Decompose meta-problem. More...

#include <decompose.h>

Inheritance diagram for pagmo::problem::decompose:

Public Types
enum	method_type { WEIGHTED =0, TCHEBYCHEFF =1, BI =2 }
	Mechanism used to perform the problem decomposition. 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
	decompose (const base &=zdt(1, 2), method_type=WEIGHTED, const std::vector< double > &=std::vector< double >(), const std::vector< double > &=std::vector< double >(), const bool=false)

base_ptr	clone () const
	Clone method.

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

const std::vector< double > &	get_weights () const

void	compute_decomposed_fitness (fitness_vector &, const fitness_vector &) const
	Computes the decomposed fitness. More...

void	compute_decomposed_fitness (fitness_vector &, const fitness_vector &, const fitness_vector &) const
	Computes the decomposed fitness. More...

void	compute_original_fitness (fitness_vector &, const decision_vector &) const
	Computes the original fitness. More...

fitness_vector	get_ideal_point () const
	Gets the ideal point.

void	set_ideal_point (const fitness_vector &f)
	Sets the ideal point.

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 information in human readable format. More...

void	objfun_impl (fitness_vector &, const decision_vector &) const
	Implementation of the objective function.

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

Decompose meta-problem.

Implements a meta-problem class resulting in a decomposed version of the multi-objective input problem, i.e. a single-objective problem having as fitness function some kind of combination of the original fitness functions

Being $F(X) = (F_1(X), \ldots, F_n(X))$ the original multi-objective fitness function and $w = (w_1, \ldots, w_n)$ $z = (z_1, \ldots, z_n)$ respectively a weight vector and a reference point, the decomposed problem has as single-objective fitness function one of the following according to which decomposition methods is choosed:

WEIGHTED: $F_d(X) = \sum_{i=1}^n w_i F_i(X)$

TCHEBYCHEFF $F_d(X) = max_{1 \leq i \leq m} w_i \vert F_i(X) - z_i \vert$

Author: Andrea Mambrini (andre.nosp@m.a.ma.nosp@m.mbrin.nosp@m.i@gm.nosp@m.ail.c.nosp@m.om)

See also: "Q. Zhang -- MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition"

Definition at line 62 of file decompose.h.

Member Enumeration Documentation

enum pagmo::problem::decompose::method_type

Mechanism used to perform the problem decomposition.

Enumerator
WEIGHTED	The fitness function is the weighted sum of the multiple original fitnesses.
TCHEBYCHEFF	The Tchebycheff method is used to perform the decomposition.
BI	The Boundary Intersection method is used to perform the decomposition.

Definition at line 66 of file decompose.h.

Constructor & Destructor Documentation

pagmo::problem::decompose::decompose	(	const base &	p = `zdt(1,2)`,
		method_type	method = `WEIGHTED`,
		const std::vector< double > &	weights = `std::vector<double>()`,
		const std::vector< double > &	z = `std::vector<double>()`,
		const bool	adapt_ideal = `false`
	)

Constructor

Parameters

[in]	p	base::problem to be decomposed
[in]	method	decomposition method (WEIGHTS, TCHEBYCHEFF, BI)
[in]	weights	the weight vector (by default is set to random weights)
[in]	z	ideal reference point (used in Tchebycheff and Boundary Intersection (BI) methods, by default it is set to 0)
[in]	adapt_ideal	if true it updates the ideal reference point each time the objective function is called checking if the computed fitness is better (assumes minimization)

See also: For the uniform random generation of weights vector see Appendix 2 in "A. Jaszkiewicz - On the Performance of Multiple-Objective Genetic Local Search on the 0/1 Knapsack Problem—A Comparative Experiment"; For the different decomposition methods see "Q. Zhang - MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition"

Definition at line 50 of file decompose.cpp.

Member Function Documentation

void pagmo::problem::decompose::compute_decomposed_fitness	(	fitness_vector &	f,
		const fitness_vector &	original_fit
	)		const

Computes the decomposed fitness.

Computes the decomposed fitness from the original multi-objective fitness using the data member m_weights

Parameters

f	decomposed fitness vector
original_fit	original multi-objective fitness vector

Definition at line 167 of file decompose.cpp.

void pagmo::problem::decompose::compute_decomposed_fitness	(	fitness_vector &	f,
		const fitness_vector &	original_fit,
		const fitness_vector &	weights
	)		const

Computes the decomposed fitness.

Computes the decomposed fitness from the original multi-objective one and a weight vector

Parameters

[out]	f	decomposed fitness vector
[in]	original_fit	original multi-objective fitness vector
[in]	weights	weights vector

Definition at line 180 of file decompose.cpp.

void pagmo::problem::decompose::compute_original_fitness	(	fitness_vector &	f,
		const decision_vector &	x
	)		const

Computes the original fitness.

Computes the original fitness of the multi-objective problem. It also updates the ideal point in case m_adapt_ideal is true

Parameters

[out]	f	non-decomposed fitness vector
[in]	x	chromosome

Definition at line 151 of file decompose.cpp.

std::string pagmo::problem::decompose::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 221 of file decompose.cpp.

const std::vector< double > & pagmo::problem::decompose::get_weights ( ) const

Get the weights vector

Returns: the weight vector

Definition at line 256 of file decompose.cpp.

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

protectedvirtual

Extra information in human readable format.

Default implementation returns an empty string.

Returns: std::string containing additional problem-specific human-readable representation of the problem.

Reimplemented from pagmo::problem::base.

Definition at line 226 of file decompose.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