Wrapper for NLopt's BOBYQA algorithm. More...

Inheritance diagram for pagmo::algorithm::nlopt_bobyqa:

Public Member Functions
	nlopt_bobyqa (int=100, const double &=1E-6, const double &=1E-6)
	Constructor. More...

base_ptr	clone () const
	Clone method. More...

std::string	get_name () const
	Algorithm name.

Public Member Functions inherited from pagmo::algorithm::base
	base ()
	Default constructor. More...

virtual	~base ()
	Trivial destructor. More...

std::string	human_readable () const
	Return human readable representation of the algorithm. More...

void	set_screen_output (const bool p)
	Setter-Getter for protected m_screen_output data. More...

bool	get_screen_output () const
	Gets screen output. More...

void	reset_rngs (const unsigned int) const
	Resets the seed of the internal rngs using a user-provided seed. More...

Additional Inherited Members
Protected Member Functions inherited from pagmo::algorithm::base_nlopt
	base_nlopt (nlopt::algorithm, bool, bool, int, const double &, const double &)
	Constructor. More...

void	evolve (population &) const
	Evolve method. More...

std::string	human_readable_extra () const
	Extra information in human readable format. More...

Protected Attributes inherited from pagmo::algorithm::base_nlopt
nlopt::opt	m_opt
	NLOPT optimization method.

const std::size_t	m_max_iter
	Maximum number of iterations.

const double	m_ftol
	Tolerance on the fitness function variation (stopping criteria)

const double	m_xtol
	Tolerance on the decision_vector variation function (stopping criteria)

Protected Attributes inherited from pagmo::algorithm::base
bool	m_screen_output
	Indicates to the derived class whether to print stuff on screen.

rng_double	m_drng
	Random number generator for double-precision floating point values.

rng_uint32	m_urng
	Random number generator for unsigned integer values.

unsigned int	m_fevals
	A counter for the number of function evaluations.

Detailed Description

Wrapper for NLopt's BOBYQA algorithm.

BOBYQA (Bound Optimization BY Quadratic Approximation) is a derivative-free single-objective continuous minimiser that supports box constraints.

See also: M. J. D. Powell, "The BOBYQA algorithm for bound constrained optimization without derivatives," Department of Applied Mathematics and Theoretical Physics, Cambridge England, technical report NA2009/06 (2009).

Author: Francesco Biscani (blues.nosp@m.carn.nosp@m.i@gma.nosp@m.il.c.nosp@m.om)

Definition at line 42 of file nlopt_bobyqa.h.

Constructor & Destructor Documentation

pagmo::algorithm::nlopt_bobyqa::nlopt_bobyqa	(	int	max_iter = `100`,
		const double &	ftol = `1E-6`,
		const double &	xtol = `1E-6`
	)

Constructor.

Definition at line 36 of file nlopt_bobyqa.cpp.

base_ptr pagmo::algorithm::nlopt_bobyqa::clone ( ) const

virtual

Clone method.

Provided that the derived algorithm implements properly the copy constructor, virtually all implementations of this method will look like this:

return base_ptr(new derived_algorithm(*this));

               @return algorithm::base_ptr to a copy of this.

Definition at line 38 of file nlopt_bobyqa.cpp.

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