Constrainted death penalty meta-problem. More...

#include <death_penalty.h>

Inheritance diagram for pagmo::problem::death_penalty:

Public Types
enum	method_type { SIMPLE = 0, KURI = 1, WEIGHTED = 2 }
	Mechanism used to assign the penalty. More...

Public Types inherited from pagmo::problem::base
typedef decision_vector::size_type	size_type
	Problem's size type: the same as pagmo::decision_vector's size type.

typedef fitness_vector::size_type	f_size_type
	Fitness' size type: the same as pagmo::fitness_vector's size type.

typedef constraint_vector::size_type	c_size_type
	Constraints' size type: the same as pagmo::constraint_vector's size type.

Public Member Functions
	death_penalty (const base &=cec2006(4), const method_type=SIMPLE, const std::vector< double > &=std::vector< double >())
	Constructor from a constrained problem. More...

base_ptr	clone () const
	Clone method.

std::string	get_name () const
	Get problem's name. More...

Public Member Functions inherited from pagmo::problem::base_meta
	base_meta (const base &p=ackley(1), int n=1, int ni=0, int nf=1, int nc=0, int nic=0, const std::vector< double > &c_tol=std::vector< double >())
	Constructor.

	base_meta (const base_meta &p)
	Copy constructor.

Public Member Functions inherited from pagmo::problem::base
	base (int, int=0, int=1, int=0, int=0, const double &=0)
	Constructor from global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

	base (int, int, int, int, int, const std::vector< double > &)
	Constructor from global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

	base (const double &, const double &, int, int=0, int=1, int=0, int=0, const double &=0)
	Constructor from values for lower and upper bounds, global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

	base (const decision_vector &, const decision_vector &, int=0, int=1, int=0, int=0, const double &=0)
	Constructor from upper/lower bounds, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

template<std::size_t N>
	base (const double(&v1)[N], const double(&v2)[N], int ni=0, int nf=1, int nc=0, int nic=0, const double &c_tol=0)
	Constructor from raw arrays, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

template<class Iterator1 , class Iterator2 >
	base (Iterator1 start1, Iterator1 end1, Iterator2 start2, Iterator2 end2, int ni=0, int nf=1, int nc=0, int nic=0, const double &c_tol=0)
	Constructor from iterators, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

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

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

bool	operator== (const base &) const
	Equality operator. More...

bool	operator!= (const base &) const
	Inequality operator. More...

bool	is_compatible (const base &) const
	Compatibility operator. More...

bool	compare_x (const decision_vector &, const decision_vector &) const
	Compare decision vectors. More...

bool	verify_x (const decision_vector &) const
	Verify compatibility of decision vector x with problem. More...

bool	compare_fc (const fitness_vector &, const constraint_vector &, const fitness_vector &, const constraint_vector &) const
	Simultaneous fitness-constraint comparison. More...

virtual void	pre_evolution (population &) const
	Pre-evolution hook. More...

virtual void	post_evolution (population &) const
	Post-evolution hook. More...

virtual void	set_sparsity (int &lenG, std::vector< int > &iGfun, std::vector< int > &jGvar) const
	Sets the sparsity pattern of the gradient. More...

const decision_vector &	get_lb () const
	Lower bounds getter. More...

const decision_vector &	get_ub () const
	Upper bounds getter. More...

void	set_bounds (const decision_vector &, const decision_vector &)
	Bounds setter from pagmo::decision_vector. More...

template<class Iterator1 , class Iterator2 >
void	set_bounds (Iterator1 start1, Iterator1 end1, Iterator2 start2, Iterator2 end2)
	Bounds setter from iterators. More...

template<std::size_t N>
void	set_bounds (const double(&v1)[N], const double(&v2)[N])
	Bounds setter from raw arrays. More...

void	set_bounds (const double &, const double &)
	Set bounds to specified values. More...

void	set_bounds (int, const double &, const double &)
	Set bounds to specified values. More...

void	set_lb (const decision_vector &)
	Set lower bounds from pagmo::decision_vector. More...

void	set_lb (int, const double &)
	Set specific lower bound to value. More...

void	set_lb (const double &)
	Set all lower bounds to value. More...

template<class Iterator >
void	set_lb (Iterator start, Iterator end)
	Lower bounds setter from iterators. More...

template<std::size_t N>
void	set_lb (const double(&v)[N])
	Lower bounds setter from raw array. More...

void	set_ub (const decision_vector &)
	Set upper bounds from pagmo::decision_vector. More...

void	set_ub (int, const double &)
	Set specific upper bound to value. More...

void	set_ub (const double &)
	Set all upper bounds to value. More...

template<class Iterator >
void	set_ub (Iterator start, Iterator end)
	Upper bounds setter from iterators. More...

template<std::size_t N>
void	set_ub (const double(&v)[N])
	Upper bounds setter from raw array. More...

unsigned int	get_fevals () const
	Return number of function evaluations. More...

unsigned int	get_cevals () const
	Return number of constraints function evaluations. More...

size_type	get_dimension () const
	Return global dimension. More...

size_type	get_i_dimension () const
	Return integer dimension. More...

f_size_type	get_f_dimension () const
	Return fitness dimension. More...

c_size_type	get_c_dimension () const
	Return global constraints dimension. More...

c_size_type	get_ic_dimension () const
	Return inequality constraints dimension. More...

const std::vector< double > &	get_c_tol () const
	Return constraints tolerance. More...

double	get_diameter () const
	Get the diameter of the problem. More...

constraint_vector	compute_constraints (const decision_vector &) const
	Compute constraints and return constraint vector. More...

void	compute_constraints (constraint_vector &, const decision_vector &) const
	Compute constraints and write them into contraint vector. More...

bool	compare_constraints (const constraint_vector &, const constraint_vector &) const
	Compare constraint vectors. More...

bool	test_constraint (const constraint_vector &, const c_size_type &) const
	Test i-th constraint of c (using tolerance information). More...

bool	feasibility_x (const decision_vector &) const
	Test feasibility of decision vector. More...

bool	feasibility_c (const constraint_vector &) const
	Test feasibility of constraint vector. More...

fitness_vector	objfun (const decision_vector &) const
	Return fitness of pagmo::decision_vector. More...

void	objfun (fitness_vector &, const decision_vector &) const
	Write fitness of pagmo::decision_vector into pagmo::fitness_vector. More...

bool	compare_fitness (const fitness_vector &, const fitness_vector &) const
	Compare fitness vectors. More...

void	reset_caches () const
	Reset internal caches. More...

const std::vector< constraint_vector > &	get_best_c (void) const
	Get the best known constraint vector. More...

const std::vector< decision_vector > &	get_best_x (void) const
	Get the best known decision vector. More...

const std::vector< fitness_vector > &	get_best_f (void) const
	Get the best known fitness vector. More...

void	set_best_x (const std::vector< decision_vector > &)
	Sets the best known decision vectors. More...

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

void	objfun_impl (fitness_vector &, const decision_vector &) const

Protected Member Functions inherited from pagmo::problem::base_meta
bool	compare_fitness_impl (const fitness_vector &f1, const fitness_vector &f2) const
	Implementation of fitness vectors comparison. More...

bool	compare_constraints_impl (const constraint_vector &c1, const constraint_vector &c2) const
	Implementation of constraint vector comparison. More...

bool	compare_fc_impl (const fitness_vector &f1, const constraint_vector &c1, const fitness_vector &f2, const constraint_vector &c2) const
	Implementation of simultaneous fitness-constraint comparison. More...

Protected Member Functions inherited from pagmo::problem::base
virtual bool	equality_operator_extra (const base &) const
	Extra requirements for equality. More...

void	estimate_sparsity (const decision_vector &, int &lenG, std::vector< int > &iGfun, std::vector< int > &jGvar) const
	Heuristics to estimate the sparsity pattern of the problem. More...

void	estimate_sparsity (int &lenG, std::vector< int > &iGfun, std::vector< int > &jGvar) const
	Heuristics to estimate the sparsity pattern of the problem. More...

virtual void	compute_constraints_impl (constraint_vector &, const decision_vector &) const
	Implementation of constraint computation. More...

Friends
class	boost::serialization::access

Additional Inherited Members
Static Public Attributes inherited from pagmo::problem::base
static const std::size_t	cache_capacity = 5
	Capacity of the internal caches.

Protected Attributes inherited from pagmo::problem::base_meta
base_ptr	m_original_problem
	Smart pointer to the original problem instance.

Detailed Description

Constrainted death penalty meta-problem.

Implements a meta-problem class that wraps some other constrained problems, resulting in death penalty constraints handling.

Two implementations of the death penalty are availlable. The first one is the most common simple death penalty. The second one is the death penalty defined by Angel Kuri Morales et al. Simple death penalty penalizes the fitness function with a high value, Kuri method penalizes the fitness function according to the rate of satisfied constraints.

Note: This constraints handling technique can only be used for MINIMIZATION problems.

See also: Coello Coello, C. A. (2002). Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Computer methods in applied mechanics and engineering, 191(11), 1245-1287.; Kuri Morales, A. and Quezada, C.C. A Universal eclectic genetic algorithm for constrained optimization, Proceedings 6th European Congress on Intelligent Techniques & Soft Computing, EUFIT'98, 518-522, 1998.

Author: Jeremie Labroquere (jerem.nosp@m.ie.l.nosp@m.abroq.nosp@m.uere.nosp@m.@gmai.nosp@m.l.co.nosp@m.m)

Definition at line 54 of file death_penalty.h.

Member Enumeration Documentation

enum pagmo::problem::death_penalty::method_type

Mechanism used to assign the penalty.

Enumerator
SIMPLE	Penalizes the fitness function with a high value id the decision vector is unfeasible.
KURI	Penalizes the fitness function according to the number of satisfied constraints.
WEIGHTED	Penalizes the fitness function with the weighted sum of the violations.

Definition at line 58 of file death_penalty.h.

Constructor & Destructor Documentation

pagmo::problem::death_penalty::death_penalty	(	const base &	problem = `cec2006(4)`,
		const method_type	method = `SIMPLE`,
		const std::vector< double > &	penalty_factors = `std::vector<double>()`
	)

Constructor from a constrained problem.

Will construct, using the selected method, the passed problem

Parameters

[in]	problem	base::problem to be modified to use a death penalty as constraints handling technique.
[in]	method	death_penalty::method_type
[in]	penalty_factors	std::vector containing

Definition at line 45 of file death_penalty.cpp.

Member Function Documentation

std::string pagmo::problem::death_penalty::get_name ( ) const

virtual

Get problem's name.

Default implementation will return the problem's mangled C++ name.

Returns: name of the problem.

Reimplemented from pagmo::problem::base.

Definition at line 183 of file death_penalty.cpp.

std::string pagmo::problem::death_penalty::human_readable_extra ( ) const

protectedvirtual

Extra human readable info for the problem.

Will return a formatted string containing the type of constraint handling

Reimplemented from pagmo::problem::base.

Definition at line 160 of file death_penalty.cpp.

void pagmo::problem::death_penalty::objfun_impl	(	fitness_vector &	f,
		const decision_vector &	x
	)		const

protectedvirtual

Implementation of the objective function. (Wraps over the original implementation)

Implements pagmo::problem::base.

Definition at line 83 of file death_penalty.cpp.

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

Public Types

Public Member Functions

Protected Member Functions

Friends

Additional Inherited Members

Detailed Description

Member Enumeration Documentation

Constructor & Destructor Documentation

Member Function Documentation