#region License Information
/* HeuristicLab
* Copyright (C) 2002-2015 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.Linq;
using HeuristicLab.Analysis;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Optimization.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Random;
using HeuristicLab.Selection;
namespace HeuristicLab.Algorithms.ScatterSearch {
///
/// A scatter search algorithm.
///
[Item("Scatter Search", "A scatter search algorithm.")]
[Creatable("Algorithms")]
[StorableClass]
public sealed class ScatterSearch : HeuristicOptimizationEngineAlgorithm, IStorableContent {
public string Filename { get; set; }
#region Problem Properties
public override Type ProblemType {
get { return typeof(ISingleObjectiveHeuristicOptimizationProblem); }
}
public new ISingleObjectiveHeuristicOptimizationProblem Problem {
get { return (ISingleObjectiveHeuristicOptimizationProblem)base.Problem; }
set { base.Problem = value; }
}
#endregion
#region Parameter Properties
public IValueParameter AnalyzerParameter {
get { return (IValueParameter)Parameters["Analyzer"]; }
}
public IConstrainedValueParameter CrossoverParameter {
get { return (IConstrainedValueParameter)Parameters["Crossover"]; }
}
public IValueParameter ExecutePathRelinkingParameter {
get { return (IValueParameter)Parameters["ExecutePathRelinking"]; }
}
public IConstrainedValueParameter ImproverParameter {
get { return (IConstrainedValueParameter)Parameters["Improver"]; }
}
public IValueParameter MaximumIterationsParameter {
get { return (IValueParameter)Parameters["MaximumIterations"]; }
}
public IValueParameter NumberOfHighQualitySolutionsParameter {
get { return (IValueParameter)Parameters["NumberOfHighQualitySolutions"]; }
}
public IConstrainedValueParameter PathRelinkerParameter {
get { return (IConstrainedValueParameter)Parameters["PathRelinker"]; }
}
public IValueParameter PopulationSizeParameter {
get { return (IValueParameter)Parameters["PopulationSize"]; }
}
public IValueParameter ReferenceSetSizeParameter {
get { return (IValueParameter)Parameters["ReferenceSetSize"]; }
}
public IValueParameter SeedParameter {
get { return (IValueParameter)Parameters["Seed"]; }
}
public IValueParameter SetSeedRandomlyParameter {
get { return (IValueParameter)Parameters["SetSeedRandomly"]; }
}
public IConstrainedValueParameter SimilarityCalculatorParameter {
get { return (IConstrainedValueParameter)Parameters["SimilarityCalculator"]; }
}
#endregion
#region Properties
public MultiAnalyzer Analyzer {
get { return AnalyzerParameter.Value; }
set { AnalyzerParameter.Value = value; }
}
public ICrossover Crossover {
get { return CrossoverParameter.Value; }
set { CrossoverParameter.Value = value; }
}
public BoolValue ExecutePathRelinking {
get { return ExecutePathRelinkingParameter.Value; }
set { ExecutePathRelinkingParameter.Value = value; }
}
public IImprovementOperator Improver {
get { return ImproverParameter.Value; }
set { ImproverParameter.Value = value; }
}
public IntValue MaximumIterations {
get { return MaximumIterationsParameter.Value; }
set { MaximumIterationsParameter.Value = value; }
}
public IntValue NumberOfHighQualitySolutions {
get { return NumberOfHighQualitySolutionsParameter.Value; }
set { NumberOfHighQualitySolutionsParameter.Value = value; }
}
public IPathRelinker PathRelinker {
get { return PathRelinkerParameter.Value; }
set { PathRelinkerParameter.Value = value; }
}
public IntValue PopulationSize {
get { return PopulationSizeParameter.Value; }
set { PopulationSizeParameter.Value = value; }
}
public IntValue ReferenceSetSize {
get { return ReferenceSetSizeParameter.Value; }
set { ReferenceSetSizeParameter.Value = value; }
}
public IntValue Seed {
get { return SeedParameter.Value; }
set { SeedParameter.Value = value; }
}
public BoolValue SetSeedRandomly {
get { return SetSeedRandomlyParameter.Value; }
set { SetSeedRandomlyParameter.Value = value; }
}
public ISingleObjectiveSolutionSimilarityCalculator SimilarityCalculator {
get { return SimilarityCalculatorParameter.Value; }
set { SimilarityCalculatorParameter.Value = value; }
}
private RandomCreator RandomCreator {
get { return (RandomCreator)OperatorGraph.InitialOperator; }
}
private SolutionsCreator SolutionsCreator {
get { return (SolutionsCreator)RandomCreator.Successor; }
}
private ScatterSearchMainLoop MainLoop {
get { return FindMainLoop(SolutionsCreator.Successor); }
}
[Storable]
private BestAverageWorstQualityAnalyzer qualityAnalyzer;
#endregion
[StorableConstructor]
private ScatterSearch(bool deserializing) : base(deserializing) { }
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() {
Initialize();
}
private ScatterSearch(ScatterSearch original, Cloner cloner)
: base(original, cloner) {
qualityAnalyzer = cloner.Clone(original.qualityAnalyzer);
Initialize();
}
public override IDeepCloneable Clone(Cloner cloner) {
return new ScatterSearch(this, cloner);
}
public ScatterSearch()
: base() {
#region Create parameters
Parameters.Add(new ValueParameter("Analyzer", "The analyzer used to analyze each iteration.", new MultiAnalyzer()));
Parameters.Add(new ConstrainedValueParameter("Crossover", "The operator used to cross solutions."));
Parameters.Add(new ValueParameter("ExecutePathRelinking", "True if path relinking should be executed instead of crossover, otherwise false.", new BoolValue(false)));
Parameters.Add(new ConstrainedValueParameter("Improver", "The operator used to improve solutions."));
Parameters.Add(new ValueParameter("MaximumIterations", "The maximum number of iterations which should be processed.", new IntValue(100)));
Parameters.Add(new ValueParameter("NumberOfHighQualitySolutions", "The number of high quality solutions in the reference set.", new IntValue(5)));
Parameters.Add(new ConstrainedValueParameter("PathRelinker", "The operator used to execute path relinking."));
Parameters.Add(new ValueParameter("PopulationSize", "The size of the population of solutions.", new IntValue(50)));
Parameters.Add(new ValueParameter("ReferenceSetSize", "The size of the reference set.", new IntValue(20)));
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 ConstrainedValueParameter("SimilarityCalculator", "The operator used to calculate the similarity between two solutions."));
#endregion
#region Create operators
RandomCreator randomCreator = new RandomCreator();
SolutionsCreator solutionsCreator = new SolutionsCreator();
UniformSubScopesProcessor uniformSubScopesProcessor = new UniformSubScopesProcessor();
Placeholder solutionEvaluator = new Placeholder();
Placeholder solutionImprover = new Placeholder();
VariableCreator variableCreator = new VariableCreator();
DataReducer dataReducer = new DataReducer();
ResultsCollector resultsCollector = new ResultsCollector();
BestSelector bestSelector = new BestSelector();
ScatterSearchMainLoop mainLoop = new ScatterSearchMainLoop();
#endregion
#region Create operator graph
OperatorGraph.InitialOperator = randomCreator;
randomCreator.RandomParameter.ActualName = "Random";
randomCreator.SeedParameter.ActualName = SeedParameter.Name;
randomCreator.SeedParameter.Value = null;
randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
randomCreator.SetSeedRandomlyParameter.Value = null;
randomCreator.Successor = solutionsCreator;
solutionsCreator.Name = "DiversificationGenerationMethod";
solutionsCreator.NumberOfSolutionsParameter.ActualName = "PopulationSize";
solutionsCreator.Successor = uniformSubScopesProcessor;
uniformSubScopesProcessor.Operator = solutionImprover;
uniformSubScopesProcessor.ParallelParameter.Value = new BoolValue(true);
uniformSubScopesProcessor.Successor = variableCreator;
solutionImprover.Name = "SolutionImprover";
solutionImprover.OperatorParameter.ActualName = "Improver";
solutionImprover.Successor = solutionEvaluator;
solutionEvaluator.Name = "SolutionEvaluator";
solutionEvaluator.OperatorParameter.ActualName = "Evaluator";
solutionEvaluator.Successor = null;
variableCreator.Name = "Initialize EvaluatedSolutions";
variableCreator.CollectedValues.Add(new ValueParameter("EvaluatedSolutions", new IntValue()));
variableCreator.Successor = dataReducer;
dataReducer.Name = "Increment EvaluatedSolutions";
dataReducer.ParameterToReduce.ActualName = "LocalEvaluatedSolutions";
dataReducer.TargetParameter.ActualName = "EvaluatedSolutions";
dataReducer.ReductionOperation.Value = new ReductionOperation(ReductionOperations.Sum);
dataReducer.TargetOperation.Value = new ReductionOperation(ReductionOperations.Sum);
dataReducer.Successor = resultsCollector;
resultsCollector.Name = "ResultsCollector";
resultsCollector.CollectedValues.Add(new LookupParameter("EvaluatedSolutions", null, "EvaluatedSolutions"));
resultsCollector.Successor = bestSelector;
bestSelector.NumberOfSelectedSubScopesParameter.ActualName = NumberOfHighQualitySolutionsParameter.Name;
bestSelector.CopySelected = new BoolValue(false);
bestSelector.Successor = mainLoop;
mainLoop.MaximumIterationsParameter.ActualName = MaximumIterationsParameter.Name;
mainLoop.RandomParameter.ActualName = randomCreator.RandomParameter.ActualName;
mainLoop.ResultsParameter.ActualName = "Results";
mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
mainLoop.IterationsParameter.ActualName = "Iterations";
mainLoop.EvaluatedSolutionsParameter.ActualName = "EvaluatedSolutions";
mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
mainLoop.PopulationSizeParameter.ActualName = PopulationSizeParameter.Name;
mainLoop.NumberOfHighQualitySolutionsParameter.ActualName = NumberOfHighQualitySolutionsParameter.Name;
mainLoop.Successor = null;
#endregion
qualityAnalyzer = new BestAverageWorstQualityAnalyzer();
ParameterizeAnalyzers();
UpdateAnalyzers();
Initialize();
}
public override void Prepare() {
if (Problem != null && Improver != null && (PathRelinker != null || ExecutePathRelinking.Value == false) && SimilarityCalculator != null)
base.Prepare();
}
#region Events
protected override void OnProblemChanged() {
ParameterizeStochasticOperator(Problem.SolutionCreator);
ParameterizeStochasticOperator(Problem.Evaluator);
foreach (IOperator op in Problem.Operators.OfType()) ParameterizeStochasticOperator(op);
ParameterizeAnalyzers();
ParameterizeSolutionsCreator();
ParameterizeBestSelector();
UpdateAnalyzers();
UpdateCrossovers();
UpdateImprovers();
UpdatePathRelinkers();
UpdateSimilarityCalculators();
ParameterizeMainLoop();
Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
base.OnProblemChanged();
}
protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
ParameterizeStochasticOperator(Problem.SolutionCreator);
ParameterizeSolutionsCreator();
base.Problem_SolutionCreatorChanged(sender, e);
}
protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
ParameterizeStochasticOperator(Problem.Evaluator);
ParameterizeSolutionsCreator();
ParameterizeMainLoop();
ParameterizeAnalyzers();
Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
base.Problem_EvaluatorChanged(sender, e);
}
protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
foreach (IOperator op in Problem.Operators.OfType()) ParameterizeStochasticOperator(op);
UpdateAnalyzers();
UpdateCrossovers();
UpdatePathRelinkers();
UpdateSimilarityCalculators();
UpdateImprovers();
ParameterizeMainLoop();
ParameterizeAnalyzers();
base.Problem_OperatorsChanged(sender, e);
}
private void PathRelinkerParameter_ValueChanged(object sender, EventArgs e) {
ExecutePathRelinking.Value = PathRelinkerParameter.Value != null;
}
private void SimilarityCalculatorParameter_ValueChanged(object sender, EventArgs e) {
ParameterizeMainLoop();
}
private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
ParameterizeMainLoop();
ParameterizeAnalyzers();
ParameterizeBestSelector();
ParameterizeSimilarityCalculators();
}
#endregion
#region Helpers
private void Initialize() {
PathRelinkerParameter.ValueChanged += new EventHandler(PathRelinkerParameter_ValueChanged);
SimilarityCalculatorParameter.ValueChanged += new EventHandler(SimilarityCalculatorParameter_ValueChanged);
if (Problem != null)
Problem.Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
}
private void UpdateAnalyzers() {
Analyzer.Operators.Clear();
if (Problem != null) {
foreach (IAnalyzer analyzer in Problem.Operators.OfType()) {
foreach (IScopeTreeLookupParameter param in analyzer.Parameters.OfType())
param.Depth = 1;
Analyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
}
}
Analyzer.Operators.Add(qualityAnalyzer, qualityAnalyzer.EnabledByDefault);
}
private void UpdateCrossovers() {
ICrossover oldCrossover = CrossoverParameter.Value;
CrossoverParameter.ValidValues.Clear();
ICrossover defaultCrossover = Problem.Operators.OfType().FirstOrDefault();
foreach (ICrossover crossover in Problem.Operators.OfType().OrderBy(x => x.Name))
CrossoverParameter.ValidValues.Add(crossover);
if (oldCrossover != null) {
ICrossover crossover = CrossoverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldCrossover.GetType());
if (crossover != null) CrossoverParameter.Value = crossover;
else oldCrossover = null;
}
if (oldCrossover == null && defaultCrossover != null)
CrossoverParameter.Value = defaultCrossover;
}
private void UpdateImprovers() {
IImprovementOperator oldImprover = ImproverParameter.Value;
ImproverParameter.ValidValues.Clear();
IImprovementOperator defaultImprover = Problem.Operators.OfType().FirstOrDefault();
foreach (IImprovementOperator improver in Problem.Operators.OfType().OrderBy(x => x.Name))
ImproverParameter.ValidValues.Add(improver);
if (oldImprover != null) {
IImprovementOperator improver = ImproverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldImprover.GetType());
if (improver != null) ImproverParameter.Value = improver;
else oldImprover = null;
}
if (oldImprover == null && defaultImprover != null)
ImproverParameter.Value = defaultImprover;
}
private void UpdatePathRelinkers() {
IPathRelinker oldPathRelinker = PathRelinkerParameter.Value;
PathRelinkerParameter.ValidValues.Clear();
IPathRelinker defaultPathRelinker = Problem.Operators.OfType().FirstOrDefault();
foreach (IPathRelinker pathRelinker in Problem.Operators.OfType().OrderBy(x => x.Name))
PathRelinkerParameter.ValidValues.Add(pathRelinker);
if (oldPathRelinker != null) {
IPathRelinker pathRelinker = PathRelinkerParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldPathRelinker.GetType());
if (pathRelinker != null) PathRelinkerParameter.Value = pathRelinker;
else oldPathRelinker = null;
}
if (oldPathRelinker == null && defaultPathRelinker != null)
PathRelinkerParameter.Value = defaultPathRelinker;
}
private void UpdateSimilarityCalculators() {
ISingleObjectiveSolutionSimilarityCalculator oldSimilarityCalculator = SimilarityCalculatorParameter.Value;
SimilarityCalculatorParameter.ValidValues.Clear();
ISingleObjectiveSolutionSimilarityCalculator defaultSimilarityCalculator = Problem.Operators.OfType().FirstOrDefault();
SimilarityCalculatorParameter.ValidValues.Add(new QualitySimilarityCalculator { QualityVariableName = Problem.Evaluator.QualityParameter.ActualName });
SimilarityCalculatorParameter.ValidValues.Add(new NoSimilarityCalculator { QualityVariableName = Problem.Evaluator.QualityParameter.ActualName });
foreach (ISingleObjectiveSolutionSimilarityCalculator similarityCalculator in Problem.Operators.OfType())
SimilarityCalculatorParameter.ValidValues.Add(similarityCalculator);
if (oldSimilarityCalculator != null) {
ISingleObjectiveSolutionSimilarityCalculator similarityCalculator = SimilarityCalculatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldSimilarityCalculator.GetType());
if (similarityCalculator != null) SimilarityCalculatorParameter.Value = similarityCalculator;
else oldSimilarityCalculator = null;
}
if (oldSimilarityCalculator == null && defaultSimilarityCalculator != null)
SimilarityCalculatorParameter.Value = defaultSimilarityCalculator;
}
private void ParameterizeBestSelector() {
OperatorGraph.Operators.OfType()
.First().QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
}
private void ParameterizeSolutionsCreator() {
SolutionsCreator.EvaluatorParameter.ActualName = Problem.EvaluatorParameter.Name;
SolutionsCreator.SolutionCreatorParameter.ActualName = Problem.SolutionCreatorParameter.Name;
}
private void ParameterizeMainLoop() {
if (Problem != null && Improver != null) {
MainLoop.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
MainLoop.OperatorGraph.Operators.OfType().Single().QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
MainLoop.OperatorGraph.Operators.OfType().Single().QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
}
}
private void ParameterizeStochasticOperator(IOperator op) {
if (op is IStochasticOperator) {
IStochasticOperator stOp = (IStochasticOperator)op;
stOp.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
stOp.RandomParameter.Hidden = true;
}
}
private void ParameterizeAnalyzers() {
qualityAnalyzer.ResultsParameter.ActualName = "Results";
qualityAnalyzer.ResultsParameter.Hidden = true;
if (Problem != null) {
qualityAnalyzer.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
qualityAnalyzer.MaximizationParameter.Hidden = true;
qualityAnalyzer.QualityParameter.Hidden = false;
qualityAnalyzer.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name;
qualityAnalyzer.BestKnownQualityParameter.Hidden = true;
} else {
qualityAnalyzer.MaximizationParameter.Hidden = false;
qualityAnalyzer.BestKnownQualityParameter.Hidden = false;
}
}
private void ParameterizeSimilarityCalculators() {
foreach (ISingleObjectiveSolutionSimilarityCalculator calc in SimilarityCalculatorParameter.ValidValues) {
calc.QualityVariableName = Problem.Evaluator.QualityParameter.ActualName;
}
}
private ScatterSearchMainLoop FindMainLoop(IOperator start) {
IOperator mainLoop = start;
while (mainLoop != null && !(mainLoop is ScatterSearchMainLoop))
mainLoop = ((SingleSuccessorOperator)mainLoop).Successor;
return mainLoop as ScatterSearchMainLoop;
}
#endregion
}
}