Implements the MOEA/D algorithm. More...

#include <shark/Algorithms/DirectSearch/MOEAD.h>

Inheritance diagram for shark::MOEAD:

Public Member Functions
SHARK_EXPORT_SYMBOL	MOEAD (random::rng_type &rng=random::globalRng)

std::string	name () const
	returns the name of the object

double	crossoverProbability () const

double &	crossoverProbability ()

double	nm () const

double &	nm ()

double	nc () const

double &	nc ()

std::size_t	mu () const

std::size_t &	mu ()

std::size_t	numInitPoints () const
	The number of points used for initialization of the algorithm.

std::size_t	neighbourhoodSize () const

std::size_t &	neighbourhoodSize ()

template<typename Archive >
void	serialize (Archive &archive)

SHARK_EXPORT_SYMBOL void	init (ObjectiveFunctionType const &function, std::vector< SearchPointType > const &initialSearchPoints)

SHARK_EXPORT_SYMBOL void	step (ObjectiveFunctionType const &function)

Public Member Functions inherited from shark::AbstractMultiObjectiveOptimizer< RealVector >
SolutionType const &	solution () const
	Accesses the current approximation of the Pareto-set and -front, respectively.

Public Member Functions inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
const Features &	features () const

virtual void	updateFeatures ()

bool	requiresValue () const

bool	requiresFirstDerivative () const

bool	requiresSecondDerivative () const

bool	canSolveConstrained () const

bool	requiresClosestFeasible () const

virtual	~AbstractOptimizer ()

virtual void	init (ObjectiveFunctionType const &function)
	Initialize the optimizer for the supplied objective function.

virtual void	init (ObjectiveFunctionType const &function, std::vector< SearchPointType > const &initPoints)=0
	Initialize the optimizer for the supplied objective function using a set of initialisation points.

virtual void	step (ObjectiveFunctionType const &function)=0
	Carry out one step of the optimizer for the supplied objective function.

Public Member Functions inherited from shark::INameable
virtual	~INameable ()

Public Member Functions inherited from shark::ISerializable
virtual	~ISerializable ()
	Virtual d'tor.

virtual void	read (InArchive &archive)
	Read the component from the supplied archive.

virtual void	write (OutArchive &archive) const
	Write the component to the supplied archive.

void	load (InArchive &archive, unsigned int version)
	Versioned loading of components, calls read(...).

void	save (OutArchive &archive, unsigned int version) const
	Versioned storing of components, calls write(...).

	BOOST_SERIALIZATION_SPLIT_MEMBER ()

Protected Types
typedef shark::Individual< RealVector, RealVector >	IndividualType

Protected Member Functions
SHARK_EXPORT_SYMBOL void	doInit (std::vector< SearchPointType > const &initialSearchPoints, std::vector< ResultType > const &functionValues, RealVector const &lowerBounds, RealVector const &upperBounds, std::size_t const mu, double const nm, double const nc, double const crossover_prob, std::size_t const neighbourhoodSize, std::vector< Preference > const &weightVectorPreferences=std::vector< Preference >())

SHARK_EXPORT_SYMBOL std::vector< IndividualType >	generateOffspring () const

SHARK_EXPORT_SYMBOL void	updatePopulation (std::vector< IndividualType > const &offspringvec)

Protected Member Functions inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
void	checkFeatures (ObjectiveFunctionType const &objectiveFunction)
	Convenience function that checks whether the features of the supplied objective function match with the required features of the optimizer.

Protected Attributes
std::vector< IndividualType >	m_parents

Protected Attributes inherited from shark::AbstractMultiObjectiveOptimizer< RealVector >
SolutionType	m_best
	The current Pareto-set/-front.

Protected Attributes inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
Features	m_features

Additional Inherited Members
Public Types inherited from shark::AbstractMultiObjectiveOptimizer< RealVector >
typedef super::SearchPointType	SearchPointType

typedef super::SolutionType	SolutionType

typedef super::ObjectiveFunctionType	ObjectiveFunctionType

Public Types inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
enum	Feature { REQUIRES_VALUE = 1 , REQUIRES_FIRST_DERIVATIVE = 2 , REQUIRES_SECOND_DERIVATIVE = 4 , CAN_SOLVE_CONSTRAINED = 8 , REQUIRES_CLOSEST_FEASIBLE = 16 }
	Models features that the optimizer requires from the objective function. More...

typedef PointType	SearchPointType

typedef ResultT	ResultType

typedef SolutionTypeT	SolutionType

typedef AbstractObjectiveFunction< PointType, ResultType >	ObjectiveFunctionType

typedef TypedFlags< Feature >	Features

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Detailed Description

Implements the MOEA/D algorithm.

Implementation of the MOEA/D algorithm from the following paper: Q. Zhang and H. Li, MOEA/D: a multi-objective evolutionary algorithm based on decomposition, IEEE Transactions on Evolutionary Computation, vol. 11, no. 6, pp. 712 - 731, 2007 DOI: 10.1109/TEVC.2007.892759

Definition at line 52 of file MOEAD.h.

Member Typedef Documentation

◆ IndividualType

typedef shark::Individual<RealVector, RealVector> shark::MOEAD::IndividualType

protected

Definition at line 129 of file MOEAD.h.

Constructor & Destructor Documentation

◆ MOEAD()

SHARK_EXPORT_SYMBOL shark::MOEAD::MOEAD ( random::rng_type & rng = random::globalRng )

Member Function Documentation

◆ crossoverProbability() [1/2]

double & shark::MOEAD::crossoverProbability ( )

inline

Definition at line 65 of file MOEAD.h.

◆ crossoverProbability() [2/2]

double shark::MOEAD::crossoverProbability ( ) const

inline

Definition at line 61 of file MOEAD.h.

◆ doInit()

SHARK_EXPORT_SYMBOL void shark::MOEAD::doInit	(	std::vector< SearchPointType > const &	initialSearchPoints,
		std::vector< ResultType > const &	functionValues,
		RealVector const &	lowerBounds,
		RealVector const &	upperBounds,
		std::size_t const	mu,
		double const	nm,
		double const	nc,
		double const	crossover_prob,
		std::size_t const	neighbourhoodSize,
		std::vector< Preference > const &	weightVectorPreferences = `std::vector< Preference >()`
	)

protected

◆ generateOffspring()

SHARK_EXPORT_SYMBOL std::vector< IndividualType > shark::MOEAD::generateOffspring ( ) const

protected

◆ init()

SHARK_EXPORT_SYMBOL void shark::MOEAD::init	(	ObjectiveFunctionType const &	function,
		std::vector< SearchPointType > const &	initialSearchPoints
	)

◆ mu() [1/2]

std::size_t & shark::MOEAD::mu ( )

inline

Definition at line 89 of file MOEAD.h.

◆ mu() [2/2]

std::size_t shark::MOEAD::mu ( ) const

inline

Definition at line 85 of file MOEAD.h.

◆ name()

std::string shark::MOEAD::name ( ) const

inlinevirtual

returns the name of the object

Reimplemented from shark::INameable.

Definition at line 57 of file MOEAD.h.

◆ nc() [1/2]

double & shark::MOEAD::nc ( )

inline

Definition at line 81 of file MOEAD.h.

References shark::SimulatedBinaryCrossover< PointType >::m_nc.

◆ nc() [2/2]

double shark::MOEAD::nc ( ) const

inline

Definition at line 77 of file MOEAD.h.

References shark::SimulatedBinaryCrossover< PointType >::m_nc.

◆ neighbourhoodSize() [1/2]

std::size_t & shark::MOEAD::neighbourhoodSize ( )

inline

Definition at line 102 of file MOEAD.h.

◆ neighbourhoodSize() [2/2]

std::size_t shark::MOEAD::neighbourhoodSize ( ) const

inline

Definition at line 98 of file MOEAD.h.

◆ nm() [1/2]

double & shark::MOEAD::nm ( )

inline

Definition at line 73 of file MOEAD.h.

References shark::PolynomialMutator::m_nm.

◆ nm() [2/2]

double shark::MOEAD::nm ( ) const

inline

Definition at line 69 of file MOEAD.h.

References shark::PolynomialMutator::m_nm.

◆ numInitPoints()

std::size_t shark::MOEAD::numInitPoints ( ) const

inlinevirtual

The number of points used for initialization of the algorithm.

Implements shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >.

Definition at line 94 of file MOEAD.h.

◆ serialize()

template<typename Archive >

void shark::MOEAD::serialize ( Archive & archive )

inline

Definition at line 107 of file MOEAD.h.

References shark::AbstractMultiObjectiveOptimizer< RealVector >::m_best, and m_parents.

◆ step()

SHARK_EXPORT_SYMBOL void shark::MOEAD::step ( ObjectiveFunctionType const & function )

◆ updatePopulation()

SHARK_EXPORT_SYMBOL void shark::MOEAD::updatePopulation ( std::vector< IndividualType > const & offspringvec )

protected

Member Data Documentation

◆ m_parents

std::vector<IndividualType> shark::MOEAD::m_parents

protected

Definition at line 146 of file MOEAD.h.

Referenced by serialize().

The documentation for this class was generated from the following file:

include/shark/Algorithms/DirectSearch/MOEAD.h

Public Member Functions

Protected Types

Protected Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ IndividualType

Constructor & Destructor Documentation

◆ MOEAD()

Member Function Documentation

◆ crossoverProbability() [1/2]

◆ crossoverProbability() [2/2]

◆ doInit()

◆ generateOffspring()

◆ init()

◆ mu() [1/2]

◆ mu() [2/2]

◆ name()

◆ nc() [1/2]

◆ nc() [2/2]

◆ neighbourhoodSize() [1/2]

◆ neighbourhoodSize() [2/2]

◆ nm() [1/2]

◆ nm() [2/2]

◆ numInitPoints()

◆ serialize()

◆ step()

◆ updatePopulation()

Member Data Documentation

◆ m_parents