#region License Information
/* HeuristicLab
* Copyright (C) 2002-2010 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.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.RealVectorEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Operators;
using HeuristicLab.Optimization.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.PluginInfrastructure;
using HeuristicLab.Random;
using HeuristicLab.Analysis;
namespace HeuristicLab.Algorithms.ParticleSwarmOptimization {
[Item("Particle Swarm Optimization", "A particle swarm optimization algorithm.")]
[Creatable("Algorithms")]
[StorableClass]
public sealed class ParticleSwarmOptimization : EngineAlgorithm {
#region Problem Properties
public override Type ProblemType {
get { return typeof(ISingleObjectiveProblem); }
}
public new ISingleObjectiveProblem Problem {
get { return (ISingleObjectiveProblem)base.Problem; }
set { base.Problem = value; }
}
public IRealVectorEncoder Encoder {
get { return EncoderParameter.Value; }
set { EncoderParameter.Value = value; }
}
public MultiAnalyzer Analyzer {
get { return AnalyzerParameter.Value; }
set { AnalyzerParameter.Value = value; }
}
#endregion
#region Parameter Properties
private ValueParameter SeedParameter {
get { return (ValueParameter)Parameters["Seed"]; }
}
private ValueParameter SetSeedRandomlyParameter {
get { return (ValueParameter)Parameters["SetSeedRandomly"]; }
}
private ValueParameter SwarmSizeParameter {
get { return (ValueParameter)Parameters["SwarmSize"]; }
}
private ValueParameter MaxIterationsParameter {
get { return (ValueParameter)Parameters["MaxIterations"]; }
}
private OptionalConstrainedValueParameter EncoderParameter {
get { return (OptionalConstrainedValueParameter)Parameters["Encoder"]; }
}
private ValueParameter AnalyzerParameter {
get { return (ValueParameter)Parameters["Analyzer"]; }
}
#endregion
#region Properties
[Storable]
private ParticleSwarmOptimizationMainLoop mainLoop; // Check this !
private ParticleSwarmOptimizationMainLoop MainLoop {
get { return mainLoop; }
}
[Storable]
private Assigner bestLocalQualityInitalizer; // Check this !
private Assigner BestLocalQualityInitalizer {
get { return bestLocalQualityInitalizer; }
}
[Storable]
private BestAverageWorstQualityAnalyzer qualityAnalyzer;
#endregion
public ParticleSwarmOptimization()
: base() {
Parameters.Add(new ValueParameter("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
Parameters.Add(new ValueParameter("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
Parameters.Add(new ValueParameter("SwarmSize", "Size of the particle swarm.", new IntValue(10)));
Parameters.Add(new ValueParameter("MaxIterations", "Maximal number of iterations.", new IntValue(1000)));
Parameters.Add(new ConstrainedValueParameter("Encoder", "The operator used to encode solutions as position vector."));
Parameters.Add(new ValueParameter("Analyzer", "The operator used to analyze each generation.", new MultiAnalyzer()));
RandomCreator randomCreator = new RandomCreator();
SolutionsCreator solutionsCreator = new SolutionsCreator();
UniformSubScopesProcessor uniformSubScopesProcessor = new UniformSubScopesProcessor();
UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
VariableCreator variableCreator = new VariableCreator();
VariableCreator localVariableCreator = new VariableCreator();
Placeholder encoder = new Placeholder();
UniformRandomRealVectorCreator velocityVectorCreator = new UniformRandomRealVectorCreator();
bestLocalQualityInitalizer = new Assigner();
Assigner bestLocalPositionInitalizer = new Assigner();
Assigner bestGlobalPositionInitalizer = new Assigner();
mainLoop = new ParticleSwarmOptimizationMainLoop();
BestAverageWorstQualityCalculator bawCalculator = new BestAverageWorstQualityCalculator();
Comparator comparator = new Comparator();
ConditionalBranch branch = new ConditionalBranch();
variableCreator.CollectedValues.Add(new ValueParameter("CurrentBestPosition", new RealVector()));
variableCreator.CollectedValues.Add(new ValueParameter("ZeroBounds", new DoubleMatrix(new double[,] { { 0, 0 } })));
variableCreator.CollectedValues.Add(new ValueParameter("Length", new IntValue(2)));
localVariableCreator.CollectedValues.Add(new ValueParameter("BestQuality", new DoubleValue(0)));
localVariableCreator.CollectedValues.Add(new ValueParameter("BestPosition", new RealVector()));
randomCreator.RandomParameter.ActualName = "Random";
randomCreator.SeedParameter.ActualName = SeedParameter.Name;
randomCreator.SeedParameter.Value = null;
randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
randomCreator.SetSeedRandomlyParameter.Value = null;
solutionsCreator.NumberOfSolutionsParameter.ActualName = SwarmSizeParameter.Name;
encoder.OperatorParameter.ActualName = "Encoder";
velocityVectorCreator.BoundsParameter.ActualName = "ZeroBounds";
velocityVectorCreator.RealVectorParameter.ActualName = "Velocity";
bestLocalQualityInitalizer.LeftSideParameter.ActualName = "BestQuality"; // cloned value
bestLocalQualityInitalizer.RightSideParameter.ActualName = "Quality"; // FIXME!!! Should be mapped
bestLocalPositionInitalizer.LeftSideParameter.ActualName = "BestPosition";
bestLocalPositionInitalizer.RightSideParameter.ActualName = "Position"; // FixMe
bestGlobalPositionInitalizer.LeftSideParameter.ActualName = "CurrentBestPosition";
bestGlobalPositionInitalizer.RightSideParameter.ActualName = "BestPosition";
bawCalculator.AverageQualityParameter.ActualName = "CurrentAverageBestQuality";
bawCalculator.BestQualityParameter.ActualName = "CurrentBestBestQuality";
bawCalculator.MaximizationParameter.ActualName = "Maximization"; // FIXME
bawCalculator.QualityParameter.ActualName = "Quality";
bawCalculator.WorstQualityParameter.ActualName = "CurrentWorstBestQuality";
comparator.Comparison = new Comparison(ComparisonType.Equal);
comparator.LeftSideParameter.ActualName = "Quality";
comparator.ResultParameter.ActualName = "NewGlobalBest";
comparator.RightSideParameter.ActualName = "CurrentBestBestQuality";
branch.ConditionParameter.ActualName = "NewGlobalBest";
branch.TrueBranch = bestGlobalPositionInitalizer; // copy position vector
mainLoop.MaximumGenerationsParameter.ActualName = MaxIterationsParameter.Name;
mainLoop.ResultsParameter.ActualName = "Results";
mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
OperatorGraph.InitialOperator = randomCreator;
randomCreator.Successor = solutionsCreator;
solutionsCreator.Successor = variableCreator;
variableCreator.Successor = uniformSubScopesProcessor;
uniformSubScopesProcessor.Operator = encoder;
encoder.Successor = velocityVectorCreator;
velocityVectorCreator.Successor = localVariableCreator;
localVariableCreator.Successor = bestLocalQualityInitalizer;
bestLocalQualityInitalizer.Successor = bestLocalPositionInitalizer;
uniformSubScopesProcessor.Successor = bawCalculator; // mainLoop;
bawCalculator.Successor = uniformSubScopesProcessor2;
uniformSubScopesProcessor2.Operator = comparator;
comparator.Successor = branch;
uniformSubScopesProcessor2.Successor = mainLoop;
InitializeAnalyzers();
UpdateAnalyzers();
Initialize();
}
[StorableHook(HookType.AfterDeserialization)]
private void Initialize() {
EncoderParameter.ValueChanged += new EventHandler(EncoderParameter_ValueChanged);
if (Problem != null) {
bestLocalQualityInitalizer.RightSideParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
}
}
[StorableConstructor]
private ParticleSwarmOptimization(bool deserializing) : base(deserializing) { }
public override IDeepCloneable Clone(Cloner cloner) {
ParticleSwarmOptimization clone = (ParticleSwarmOptimization)base.Clone(cloner);
clone.Initialize();
return clone;
}
public override void Prepare() {
if (Problem != null) base.Prepare();
}
#region Events
protected override void OnProblemChanged() {
UpdateEncoders();
UpdateAnalyzers();
ParameterizeAnalyzers();
bestLocalQualityInitalizer.RightSideParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
MainLoop.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
base.OnProblemChanged();
}
private void EncoderParameter_ValueChanged(object sender, EventArgs e) {
//MainLoop.EncoderParameter.ActualValue = (IRealVectorEncoder) EncoderParameter.ActualValue;
//((UniformSubScopesProcessor)((VariableCreator)((SolutionsCreator)((RandomCreator)OperatorGraph.InitialOperator).Successor).Successor).Successor).Operator = EncoderParameter.Value;
//((SingleSuccessorOperator)EncoderParameter.Value).Successor = ((SingleSuccessorOperator)old).Successor;
}
#endregion
#region Helpers
private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
//
//
}
private void UpdateEncoders() {
IRealVectorEncoder oldEncoder = EncoderParameter.Value;
EncoderParameter.ValidValues.Clear();
List encoders = Problem.Operators.OfType().OrderBy(x => x.Name).ToList();
if (encoders.Count > 0) { // ToDo: Add wiring; else: use Position Vector directly --> name matching
foreach (IRealVectorEncoder encoder in Problem.Operators.OfType().OrderBy(x => x.Name)) {
EncoderParameter.ValidValues.Add(encoder);
((ILookupParameter)encoder.RealVectorParameter).ActualName = "Position";
}
if (oldEncoder != null) {
IRealVectorEncoder encoder = EncoderParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldEncoder.GetType());
if (encoder != null) EncoderParameter.Value = encoder;
}
}
}
private void InitializeAnalyzers() {
qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
ParameterizeAnalyzers();
}
private void ParameterizeAnalyzers() {
qualityAnalyzer.ResultsParameter.ActualName = "Results";
if (Problem != null) {
qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
qualityAnalyzer.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
}
}
private void UpdateAnalyzers() {
Analyzer.Operators.Clear();
if (Problem != null) {
foreach (IAnalyzer analyzer in Problem.Operators.OfType())
Analyzer.Operators.Add(analyzer);
}
Analyzer.Operators.Add(qualityAnalyzer);
}
#endregion
}
}