pagmo::algorithm::nsga2 Class Reference

Nondominated Sorting genetic algorithm II (NSGA-II) More...

#include <nsga2.h>

Inheritance diagram for pagmo::algorithm::nsga2:

Public Member Functions
	nsga2 (int gen=100, double cr=0.95, double eta_c=10, double m=0.01, double eta_m=50)
	Constructor. More...
base_ptr	clone () const
	Clone method.
void	evolve (population &) const
	Evolve implementation. 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...

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

Nondominated Sorting genetic algorithm II (NSGA-II)

NSGA-II is a nondominated-sorting based multiobjective evolutionary algorithm. It genererates offspring with crossover and mutation and select the next generation according to nondominated-sorting and crowding distance comparison.

The algorithm can be applied to continuous box-bounded optimization. The version for mixed integer and constrained optimization is also planned.

See also

Deb, K. and Pratap, A. and Agarwal, S. and Meyarivan, T., "A fast and elitist multiobjective genetic algorithm: NSGA-II"

Author

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

Definition at line 49 of file nsga2.h.

Constructor & Destructor Documentation

pagmo::algorithm::nsga2::nsga2	(	int	gen = 100,
		double	cr = 0.95,
		double	eta_c = 10,
		double	m = 0.01,
		double	eta_m = 50
	)

Constructor.

Constructs a NSGA II algorithm

Parameters

[in]	gen	Number of generations to evolve.
[in]	cr	Crossover probability
[in]	eta_c	Distribution index for crossover
[in]	m	Mutation probability
[in]	eta_m	Distribution index for mutation

Exceptions

value_error

if gen is negative, crossover probability is not , mutation probability or mutation width is not ,

Definition at line 56 of file nsga2.cpp.

Member Function Documentation

void pagmo::algorithm::nsga2::evolve ( population &  pop ) const

virtual

Evolve implementation.

Run the NSGA-II algorithm for the number of generations specified in the constructors.

Parameters

[in,out]

pop

input/output pagmo::population to be evolved.

Implements pagmo::algorithm::base.

Definition at line 245 of file nsga2.cpp.

std::string pagmo::algorithm::nsga2::human_readable_extra ( ) const

protectedvirtual

Extra human readable algorithm info.

Will return a formatted string displaying the parameters of the algorithm.

Reimplemented from pagmo::algorithm::base.

Definition at line 335 of file nsga2.cpp.

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

• nsga2.h
• nsga2.cpp