[11492] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2014 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 HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.Operators;
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| 29 | using HeuristicLab.Optimization;
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| 30 | using HeuristicLab.Parameters;
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| 31 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 32 |
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| 33 | namespace HeuristicLab.Algorithms.VOffspringSelectionGeneticAlgorithm {
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| 34 | [Item("ProbabilitiesGenerator", "An operator the generates the probability vector for Multi Crossovers/Mutators")]
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| 35 | [StorableClass]
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| 36 | public class ProbabilitiesGenerator : SingleSuccessorOperator {
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| 37 | public ValueParameter<StringValue> SuccessfulOffspringFlagParameter {
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| 38 | get { return (ValueParameter<StringValue>)Parameters["SuccessfulOffspringFlag"]; }
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| 39 | }
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| 40 |
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| 41 | public ValueParameter<StringValue> OperatorNameVariableParameter {
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| 42 | get { return (ValueParameter<StringValue>)Parameters["OperatorNameVariable"]; }
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| 43 | }
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| 44 | public LookupParameter<ResultCollection> SuccessfulOffspringAnalysisParameter {
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| 45 | get { return (LookupParameter<ResultCollection>)Parameters["SuccessfulOffspringAnalysis"]; }
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| 46 | }
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| 47 | public LookupParameter<IOperator> CrossoverParameter {
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| 48 | get { return (LookupParameter<IOperator>)Parameters["Crossover"]; }
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| 49 | }
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| 50 | public ILookupParameter<IntValue> GenerationsParameter {
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| 51 | get { return (LookupParameter<IntValue>)Parameters["Generations"]; }
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| 52 | }
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| 53 | public LookupParameter<DoubleArray> ProbablilitiesParameter {
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| 54 | get { return (LookupParameter<DoubleArray>)Parameters["Probabilities"]; }
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| 55 |
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| 56 | }
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| 57 | public ValueParameter<DoubleValue> MinimumOperatorUsageParameter {
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| 58 | get { return (ValueParameter<DoubleValue>)Parameters["MinimumOperatorUsage"]; }
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| 59 | }
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| 60 |
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| 61 | public override IDeepCloneable Clone(Cloner cloner) {
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| 62 | return new ProbabilitiesGenerator(this, cloner);
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| 63 | }
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| 64 | [StorableConstructor]
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| 65 | private ProbabilitiesGenerator(bool deserializing) : base(deserializing) { }
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| 66 | private ProbabilitiesGenerator(ProbabilitiesGenerator original, Cloner cloner) : base(original, cloner) { }
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| 67 | public ProbabilitiesGenerator()
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| 68 | : base() {
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| 69 | Parameters.Add(new ValueParameter<StringValue>("SuccessfulOffspringFlag", "The name of the flag which indicates if the individual was successful.", new StringValue("SuccessfulOffspring")));
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| 70 | Parameters.Add(new ValueParameter<StringValue>("OperatorNameVariable", "The properties of the successful offspring that should be collected.", new StringValue("SelectedCrossoverOperator")));
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| 71 | Parameters.Add(new LookupParameter<IntValue>("Generations", "The current number of generations."));
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| 72 | Parameters.Add(new LookupParameter<ResultCollection>("SuccessfulOffspringAnalysis", "The successful offspring analysis which is created."));
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| 73 | Parameters.Add(new LookupParameter<DoubleArray>("Probabilities"));
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| 74 | Parameters.Add(new LookupParameter<IOperator>("Crossover"));
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| 75 | Parameters.Add(new ValueParameter<DoubleValue>("MinimumOperatorUsage", "Minimum percentage of operator usage. ", new DoubleValue(0.05)));
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| 76 | }
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| 77 |
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| 78 | public override IOperation Apply() {
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| 79 | IScope scope = ExecutionContext.Scope;
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| 80 | IScope offspring = scope.SubScopes[1];
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| 81 | string operatorName = OperatorNameVariableParameter.Value.Value;
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| 82 | string succssFlag = SuccessfulOffspringFlagParameter.Value.Value;
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| 83 | Dictionary<string, int> operatorCount = new Dictionary<string, int>();
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| 84 | Dictionary<string, int> successfulOperatorCount = new Dictionary<string, int>();
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| 85 |
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| 86 | var crossover = CrossoverParameter.ActualValue;
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| 87 | if (crossover.GetType().GetInterfaces().Any(x => x.IsGenericType &&
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| 88 | x.GetGenericTypeDefinition() == typeof(ICheckedMultiOperator<>))) {
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| 89 |
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| 90 | for (int i = 0; i < offspring.SubScopes.Count; i++) {
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| 91 | // fetch values from scopes
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| 92 | IVariable tmpVar;
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| 93 | if (!offspring.SubScopes[i].Variables.TryGetValue(succssFlag, out tmpVar))
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| 94 | throw new InvalidOperationException(Name + ": Could not determine if an offspring was successful or not.");
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| 95 | BoolValue success = (tmpVar.Value as BoolValue);
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| 96 | if (success == null) throw new InvalidOperationException(Name + ": The variable that indicates whether an offspring is successful or not must contain a BoolValue.");
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| 97 |
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| 98 | if (!offspring.SubScopes[i].Variables.TryGetValue(operatorName, out tmpVar))
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| 99 | throw new InvalidOperationException(Name + ": Could not determine operator an offspring was created with.");
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| 100 | StringValue op = (tmpVar.Value as StringValue);
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| 101 | if (op == null) throw new InvalidOperationException(Name + ": The variable the contains the operator name must be a string.");
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| 102 |
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| 103 | if (!operatorCount.ContainsKey(op.Value)) {
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| 104 | operatorCount.Add(op.Value, 1);
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| 105 | } else {
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| 106 | operatorCount[op.Value]++;
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| 107 | }
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| 108 |
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| 109 | if (success.Value) {
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| 110 | if (!successfulOperatorCount.ContainsKey(op.Value)) {
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| 111 | successfulOperatorCount.Add(op.Value, 1);
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| 112 | } else {
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| 113 | successfulOperatorCount[op.Value]++;
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| 114 | }
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| 115 | }
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| 116 | }
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| 117 |
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| 118 | dynamic opCrossover = (dynamic)crossover;
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| 119 | int crossoverCount = (int)opCrossover.Operators.Count;
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| 120 | int checkedCrossoverCount = Enumerable.Count(opCrossover.Operators.CheckedItems);
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| 121 | dynamic[] crossoverNames = new dynamic[checkedCrossoverCount];
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| 122 | dynamic checkedItemsArray = Enumerable.ToArray(opCrossover.Operators.CheckedItems);
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| 123 |
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| 124 | for (int i = 0; i < checkedCrossoverCount; i++) {
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| 125 | crossoverNames[i] = checkedItemsArray[i];
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| 126 | }
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| 127 |
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| 128 | //fill probabilities vector
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| 129 | for (int i = 0; i < crossoverCount; i++) {
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| 130 | var cxNames = Enumerable.Where(crossoverNames, x => x.Index == i);
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| 131 |
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| 132 | if (Enumerable.Any(cxNames)) {
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| 133 | var cxName = (string)Enumerable.Single(cxNames).Value.ItemName;
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| 134 | if (operatorCount.Any(x => x.Key.Contains(cxName))) {
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| 135 | int overallCount = operatorCount.Single(x => x.Key.Contains(cxName)).Value;
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| 136 | int successCount = 0;
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| 137 |
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| 138 | if (successfulOperatorCount.Any(x => x.Key.Contains(cxName))) {
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| 139 | successCount = successfulOperatorCount.Single(x => x.Key.Contains(cxName)).Value;
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| 140 | }
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| 141 |
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| 142 | double ratio = successCount / (double)overallCount;
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| 143 | if (ratio < MinimumOperatorUsageParameter.Value.Value) {
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| 144 | ratio = MinimumOperatorUsageParameter.Value.Value;
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| 145 | }
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| 146 | ProbablilitiesParameter.ActualValue[i] = ratio;
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| 147 | } else {
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| 148 | ProbablilitiesParameter.ActualValue[i] = MinimumOperatorUsageParameter.Value.Value;
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| 149 | }
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| 150 | } else {
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| 151 | ProbablilitiesParameter.ActualValue[i] = 0.0;
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| 152 | }
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| 153 | }
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| 154 | }
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| 155 |
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| 156 | return base.Apply();
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| 157 | }
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| 158 | }
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| 159 | }
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