1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 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 HeuristicLab.Common;
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23 | using HeuristicLab.Core;
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24 | using HeuristicLab.Data;
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25 | using HeuristicLab.Operators;
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26 | using HeuristicLab.Optimization;
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27 | using HeuristicLab.Parameters;
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28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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29 | using System;
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30 | using System.Linq;
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31 |
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32 | namespace HeuristicLab.Algorithms.CMAEvolutionStrategy {
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33 | [Item("Terminator", "Decides if the algorithm should terminate or not.")]
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34 | [StorableType("0B0C59FC-C2B8-4076-9710-66FE5F45C19E")]
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35 | public class Terminator : Operator, IIterationBasedOperator, ISingleObjectiveOperator {
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36 |
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37 | protected OperatorParameter ContinueParameter {
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38 | get { return (OperatorParameter)Parameters["Continue"]; }
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39 | }
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40 | protected OperatorParameter TerminateParameter {
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41 | get { return (OperatorParameter)Parameters["Terminate"]; }
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42 | }
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43 |
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44 | public IOperator Continue {
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45 | get { return ContinueParameter.Value; }
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46 | set { ContinueParameter.Value = value; }
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47 | }
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48 |
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49 | public IOperator Terminate {
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50 | get { return TerminateParameter.Value; }
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51 | set { TerminateParameter.Value = value; }
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52 | }
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53 |
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54 | public IValueLookupParameter<BoolValue> MaximizationParameter {
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55 | get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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56 | }
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57 |
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58 | public ILookupParameter<CMAParameters> StrategyParametersParameter {
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59 | get { return (ILookupParameter<CMAParameters>)Parameters["StrategyParameters"]; }
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60 | }
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61 |
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62 | public ILookupParameter<IntValue> IterationsParameter {
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63 | get { return (ILookupParameter<IntValue>)Parameters["Iterations"]; }
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64 | }
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65 |
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66 | public IValueLookupParameter<IntValue> MaximumIterationsParameter {
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67 | get { return (IValueLookupParameter<IntValue>)Parameters["MaximumIterations"]; }
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68 | }
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69 |
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70 | public ILookupParameter<IntValue> EvaluatedSolutionsParameter {
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71 | get { return (ILookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
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72 | }
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73 |
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74 | public IValueLookupParameter<IntValue> MaximumEvaluatedSolutionsParameter {
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75 | get { return (IValueLookupParameter<IntValue>)Parameters["MaximumEvaluatedSolutions"]; }
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76 | }
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77 |
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78 | public IScopeTreeLookupParameter<DoubleValue> QualityParameter {
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79 | get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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80 | }
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81 |
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82 | public IValueLookupParameter<DoubleValue> TargetQualityParameter {
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83 | get { return (IValueLookupParameter<DoubleValue>)Parameters["TargetQuality"]; }
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84 | }
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85 |
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86 | public IValueLookupParameter<DoubleValue> MinimumQualityChangeParameter {
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87 | get { return (IValueLookupParameter<DoubleValue>)Parameters["MinimumQualityChange"]; }
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88 | }
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89 |
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90 | public IValueLookupParameter<DoubleValue> MinimumQualityHistoryChangeParameter {
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91 | get { return (IValueLookupParameter<DoubleValue>)Parameters["MinimumQualityHistoryChange"]; }
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92 | }
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93 |
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94 | public IValueLookupParameter<DoubleValue> MinimumStandardDeviationParameter {
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95 | get { return (IValueLookupParameter<DoubleValue>)Parameters["MinimumStandardDeviation"]; }
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96 | }
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97 |
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98 | public ILookupParameter<DoubleArray> InitialSigmaParameter {
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99 | get { return (ILookupParameter<DoubleArray>)Parameters["InitialSigma"]; }
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100 | }
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101 |
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102 | public IValueLookupParameter<DoubleValue> MaximumStandardDeviationChangeParameter {
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103 | get { return (IValueLookupParameter<DoubleValue>)Parameters["MaximumStandardDeviationChange"]; }
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104 | }
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105 |
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106 | public ILookupParameter<BoolValue> DegenerateStateParameter {
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107 | get { return (ILookupParameter<BoolValue>)Parameters["DegenerateState"]; }
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108 | }
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109 |
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110 | [StorableConstructor]
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111 | protected Terminator(bool deserializing) : base(deserializing) { }
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112 | protected Terminator(Terminator original, Cloner cloner)
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113 | : base(original, cloner) { }
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114 | public Terminator() {
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115 | Parameters.Add(new OperatorParameter("Continue", "The operator that is executed if the stop conditions have not been met!"));
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116 | Parameters.Add(new OperatorParameter("Terminate", "The operator that is executed if the stop conditions have been met!"));
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117 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is to be maximized and false otherwise."));
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118 | Parameters.Add(new LookupParameter<CMAParameters>("StrategyParameters", "The CMA-ES strategy parameters."));
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119 | Parameters.Add(new LookupParameter<IntValue>("Iterations", "The number of iterations passed."));
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120 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumIterations", "The maximum number of iterations."));
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121 | Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of evaluated solutions."));
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122 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumEvaluatedSolutions", "The maximum number of evaluated solutions."));
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123 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The quality of the offspring."));
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124 | Parameters.Add(new ValueLookupParameter<DoubleValue>("TargetQuality", "(stopFitness) Surpassing this quality value terminates the algorithm."));
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125 | Parameters.Add(new ValueLookupParameter<DoubleValue>("MinimumQualityChange", "(stopTolFun) If the range of fitness values is less than a certain value the algorithm terminates (set to 0 or positive value to enable)."));
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126 | Parameters.Add(new ValueLookupParameter<DoubleValue>("MinimumQualityHistoryChange", "(stopTolFunHist) If the range of fitness values is less than a certain value for a certain time the algorithm terminates (set to 0 or positive to enable)."));
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127 | Parameters.Add(new ValueLookupParameter<DoubleValue>("MinimumStandardDeviation", "(stopTolXFactor) If the standard deviation falls below a certain value the algorithm terminates (set to 0 or positive to enable)."));
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128 | Parameters.Add(new LookupParameter<DoubleArray>("InitialSigma", "The initial value for Sigma."));
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129 | Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumStandardDeviationChange", "(stopTolUpXFactor) If the standard deviation changes by a value larger than this parameter the algorithm stops (set to a value > 0 to enable)."));
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130 | Parameters.Add(new LookupParameter<BoolValue>("DegenerateState", "Whether the algorithm state has degenerated and should be terminated."));
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131 | }
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132 |
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133 | public override IDeepCloneable Clone(Cloner cloner) {
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134 | return new Terminator(this, cloner);
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135 | }
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136 |
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137 | public override IOperation Apply() {
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138 | var terminateOp = Terminate != null ? ExecutionContext.CreateOperation(Terminate) : null;
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139 |
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140 | var degenerated = DegenerateStateParameter.ActualValue.Value;
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141 | if (degenerated) return terminateOp;
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142 |
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143 | var iterations = IterationsParameter.ActualValue.Value;
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144 | var maxIterations = MaximumIterationsParameter.ActualValue.Value;
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145 | if (iterations >= maxIterations) return terminateOp;
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146 |
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147 | var evals = EvaluatedSolutionsParameter.ActualValue.Value;
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148 | var maxEvals = MaximumEvaluatedSolutionsParameter.ActualValue.Value;
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149 | if (evals >= maxEvals) return terminateOp;
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150 |
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151 | var maximization = MaximizationParameter.ActualValue.Value;
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152 | var bestQuality = QualityParameter.ActualValue.First().Value;
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153 | var targetQuality = TargetQualityParameter.ActualValue.Value;
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154 | if (iterations > 1 && (maximization && bestQuality >= targetQuality
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155 | || !maximization && bestQuality <= targetQuality)) return terminateOp;
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156 |
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157 | var sp = StrategyParametersParameter.ActualValue;
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158 | var worstQuality = QualityParameter.ActualValue.Last().Value;
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159 | var minHist = sp.QualityHistory.Min();
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160 | var maxHist = sp.QualityHistory.Max();
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161 | var change = Math.Max(maxHist, Math.Max(bestQuality, worstQuality))
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162 | - Math.Min(minHist, Math.Min(bestQuality, worstQuality));
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163 | var stopTolFun = MinimumQualityChangeParameter.ActualValue.Value;
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164 | if (change <= stopTolFun) return terminateOp;
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165 |
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166 | if (iterations > sp.QualityHistorySize &&
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167 | maxHist - minHist <= MinimumQualityHistoryChangeParameter.ActualValue.Value)
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168 | return terminateOp;
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169 |
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170 | double minSqrtdiagC = int.MaxValue, maxSqrtdiagC = int.MinValue;
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171 | for (int i = 0; i < sp.C.GetLength(0); i++) {
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172 | if (Math.Sqrt(sp.C[i, i]) < minSqrtdiagC) minSqrtdiagC = Math.Sqrt(sp.C[i, i]);
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173 | if (Math.Sqrt(sp.C[i, i]) > maxSqrtdiagC) maxSqrtdiagC = Math.Sqrt(sp.C[i, i]);
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174 | }
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175 |
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176 | var tolx = MinimumStandardDeviationParameter.ActualValue.Value;
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177 | if (sp.Sigma * maxSqrtdiagC < tolx
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178 | && sp.Sigma * sp.PC.Select(x => Math.Abs(x)).Max() < tolx) return terminateOp;
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179 |
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180 | var stopTolUpXFactor = MaximumStandardDeviationChangeParameter.ActualValue.Value;
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181 | if (sp.Sigma * maxSqrtdiagC > stopTolUpXFactor * InitialSigmaParameter.ActualValue.Max())
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182 | return terminateOp;
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183 |
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184 | return Continue != null ? ExecutionContext.CreateOperation(Continue) : null;
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185 | }
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186 | }
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187 | }
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