[645] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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| 23 | using System.Collections.Generic;
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| 24 | using System.Linq;
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| 25 | using System.Text;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Operators;
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| 28 | using HeuristicLab.Random;
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| 29 | using HeuristicLab.Data;
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| 30 | using HeuristicLab.Constraints;
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| 31 | using System.Diagnostics;
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| 32 |
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| 33 | namespace HeuristicLab.GP {
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| 34 | /// <summary>
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| 35 | /// Implementation of a size fair crossover operator as described in:
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| 36 | /// William B. Langdon
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| 37 | /// Size Fair and Homologous Tree Genetic Programming Crossovers,
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| 38 | /// Genetic Programming and Evolvable Machines, Vol. 1, Number 1/2, pp. 95-119, April 2000
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| 39 | /// </summary>
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[833] | 40 | public class SizeFairCrossOver : GPCrossoverBase {
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[645] | 41 | private const int MAX_RECOMBINATION_TRIES = 20;
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| 42 | public override string Description {
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| 43 | get {
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| 44 | return @"";
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| 45 | }
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| 46 | }
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| 47 | public SizeFairCrossOver()
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| 48 | : base() {
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| 49 | AddVariableInfo(new VariableInfo("MaxTreeHeight", "The maximal allowed height of the tree", typeof(IntData), VariableKind.In));
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| 50 | AddVariableInfo(new VariableInfo("MaxTreeSize", "The maximal allowed size (number of nodes) of the tree", typeof(IntData), VariableKind.In));
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| 51 | }
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| 52 |
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[833] | 53 | internal override IFunctionTree Cross(IScope scope, TreeGardener gardener, MersenneTwister random, IFunctionTree tree0, IFunctionTree tree1) {
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[645] | 54 | int maxTreeHeight = GetVariableValue<IntData>("MaxTreeHeight", scope, true).Data;
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| 55 | int maxTreeSize = GetVariableValue<IntData>("MaxTreeSize", scope, true).Data;
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| 56 |
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[833] | 57 | // when tree0 is terminal then try to cross into tree1, when tree1 is also terminal just return tree0 unchanged.
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| 58 | IFunctionTree newTree;
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| 59 | if(tree0.SubTrees.Count > 0) {
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| 60 | newTree = Cross(gardener, tree0, tree1, random, maxTreeSize, maxTreeHeight);
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| 61 | } else if(tree1.SubTrees.Count > 0) {
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| 62 | newTree = Cross(gardener, tree1, tree0, random, maxTreeSize, maxTreeHeight);
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| 63 | } else newTree = tree0;
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[645] | 64 |
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[833] | 65 | // check if the height and size of the new tree are still in the allowed bounds
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| 66 | Debug.Assert(newTree.Height <= maxTreeHeight);
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| 67 | Debug.Assert(newTree.Size <= maxTreeSize);
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| 68 | return newTree;
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[645] | 69 | }
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| 70 |
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[833] | 71 | private IFunctionTree Cross(TreeGardener gardener, IFunctionTree tree0, IFunctionTree tree1, MersenneTwister random, int maxTreeSize, int maxTreeHeight) {
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| 72 | int tries = 0;
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| 73 | IFunctionTree insertedBranch = null;
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| 74 | IFunctionTree crossoverPoint = null;
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| 75 | int removedBranchIndex = 0;
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| 76 | do {
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| 77 | // select a random suboperator of the 'receiving' tree
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| 78 | while(crossoverPoint == null) crossoverPoint = gardener.GetRandomParentNode(tree0);
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[814] | 79 | removedBranchIndex = random.Next(crossoverPoint.SubTrees.Count);
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[833] | 80 | IFunctionTree removedBranch = crossoverPoint.SubTrees[removedBranchIndex];
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| 81 | IList<IFunction> allowedFunctions = gardener.GetAllowedSubFunctions(crossoverPoint.Function, removedBranchIndex);
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| 82 | int removedBranchSize = removedBranch.Size;
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| 83 | int maxBranchSize = maxTreeSize - (tree0.Size - removedBranchSize);
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| 84 | int maxBranchHeight = maxTreeHeight - gardener.GetBranchLevel(tree0, crossoverPoint);
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| 85 | insertedBranch = GetReplacementBranch(random, gardener, allowedFunctions, tree1, removedBranchSize, maxBranchSize, maxBranchHeight);
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| 86 | } while(insertedBranch == null && tries++ < MAX_RECOMBINATION_TRIES);
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[645] | 87 |
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[833] | 88 | if(insertedBranch != null) {
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[814] | 89 | // replace the branch below the crossoverpoint with the selected branch from root1
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| 90 | crossoverPoint.RemoveSubTree(removedBranchIndex);
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| 91 | crossoverPoint.InsertSubTree(removedBranchIndex, insertedBranch);
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| 92 | }
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[833] | 93 | return tree0;
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[645] | 94 | }
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| 95 |
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| 96 | private IFunctionTree GetReplacementBranch(IRandom random, TreeGardener gardener, IList<IFunction> allowedFunctions, IFunctionTree tree, int removedBranchSize, int maxBranchSize, int maxBranchHeight) {
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[833] | 97 | var branches = gardener.GetAllSubTrees(tree).Where(t => allowedFunctions.Contains(t.Function) && t.Size <= maxBranchSize && t.Height <= maxBranchHeight)
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[645] | 98 | .Select(t => new { Tree = t, Size = t.Size }).Where(s => s.Size < 2 * removedBranchSize + 1);
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| 99 |
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| 100 | var shorterBranches = branches.Where(t => t.Size < removedBranchSize);
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| 101 | var longerBranches = branches.Where(t => t.Size > removedBranchSize);
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| 102 | var equalLengthBranches = branches.Where(t => t.Size == removedBranchSize);
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| 103 |
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[833] | 104 | if(shorterBranches.Count() == 0 || longerBranches.Count() == 0) {
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| 105 | if(equalLengthBranches.Count() == 0) {
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[645] | 106 | return null;
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| 107 | } else {
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| 108 | return equalLengthBranches.ElementAt(random.Next(equalLengthBranches.Count())).Tree;
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| 109 | }
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| 110 | } else {
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| 111 | // invariant: |shorterBranches| > 0 and |longerBranches| > 0
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| 112 | double pEqualLength = equalLengthBranches.Count() > 0 ? 1.0 / removedBranchSize : 0.0;
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| 113 | double pLonger = (1.0 - pEqualLength) / (longerBranches.Count() * (1.0 + longerBranches.Average(t => t.Size) / shorterBranches.Average(t => t.Size)));
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| 114 | double pShorter = (1.0 - pEqualLength - pLonger);
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| 115 |
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| 116 | double r = random.NextDouble();
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[833] | 117 | if(r < pLonger) {
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[645] | 118 | return longerBranches.ElementAt(random.Next(longerBranches.Count())).Tree;
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[833] | 119 | } else if(r < pLonger + pShorter) {
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[645] | 120 | return shorterBranches.ElementAt(random.Next(shorterBranches.Count())).Tree;
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| 121 | } else {
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| 122 | return equalLengthBranches.ElementAt(random.Next(equalLengthBranches.Count())).Tree;
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| 123 | }
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| 124 | }
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| 125 | }
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| 126 | }
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| 127 | }
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