[2] | 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.Text;
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| 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Data;
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| 27 |
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| 28 | namespace HeuristicLab.Selection.OffspringSelection {
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[1153] | 29 | /// <summary>
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| 30 | /// Analyzes the offspring in a given scope whether it is successful or not.
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| 31 | /// </summary>
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[2] | 32 | public class OffspringAnalyzer : OperatorBase {
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[1153] | 33 | /// <inheritdoc select="summary"/>
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[2] | 34 | public override string Description {
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| 35 | get { return @"TODO\r\nOperator description still missing ..."; }
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| 36 | }
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| 37 |
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[1153] | 38 | /// <summary>
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| 39 | /// Initializes a new instance of <see cref="OffspringAnalyzer"/> with six variable infos
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| 40 | /// (<c>Maximization</c>, <c>Quality</c>, <c>ParentQualities</c>, <c>SuccessfulChild</c>,
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| 41 | /// <c>ComparisonFactor</c> and <c>ParentsCount</c>).
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| 42 | /// </summary>
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[2] | 43 | public OffspringAnalyzer() {
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| 44 | AddVariableInfo(new VariableInfo("Maximization", "Problem is a maximization problem", typeof(BoolData), VariableKind.In));
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| 45 | AddVariableInfo(new VariableInfo("Quality", "Quality value", typeof(DoubleData), VariableKind.In));
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| 46 | AddVariableInfo(new VariableInfo("ParentQualities", "Temporarily store parent qualities", typeof(DoubleArrayData), VariableKind.New | VariableKind.Out | VariableKind.In | VariableKind.Deleted));
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| 47 | AddVariableInfo(new VariableInfo("SuccessfulChild", "True if the child was successful", typeof(BoolData), VariableKind.New));
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| 48 |
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| 49 | VariableInfo compFactorInfo = new VariableInfo("ComparisonFactor", "Factor for comparing the quality of a child with the qualities of its parents (0 = better than worst parent, 1 = better than best parent)", typeof(DoubleData), VariableKind.In);
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| 50 | compFactorInfo.Local = true;
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| 51 | AddVariableInfo(compFactorInfo);
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| 52 | AddVariable(new Variable("ComparisonFactor", new DoubleData(0.5)));
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| 53 | VariableInfo parentCount = new VariableInfo("ParentsCount", "How many parents created the offspring", typeof(IntData), VariableKind.In);
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| 54 | parentCount.Local = true;
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| 55 | AddVariableInfo(parentCount);
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| 56 | AddVariable(new Variable("ParentsCount", new IntData(2)));
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| 57 | }
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| 58 |
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[1153] | 59 | /// <summary>
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| 60 | /// Analyzes the offspring in the given scope whether the children are successful or not.
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| 61 | /// </summary>
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| 62 | /// <exception cref="InvalidOperationException">Thrown when <c>ParentsCount</c> smaller than 1.</exception>
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| 63 | /// <exception cref="InvalidOperationException">Thrown when the number of children is not constant or
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| 64 | /// smaller than 1.</exception>
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| 65 | /// <param name="scope">The scope whose offspring should be analyzed.</param>
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[1157] | 66 | /// <returns>The next operation or <c>null</c>.</returns>
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[2] | 67 | public override IOperation Apply(IScope scope) {
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| 68 | bool maximize = GetVariableValue<BoolData>("Maximization", scope, true).Data;
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| 69 | double compFact = GetVariableValue<DoubleData>("ComparisonFactor", scope, true).Data;
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| 70 | int parentsCount = GetVariableValue<IntData>("ParentsCount", scope, true).Data;
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| 71 | if (parentsCount < 1) throw new InvalidOperationException("OffspringAnalyzer: ParentsCount must be >= 1");
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| 72 |
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| 73 | DoubleArrayData qualities = GetVariableValue<DoubleArrayData>("ParentQualities", scope, false, false);
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| 74 | if (qualities == null) {
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| 75 | // fetch and store parent qualities
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| 76 | IVariableInfo qualityInfo = GetVariableInfo("Quality");
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| 77 | double[] qualitiesArray = new double[scope.SubScopes.Count];
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| 78 | for (int i = 0; i < qualitiesArray.Length; i++)
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[77] | 79 | qualitiesArray[i] = scope.SubScopes[i].GetVariableValue<DoubleData>(qualityInfo.FormalName, false).Data;
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[2] | 80 | qualities = new DoubleArrayData(qualitiesArray);
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| 81 | IVariableInfo parentQualitiesInfo = GetVariableInfo("ParentQualities");
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| 82 | if (parentQualitiesInfo.Local)
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| 83 | AddVariable(new Variable(parentQualitiesInfo.ActualName, qualities));
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| 84 | else
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[77] | 85 | scope.AddVariable(new Variable(scope.TranslateName(parentQualitiesInfo.FormalName), qualities));
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[2] | 86 |
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| 87 | CompositeOperation next = new CompositeOperation();
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| 88 | next.AddOperation(new AtomicOperation(SubOperators[0], scope));
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| 89 | next.AddOperation(new AtomicOperation(this, scope));
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| 90 | return next;
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| 91 | } else {
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[806] | 92 | int crossoverEvents = qualities.Data.Length / parentsCount;
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| 93 | int childrenPerCrossoverEvent = scope.SubScopes.Count / crossoverEvents;
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| 94 | if (scope.SubScopes.Count % crossoverEvents != 0 ||
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| 95 | childrenPerCrossoverEvent < 1) throw new InvalidOperationException("OffspringAnalyzer: The number of children per crossover event has to be constant and >= 1");
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| 96 | // analyze offspring of all crossoverEvents
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| 97 | for (int i = 0; i < crossoverEvents; i++) {
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| 98 | double worstParent = double.MaxValue; // lowest quality parent
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| 99 | double bestParent = double.MinValue; // highest quality parent
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| 100 | for (int y = 0; y < parentsCount; y++) {
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| 101 | if (qualities.Data[i * parentsCount + y] < worstParent) worstParent = qualities.Data[i * parentsCount + y];
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| 102 | if (qualities.Data[i * parentsCount + y] > bestParent) bestParent = qualities.Data[i * parentsCount + y];
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[2] | 103 | }
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[806] | 104 | for (int j = 0; j < childrenPerCrossoverEvent; j++) {
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| 105 | IVariableInfo qualityInfo = GetVariableInfo("Quality");
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| 106 | double child = scope.SubScopes[i * childrenPerCrossoverEvent + j].GetVariableValue<DoubleData>(qualityInfo.FormalName, false).Data;
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| 107 | double threshold;
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[2] | 108 |
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[806] | 109 | if (!maximize)
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| 110 | threshold = bestParent + (worstParent - bestParent) * compFact;
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| 111 | else
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| 112 | threshold = worstParent + (bestParent - worstParent) * compFact;
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[2] | 113 |
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[806] | 114 | IVariableInfo successfulInfo = GetVariableInfo("SuccessfulChild");
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| 115 | BoolData successful;
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| 116 | if (((!maximize) && (child < threshold)) ||
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| 117 | ((maximize) && (child > threshold)))
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| 118 | successful = new BoolData(true);
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| 119 | else
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| 120 | successful = new BoolData(false);
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| 121 | scope.SubScopes[i * childrenPerCrossoverEvent + j].AddVariable(new Variable(scope.TranslateName(successfulInfo.FormalName), successful));
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| 122 | }
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[2] | 123 | }
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| 124 |
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| 125 | // remove parent qualities again
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| 126 | IVariableInfo parentQualitiesInfo = GetVariableInfo("ParentQualities");
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| 127 | if (parentQualitiesInfo.Local)
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| 128 | RemoveVariable(parentQualitiesInfo.ActualName);
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| 129 | else
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[77] | 130 | scope.RemoveVariable(scope.TranslateName(parentQualitiesInfo.FormalName));
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[2] | 131 |
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| 132 | return null;
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| 133 | }
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| 134 | }
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| 135 | }
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| 136 | }
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