#region License Information /* HeuristicLab * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System; using System.Collections.Generic; using System.Drawing; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Encodings.RealVectorEncoding; using HeuristicLab.Optimization; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; using HeuristicLab.PluginInfrastructure; namespace HeuristicLab.Problems.TestFunctions { [Item("Single Objective Test Function", "Test function with real valued inputs and a single objective.")] [StorableClass] [Creatable("Problems")] public sealed class SingleObjectiveTestFunctionProblem : ParameterizedNamedItem, ISingleObjectiveHeuristicOptimizationProblem, IStorableContent { public string Filename { get; set; } [Storable] private StdDevStrategyVectorCreator strategyVectorCreator; [Storable] private StdDevStrategyVectorCrossover strategyVectorCrossover; [Storable] private StdDevStrategyVectorManipulator strategyVectorManipulator; public override Image ItemImage { get { return HeuristicLab.Common.Resources.VSImageLibrary.Type; } } #region Parameter Properties public ValueParameter MaximizationParameter { get { return (ValueParameter)Parameters["Maximization"]; } } IParameter ISingleObjectiveHeuristicOptimizationProblem.MaximizationParameter { get { return MaximizationParameter; } } public ValueParameter BoundsParameter { get { return (ValueParameter)Parameters["Bounds"]; } } public ValueParameter ProblemSizeParameter { get { return (ValueParameter)Parameters["ProblemSize"]; } } public ValueParameter SolutionCreatorParameter { get { return (ValueParameter)Parameters["SolutionCreator"]; } } IParameter IHeuristicOptimizationProblem.SolutionCreatorParameter { get { return SolutionCreatorParameter; } } public ValueParameter EvaluatorParameter { get { return (ValueParameter)Parameters["Evaluator"]; } } IParameter IHeuristicOptimizationProblem.EvaluatorParameter { get { return EvaluatorParameter; } } public OptionalValueParameter BestKnownQualityParameter { get { return (OptionalValueParameter)Parameters["BestKnownQuality"]; } } IParameter ISingleObjectiveHeuristicOptimizationProblem.BestKnownQualityParameter { get { return BestKnownQualityParameter; } } public OptionalValueParameter BestKnownSolutionParameter { get { return (OptionalValueParameter)Parameters["BestKnownSolution"]; } } #endregion #region Properties public BoolValue Maximization { get { return MaximizationParameter.Value; } set { MaximizationParameter.Value = value; } } public DoubleMatrix Bounds { get { return BoundsParameter.Value; } set { BoundsParameter.Value = value; } } public IntValue ProblemSize { get { return ProblemSizeParameter.Value; } set { ProblemSizeParameter.Value = value; } } public IRealVectorCreator SolutionCreator { get { return SolutionCreatorParameter.Value; } set { SolutionCreatorParameter.Value = value; } } ISolutionCreator IHeuristicOptimizationProblem.SolutionCreator { get { return SolutionCreatorParameter.Value; } } public ISingleObjectiveTestFunctionProblemEvaluator Evaluator { get { return EvaluatorParameter.Value; } set { EvaluatorParameter.Value = value; } } ISingleObjectiveEvaluator ISingleObjectiveHeuristicOptimizationProblem.Evaluator { get { return EvaluatorParameter.Value; } } IEvaluator IHeuristicOptimizationProblem.Evaluator { get { return EvaluatorParameter.Value; } } public DoubleValue BestKnownQuality { get { return BestKnownQualityParameter.Value; } set { BestKnownQualityParameter.Value = value; } } public IEnumerable Operators { get { return operators; } } private BestSingleObjectiveTestFunctionSolutionAnalyzer BestSingleObjectiveTestFunctionSolutionAnalyzer { get { return operators.OfType().FirstOrDefault(); } } #endregion [Storable] private List operators; [StorableConstructor] private SingleObjectiveTestFunctionProblem(bool deserializing) : base(deserializing) { } private SingleObjectiveTestFunctionProblem(SingleObjectiveTestFunctionProblem original, Cloner cloner) : base(original, cloner) { operators = original.operators.Where(x => original.IsNotFieldReferenced(x)).Select(x => cloner.Clone(x)).ToList(); strategyVectorCreator = cloner.Clone(original.strategyVectorCreator); operators.Add(strategyVectorCreator); strategyVectorCrossover = cloner.Clone(original.strategyVectorCrossover); operators.Add(strategyVectorCrossover); strategyVectorManipulator = cloner.Clone(original.strategyVectorManipulator); operators.Add(strategyVectorManipulator); AttachEventHandlers(); } public SingleObjectiveTestFunctionProblem() : base() { UniformRandomRealVectorCreator creator = new UniformRandomRealVectorCreator(); AckleyEvaluator evaluator = new AckleyEvaluator(); Parameters.Add(new ValueParameter("Maximization", "Set to false as most test functions are minimization problems.", new BoolValue(evaluator.Maximization))); Parameters.Add(new ValueParameter("Bounds", "The lower and upper bounds in each dimension.", evaluator.Bounds)); Parameters.Add(new ValueParameter("ProblemSize", "The dimension of the problem.", new IntValue(2))); Parameters.Add(new ValueParameter("SolutionCreator", "The operator which should be used to create new test function solutions.", creator)); Parameters.Add(new ValueParameter("Evaluator", "The operator which should be used to evaluate test function solutions.", evaluator)); Parameters.Add(new OptionalValueParameter("BestKnownQuality", "The quality of the best known solution of this test function.", new DoubleValue(evaluator.BestKnownQuality))); Parameters.Add(new OptionalValueParameter("BestKnownSolution", "The best known solution for this test function instance.")); strategyVectorCreator = new StdDevStrategyVectorCreator(); strategyVectorCreator.LengthParameter.ActualName = ProblemSizeParameter.Name; strategyVectorCrossover = new StdDevStrategyVectorCrossover(); strategyVectorManipulator = new StdDevStrategyVectorManipulator(); strategyVectorManipulator.LearningRateParameter.Value = new DoubleValue(0.5); strategyVectorManipulator.GeneralLearningRateParameter.Value = new DoubleValue(0.5); creator.RealVectorParameter.ActualName = "Point"; ParameterizeSolutionCreator(); ParameterizeEvaluator(); InitializeOperators(); AttachEventHandlers(); UpdateStrategyVectorBounds(); } public override IDeepCloneable Clone(Cloner cloner) { return new SingleObjectiveTestFunctionProblem(this, cloner); } private bool IsNotFieldReferenced(IOperator x) { return !(x == strategyVectorCreator || x == strategyVectorCrossover || x == strategyVectorManipulator); } #region Events public event EventHandler SolutionCreatorChanged; private void OnSolutionCreatorChanged() { EventHandler handler = SolutionCreatorChanged; if (handler != null) handler(this, EventArgs.Empty); } public event EventHandler EvaluatorChanged; private void OnEvaluatorChanged() { EventHandler handler = EvaluatorChanged; if (handler != null) handler(this, EventArgs.Empty); } public event EventHandler OperatorsChanged; private void OnOperatorsChanged() { EventHandler handler = OperatorsChanged; if (handler != null) handler(this, EventArgs.Empty); } public event EventHandler Reset; private void OnReset() { EventHandler handler = Reset; if (handler != null) handler(this, EventArgs.Empty); } private void ProblemSizeParameter_ValueChanged(object sender, EventArgs e) { ProblemSize.ValueChanged += new EventHandler(ProblemSize_ValueChanged); ProblemSize_ValueChanged(null, EventArgs.Empty); } private void ProblemSize_ValueChanged(object sender, EventArgs e) { if (ProblemSize.Value < 1) ProblemSize.Value = 1; ParameterizeSolutionCreator(); ParameterizeEvaluator(); strategyVectorManipulator.GeneralLearningRateParameter.Value = new DoubleValue(1.0 / Math.Sqrt(2 * ProblemSize.Value)); strategyVectorManipulator.LearningRateParameter.Value = new DoubleValue(1.0 / Math.Sqrt(2 * Math.Sqrt(ProblemSize.Value))); OnReset(); } private void SolutionCreatorParameter_ValueChanged(object sender, EventArgs e) { ParameterizeSolutionCreator(); ParameterizeAnalyzers(); SolutionCreator_RealVectorParameter_ActualNameChanged(null, EventArgs.Empty); OnSolutionCreatorChanged(); } private void SolutionCreator_RealVectorParameter_ActualNameChanged(object sender, EventArgs e) { ParameterizeEvaluator(); ParameterizeOperators(); ParameterizeAnalyzers(); } private void EvaluatorParameter_ValueChanged(object sender, EventArgs e) { ParameterizeEvaluator(); UpdateMoveEvaluators(); ParameterizeAnalyzers(); Maximization.Value = Evaluator.Maximization; BoundsParameter.Value = Evaluator.Bounds; if (ProblemSize.Value < Evaluator.MinimumProblemSize) ProblemSize.Value = Evaluator.MinimumProblemSize; else if (ProblemSize.Value > Evaluator.MaximumProblemSize) ProblemSize.Value = Evaluator.MaximumProblemSize; BestKnownQuality = new DoubleValue(Evaluator.BestKnownQuality); Evaluator_QualityParameter_ActualNameChanged(null, EventArgs.Empty); OnEvaluatorChanged(); OnReset(); } private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) { ParameterizeOperators(); } private void BoundsParameter_ValueChanged(object sender, EventArgs e) { Bounds.ToStringChanged += new EventHandler(Bounds_ToStringChanged); Bounds_ToStringChanged(null, EventArgs.Empty); } private void Bounds_ToStringChanged(object sender, EventArgs e) { if (Bounds.Columns != 2 || Bounds.Rows < 1) Bounds = new DoubleMatrix(1, 2); ParameterizeOperators(); UpdateStrategyVectorBounds(); } private void Bounds_ItemChanged(object sender, EventArgs e) { if (e.Value2 == 0 && Bounds[e.Value, 1] <= Bounds[e.Value, 0]) Bounds[e.Value, 1] = Bounds[e.Value, 0] + 0.1; if (e.Value2 == 1 && Bounds[e.Value, 0] >= Bounds[e.Value, 1]) Bounds[e.Value, 0] = Bounds[e.Value, 1] - 0.1; ParameterizeOperators(); UpdateStrategyVectorBounds(); } private void MoveGenerator_AdditiveMoveParameter_ActualNameChanged(object sender, EventArgs e) { string name = ((ILookupParameter)sender).ActualName; foreach (IAdditiveRealVectorMoveOperator op in Operators.OfType()) { op.AdditiveMoveParameter.ActualName = name; } } private void SphereEvaluator_Parameter_ValueChanged(object sender, EventArgs e) { SphereEvaluator eval = (Evaluator as SphereEvaluator); if (eval != null) { foreach (ISphereMoveEvaluator op in Operators.OfType()) { op.C = eval.C; op.Alpha = eval.Alpha; } } } private void RastriginEvaluator_Parameter_ValueChanged(object sender, EventArgs e) { RastriginEvaluator eval = (Evaluator as RastriginEvaluator); if (eval != null) { foreach (IRastriginMoveEvaluator op in Operators.OfType()) { op.A = eval.A; } } } private void strategyVectorCreator_BoundsParameter_ValueChanged(object sender, EventArgs e) { strategyVectorManipulator.BoundsParameter.Value = (DoubleMatrix)strategyVectorCreator.BoundsParameter.Value.Clone(); } private void strategyVectorCreator_StrategyParameterParameter_ActualNameChanged(object sender, EventArgs e) { string name = strategyVectorCreator.StrategyParameterParameter.ActualName; strategyVectorCrossover.ParentsParameter.ActualName = name; strategyVectorCrossover.StrategyParameterParameter.ActualName = name; strategyVectorManipulator.StrategyParameterParameter.ActualName = name; } #endregion #region Helpers [StorableHook(HookType.AfterDeserialization)] private void AfterDeserialization() { // BackwardsCompatibility3.3 #region Backwards compatible code (remove with 3.4) if (operators == null) InitializeOperators(); #endregion AttachEventHandlers(); } private void AttachEventHandlers() { ProblemSizeParameter.ValueChanged += new EventHandler(ProblemSizeParameter_ValueChanged); ProblemSize.ValueChanged += new EventHandler(ProblemSize_ValueChanged); BoundsParameter.ValueChanged += new EventHandler(BoundsParameter_ValueChanged); Bounds.ToStringChanged += new EventHandler(Bounds_ToStringChanged); Bounds.ItemChanged += new EventHandler>(Bounds_ItemChanged); SolutionCreatorParameter.ValueChanged += new EventHandler(SolutionCreatorParameter_ValueChanged); SolutionCreator.RealVectorParameter.ActualNameChanged += new EventHandler(SolutionCreator_RealVectorParameter_ActualNameChanged); EvaluatorParameter.ValueChanged += new EventHandler(EvaluatorParameter_ValueChanged); Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged); strategyVectorCreator.BoundsParameter.ValueChanged += new EventHandler(strategyVectorCreator_BoundsParameter_ValueChanged); strategyVectorCreator.StrategyParameterParameter.ActualNameChanged += new EventHandler(strategyVectorCreator_StrategyParameterParameter_ActualNameChanged); } private void ParameterizeAnalyzers() { BestSingleObjectiveTestFunctionSolutionAnalyzer.RealVectorParameter.ActualName = SolutionCreator.RealVectorParameter.ActualName; BestSingleObjectiveTestFunctionSolutionAnalyzer.ResultsParameter.ActualName = "Results"; BestSingleObjectiveTestFunctionSolutionAnalyzer.QualityParameter.ActualName = Evaluator.QualityParameter.ActualName; BestSingleObjectiveTestFunctionSolutionAnalyzer.BestKnownQualityParameter.ActualName = BestKnownQualityParameter.Name; BestSingleObjectiveTestFunctionSolutionAnalyzer.BestKnownSolutionParameter.ActualName = BestKnownSolutionParameter.Name; BestSingleObjectiveTestFunctionSolutionAnalyzer.MaximizationParameter.ActualName = MaximizationParameter.Name; BestSingleObjectiveTestFunctionSolutionAnalyzer.EvaluatorParameter.ActualName = EvaluatorParameter.Name; BestSingleObjectiveTestFunctionSolutionAnalyzer.BoundsParameter.ActualName = BoundsParameter.Name; } private void InitializeOperators() { operators = new List(); operators.Add(new BestSingleObjectiveTestFunctionSolutionAnalyzer()); ParameterizeAnalyzers(); operators.AddRange(ApplicationManager.Manager.GetInstances().Cast()); operators.Add(strategyVectorCreator); operators.Add(strategyVectorCrossover); operators.Add(strategyVectorManipulator); UpdateMoveEvaluators(); ParameterizeOperators(); InitializeMoveGenerators(); } private void InitializeMoveGenerators() { foreach (IAdditiveRealVectorMoveOperator op in Operators.OfType()) { if (op is IMoveGenerator) { op.AdditiveMoveParameter.ActualNameChanged += new EventHandler(MoveGenerator_AdditiveMoveParameter_ActualNameChanged); } } } private void UpdateMoveEvaluators() { foreach (ISingleObjectiveTestFunctionMoveEvaluator op in Operators.OfType().ToList()) operators.Remove(op); foreach (ISingleObjectiveTestFunctionMoveEvaluator op in ApplicationManager.Manager.GetInstances()) if (op.EvaluatorType == Evaluator.GetType()) { operators.Add(op); #region Synchronize evaluator specific parameters with the parameters of the corresponding move evaluators if (op is ISphereMoveEvaluator) { SphereEvaluator e = (Evaluator as SphereEvaluator); e.AlphaParameter.ValueChanged += new EventHandler(SphereEvaluator_Parameter_ValueChanged); e.CParameter.ValueChanged += new EventHandler(SphereEvaluator_Parameter_ValueChanged); ISphereMoveEvaluator em = (op as ISphereMoveEvaluator); em.C = e.C; em.Alpha = e.Alpha; } else if (op is IRastriginMoveEvaluator) { RastriginEvaluator e = (Evaluator as RastriginEvaluator); e.AParameter.ValueChanged += new EventHandler(RastriginEvaluator_Parameter_ValueChanged); IRastriginMoveEvaluator em = (op as IRastriginMoveEvaluator); em.A = e.A; } #endregion } ParameterizeOperators(); OnOperatorsChanged(); } private void ParameterizeSolutionCreator() { SolutionCreator.LengthParameter.Value = new IntValue(ProblemSize.Value); } private void ParameterizeEvaluator() { Evaluator.PointParameter.ActualName = SolutionCreator.RealVectorParameter.ActualName; BestKnownSolutionParameter.Value = Evaluator.GetBestKnownSolution(ProblemSize.Value); } private void ParameterizeOperators() { foreach (IRealVectorCrossover op in Operators.OfType()) { op.ParentsParameter.ActualName = SolutionCreator.RealVectorParameter.ActualName; op.ChildParameter.ActualName = SolutionCreator.RealVectorParameter.ActualName; op.BoundsParameter.ActualName = BoundsParameter.Name; } foreach (IRealVectorManipulator op in Operators.OfType()) { op.RealVectorParameter.ActualName = SolutionCreator.RealVectorParameter.ActualName; op.BoundsParameter.ActualName = BoundsParameter.Name; } foreach (IRealVectorMoveOperator op in Operators.OfType()) { op.RealVectorParameter.ActualName = SolutionCreator.RealVectorParameter.ActualName; } foreach (IRealVectorMoveGenerator op in Operators.OfType()) { op.BoundsParameter.ActualName = BoundsParameter.Name; } foreach (ISingleObjectiveTestFunctionAdditiveMoveEvaluator op in Operators.OfType()) { op.QualityParameter.ActualName = Evaluator.QualityParameter.ActualName; op.RealVectorParameter.ActualName = SolutionCreator.RealVectorParameter.ActualName; } foreach (IRealVectorParticleCreator op in Operators.OfType()) { op.RealVectorParameter.ActualName = SolutionCreator.RealVectorParameter.ActualName; op.BoundsParameter.ActualName = BoundsParameter.Name; op.ProblemSizeParameter.ActualName = ProblemSizeParameter.Name; } foreach (IRealVectorParticleUpdater op in Operators.OfType()) { op.RealVectorParameter.ActualName = SolutionCreator.RealVectorParameter.ActualName; op.BoundsParameter.ActualName = BoundsParameter.Name; } foreach (IRealVectorSwarmUpdater op in Operators.OfType()) { op.RealVectorParameter.ActualName = SolutionCreator.RealVectorParameter.ActualName; op.MaximizationParameter.ActualName = MaximizationParameter.Name; } } private void UpdateStrategyVectorBounds() { DoubleMatrix strategyBounds = (DoubleMatrix)Bounds.Clone(); for (int i = 0; i < strategyBounds.Rows; i++) { if (strategyBounds[i, 0] < 0) strategyBounds[i, 0] = 0; strategyBounds[i, 1] = 0.1 * (Bounds[i, 1] - Bounds[i, 0]); } strategyVectorCreator.BoundsParameter.Value = strategyBounds; } #endregion } }