[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 homologous one point crossover operator as described in:
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| 36 | /// W. B. Langdon and R. Poli. Foundations of Genetic Programming. Springer-Verlag, 2002.
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| 37 | /// </summary>
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[1197] | 38 | public class OnePointCrossOver : SizeConstrictedGPCrossoverBase {
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[815] | 39 | // internal data structure to represent crossover points
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| 40 | private class CrossoverPoint {
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| 41 | public IFunctionTree parent0;
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| 42 | public IFunctionTree parent1;
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| 43 | public int childIndex;
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| 44 | }
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[645] | 45 | public override string Description {
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| 46 | get {
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[1197] | 47 | return @"One point crossover for trees as described in W. B. Langdon and R. Poli. Foundations of Genetic Programming. Springer-Verlag, 2002.";
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[645] | 48 | }
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| 49 | }
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| 50 |
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[1286] | 51 | internal override IFunctionTree Cross(TreeGardener gardener, IRandom random, IFunctionTree tree0, IFunctionTree tree1, int maxTreeSize, int maxTreeHeight) {
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[815] | 52 | List<CrossoverPoint> allowedCrossOverPoints = new List<CrossoverPoint>();
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[1197] | 53 | GetCrossOverPoints(gardener, tree0, tree1, maxTreeSize - tree0.Size, allowedCrossOverPoints);
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[809] | 54 | if (allowedCrossOverPoints.Count > 0) {
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| 55 | CrossoverPoint crossOverPoint = allowedCrossOverPoints[random.Next(allowedCrossOverPoints.Count)];
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| 56 | IFunctionTree parent0 = crossOverPoint.parent0;
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| 57 | IFunctionTree branch1 = crossOverPoint.parent1.SubTrees[crossOverPoint.childIndex];
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| 58 | parent0.RemoveSubTree(crossOverPoint.childIndex);
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| 59 | parent0.InsertSubTree(crossOverPoint.childIndex, branch1);
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[645] | 60 | }
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[815] | 61 | return tree0;
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[645] | 62 | }
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| 63 |
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[1197] | 64 | private void GetCrossOverPoints(TreeGardener gardener, IFunctionTree branch0, IFunctionTree branch1, int maxNewNodes, List<CrossoverPoint> crossoverPoints) {
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[815] | 65 | if (branch0.SubTrees.Count != branch1.SubTrees.Count) return;
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[809] | 66 |
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| 67 | for (int i = 0; i < branch0.SubTrees.Count; i++) {
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[815] | 68 | // if the current branch can be attached as a sub-tree to branch0
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[1197] | 69 | if (gardener.GetAllowedSubFunctions(branch0.Function, i).Contains(branch1.SubTrees[i].Function) &&
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| 70 | branch1.SubTrees[i].Size - branch0.SubTrees[i].Size <= maxNewNodes) {
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[809] | 71 | CrossoverPoint p = new CrossoverPoint();
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| 72 | p.childIndex = i;
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| 73 | p.parent0 = branch0;
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| 74 | p.parent1 = branch1;
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[815] | 75 | crossoverPoints.Add(p);
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[707] | 76 | }
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[1197] | 77 | GetCrossOverPoints(gardener, branch0.SubTrees[i], branch1.SubTrees[i], maxNewNodes, crossoverPoints);
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[645] | 78 | }
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| 79 | }
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| 80 | }
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| 81 | }
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