Monotonic Basin Hopping (generalized) More...

#include <mbh.h>

Inheritance diagram for pagmo::algorithm::mbh:

Public Member Functions
	mbh (const base &=cs(), int stop=5, double perturb=5e-2)
	Constructor. More...

	mbh (const base &, int stop, const std::vector< double > &perturb)
	Constructor. More...

	mbh (const mbh &)
	Copy constructor.

base_ptr	clone () const
	Clone method.

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

std::string	get_name () const
	Algorithm name.

base_ptr	get_algorithm () const
	Get a copy of the internal local algorithm. More...

void	set_algorithm (const base &)
	Set algorithm. More...

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...

Protected Member Functions
std::string	human_readable_extra () const
	Extra human readable algorithm info. More...

Friends
class	boost::serialization::access

Additional Inherited Members
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

Monotonic Basin Hopping (generalized)

A schematic diagram illustrating the effects of the basin hopping transformation on a one dimensional landscape.

Monotonic basin hopping, or simply, basin hopping, is an algorithm rooted in the idea of transforming each the objective function at $\mathbf x$ into the local minima found starting from $\mathbf x$ This simple idea allowed a substantial increase of efficiency in solving problems, such as the Lennard-Jones cluster or the MGA-DSM interplanetary trajectory problem that are conjectured to have a so-called funnel structure.

In PaGMO we provide an original generalization of the method that operates on any pagmo::population using any pagmo::algorithm. When a population containing a single individual is used and coupled with a local optimizer, the original method is recovered. The pseudo code of the generalized version is:

> Select a pagmo::population
> Select a pagmo::algorithm
> Store best individual
> while i < stop_criteria
> > Perturb the population in a selected neighbourhood
> > Evolve the population using the algorithm
> > if the best individual is improved (according to the problem::compare_fc criteria)
> > > increment i
> > > update best individual
> > else
> > > i = 0

See also: http://arxiv.org/pdf/cond-mat/9803344 for the paper inroducing the basin hopping idea for a Lennard-Jones cluster optimization

Author: Dario Izzo (dario.nosp@m..izz.nosp@m.o@goo.nosp@m.glem.nosp@m.ail.c.nosp@m.om)

Definition at line 75 of file mbh.h.

Constructor & Destructor Documentation

pagmo::algorithm::mbh::mbh	(	const base &	local = `cs()`,
		int	stop = `5`,
		double	perturb = `5e-2`
	)

Constructor.

Constructs an mbh algorithm with uniform neighbourhoods

Parameters

[in]	local	pagmo::algorithm to use as 'local' optimization method
[in]	stop	number of consecutive step allowed without any improvement
[in]	perturb	At the end of one iteration of mbh, each chromosome of each individual will be perturbed within +-perturb*(ub-lb), the same for the velocity. The integer part is treated the same way. rounding to the floor

Exceptions

value_error if stop is negative or perturb is not in [0,1]

Definition at line 50 of file mbh.cpp.

pagmo::algorithm::mbh::mbh	(	const base &	local,
		int	stop,
		const std::vector< double > &	perturb
	)

Constructor.

Allows to specify in detail all the parameters of the algorithm.

Parameters

[in]	local	pagmo::algorithm to use as 'local' optimization method
[in]	stop	number of consecutive step allowed without any improvement
[in]	perturb	At the end of one iteration of mbh, the i-th chromosome of each individual will be perturbed within +-perturb[i]*(ub[i]-lb[i]), the same for the velocity. The integer part is treated the same way rounding to the floor

Exceptions

value_error if stop is negative or perturb[i] is not in [0,1]

Definition at line 72 of file mbh.cpp.

Member Function Documentation

void pagmo::algorithm::mbh::evolve ( population & pop ) const

virtual

Evolve implementation.

Run the MBH algorithm

Parameters

[in,out] pop input/output pagmo::population to be evolved.

Implements pagmo::algorithm::base.

Definition at line 104 of file mbh.cpp.

base_ptr pagmo::algorithm::mbh::get_algorithm ( ) const

Get a copy of the internal local algorithm.

Returns: algorithm::base_ptr to a copy of the internal local algorithm.

Definition at line 208 of file mbh.cpp.

std::string pagmo::algorithm::mbh::human_readable_extra ( ) const

protectedvirtual

Extra human readable algorithm info.

Returns: a formatted string displaying the parameters of the algorithm.

Reimplemented from pagmo::algorithm::base.

Definition at line 228 of file mbh.cpp.

void pagmo::algorithm::mbh::set_algorithm ( const base & algo )

Set algorithm.

A copy of the input algorithm will be set as the internal local algorithm.

Parameters

[in] algo algorithm to be set as local algorithm.

Definition at line 219 of file mbh.cpp.

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

Public Member Functions

Protected Member Functions

Friends

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation