Golomb ruler problem. More...

#include <golomb_ruler.h>

Inheritance diagram for pagmo::problem::golomb_ruler:

Public Member Functions
	golomb_ruler (int=5, int=10)
	Constructor from order and maximum distance between consecutive marks. 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
	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...

virtual std::string	human_readable_extra () const
	Extra information in human readable format. 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
void	objfun_impl (fitness_vector &, const decision_vector &) const
	Implementation of the objective function. More...

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

bool	equality_operator_extra (const base &) const
	Additional requirements for equality. More...

Protected Member Functions inherited from pagmo::problem::base
virtual bool	compare_fc_impl (const fitness_vector &, const constraint_vector &, const fitness_vector &, const constraint_vector &) const
	Implementation of simultaneous fitness-constraint comparison. 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 bool	compare_constraints_impl (const constraint_vector &, const constraint_vector &) const
	Implementation of constraint vector comparison. More...

virtual bool	compare_fitness_impl (const fitness_vector &, const fitness_vector &) const
	Implementation of fitness vectors comparison. More...

Friends
class	boost::serialization::access

Additional Inherited Members
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.

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

Detailed Description

Golomb ruler problem.

Optimal and perfect Golomb ruler of order 4.

A Golomb ruler is a set of marks at integer positions along an imaginary ruler such that no two pairs of marks are the same distance apart. The number of marks on the ruler is its order, and the largest distance between two of its marks is its length. A Golomb ruler is optimal if no shorter Golomb ruler of the same order exists.

This problem is setup to look for optimal Golomb rulers of a given order. The problem has dimension (order - 1), with the decision vector representing distances between successive marks. The objective is to minimise the length of the ruler, with the equality constraint that for each possible pair of marks the distance must be unique (i.e., the number of duplicate distances must be null in order to satisfy the constraint). Note that when this constraint is not satisfied, the ruler is not a Golomb ruler.

See also: http://en.wikipedia.org/wiki/Golomb_ruler

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

Definition at line 56 of file golomb_ruler.h.

Constructor & Destructor Documentation

pagmo::problem::golomb_ruler::golomb_ruler	(	int	n = `5`,
		int	m = `10`
	)

Constructor from order and maximum distance between consecutive marks.

Construct a Golomb ruler problem of order n and whose maximum distance between consecutive marks is m.

Parameters

[in]	n	order of the Golomb ruler.
[in]	m	upper limit for the distance between consecutive marks.

Definition at line 57 of file golomb_ruler.cpp.

Member Function Documentation

void pagmo::problem::golomb_ruler::compute_constraints_impl	(	constraint_vector &	c,
		const decision_vector &	x
	)		const

protectedvirtual

Implementation of constraint calculation.

Implements an equality constraint on the number of equal distances between the marks pairs. If this number is 0, the constraint is satisfied and the ruler is a Golomb ruler.

Parameters

[out]	c	pagmo::constraint_vector that stores the output constraint.
[in]	x	pagmo::decision_vector whose feasibility will be calculated.

Reimplemented from pagmo::problem::base.

Definition at line 111 of file golomb_ruler.cpp.

bool pagmo::problem::golomb_ruler::equality_operator_extra ( const base & other ) const

protectedvirtual

Additional requirements for equality.

Returns: true if upper limits for length are equal, false otherwise.

Reimplemented from pagmo::problem::base.

Definition at line 82 of file golomb_ruler.cpp.

std::string pagmo::problem::golomb_ruler::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 147 of file golomb_ruler.cpp.

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

protectedvirtual

Implementation of the objective function.

Will return the distance of the ruler.

Parameters

[out]	f	pagmo::fitness_vector that stores the output fitness.
[in]	x	pagmo::decision_vector whose fitness will be calculated.

Implements pagmo::problem::base.

Definition at line 95 of file golomb_ruler.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