
  • generally improved code of SizeFairCrossOver
  • changed LangdonHomologousCrossOver to inherit from SizeFairCrossOver and implemented only the method to finally select branches.

#393 (Refactor GP crossover operators to extract common code into the abstract base class GPCrossoverBase)

File size: 2.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2008 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 System.Collections.Generic;
24using System.Linq;
25using System.Text;
26using HeuristicLab.Core;
27using HeuristicLab.Operators;
28using HeuristicLab.Random;
29using HeuristicLab.Data;
30using HeuristicLab.Constraints;
31using System.Diagnostics;
32
33namespace HeuristicLab.GP {
34  public abstract class SizeConstrictedGPCrossoverBase : GPCrossoverBase{
35    public SizeConstrictedGPCrossoverBase()
36      : base() {
37      AddVariableInfo(new VariableInfo("MaxTreeHeight", "The maximal allowed height of the tree", typeof(IntData), VariableKind.In));
38      AddVariableInfo(new VariableInfo("MaxTreeSize", "The maximal allowed size (number of nodes) of the tree", typeof(IntData), VariableKind.In));
39    }
40
41    internal override IFunctionTree Cross(IScope scope, TreeGardener gardener, MersenneTwister random, IFunctionTree tree0, IFunctionTree tree1) {
42      int maxTreeHeight = GetVariableValue<IntData>("MaxTreeHeight", scope, true).Data;
43      int maxTreeSize = GetVariableValue<IntData>("MaxTreeSize", scope, true).Data;
44
45      // when tree0 is terminal then try to cross into tree1, when tree1 is also terminal just return tree0 unchanged.
46      IFunctionTree newTree;
47      if (tree0.SubTrees.Count > 0) {
48        newTree = Cross(gardener, random, tree0, tree1, maxTreeSize, maxTreeHeight);
49      } else if (tree1.SubTrees.Count > 0) {
50        newTree = Cross(gardener, random, tree1, tree0, maxTreeSize, maxTreeHeight);
51      } else newTree = tree0;
52
53      // check if the size and height of the new tree are still within the allowed bounds
54      Debug.Assert(newTree.Height <= maxTreeHeight);
55      Debug.Assert(newTree.Size <= maxTreeSize);
56      return newTree;
57    }
58
59    internal abstract IFunctionTree Cross(TreeGardener gardener, MersenneTwister random, IFunctionTree tree0, IFunctionTree tree1, int maxTreeSize, int maxTreeHeight);
60
61    private IFunctionTree TakeNextParent(IScope scope) {
62      IFunctionTree parent = GetVariableValue<IFunctionTree>("FunctionTree", scope.SubScopes[0], false);
63      scope.RemoveSubScope(scope.SubScopes[0]);
64      return parent;
65    }
66  }
67}
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