The City-Selection Travelling Salesman Problem. More...

#include <tsp_cs.h>

Inheritance diagram for pagmo::problem::tsp_cs:

Public Member Functions
	tsp_cs ()
	Constructors. More...

	tsp_cs (const std::vector< std::vector< double > > &, const std::vector< double > &, const double, const base_tsp::encoding_type &=CITIES)
	Constructor. More...

base_ptr	clone () const
	Copy constructor for polymorphic objects. More...

void	find_subsequence (const decision_vector &, double &, double &, decision_vector::size_type &, decision_vector::size_type &) const
	Computes the best subpath of an hamilonian path satisfying the max_path_length constraint. More...

Getters
const std::vector< std::vector< double > > &	get_weights () const
	Getter for m_weights. More...

const std::vector< double > &	get_values () const
	Getter for m_values. More...

double	get_max_path_length () const
	Getter for m_max_path_value. More...

Implementation of virtual methods
std::string	get_name () const
	Returns the problem name.

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

double	distance (decision_vector::size_type, decision_vector::size_type) const
	Definition of distance function.

Public Member Functions inherited from pagmo::problem::base_tsp
	base_tsp (int n_cities, int nc, int nic, encoding_type=CITIES)
	Constructor from dimensins and encoding. More...

encoding_type	get_encoding () const
	Getter for m_encoding. More...

decision_vector::size_type	get_n_cities () const
	Getter for m_n_cities. More...

pagmo::decision_vector	full2cities (const pagmo::decision_vector &) const
	From FULL to CITIES encoding. More...

pagmo::decision_vector	cities2full (const pagmo::decision_vector &) const
	From CITIES to FULL encoding. More...

pagmo::decision_vector	randomkeys2cities (const pagmo::decision_vector &) const
	From RANDOMKEYS to CITIES encoding. More...

pagmo::decision_vector	cities2randomkeys (const pagmo::decision_vector &, const pagmo::decision_vector &) const
	From CITIES to RANDOMKEYS encoding. 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...

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...

Friends
class	boost::serialization::access

Additional Inherited Members
Public Types inherited from pagmo::problem::base_tsp
enum	encoding_type { RANDOMKEYS = 0, FULL = 1, CITIES = 2 }
	Mechanism used to encode the sequence of vertices to be visited. 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.

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

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

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...

Detailed Description

The City-Selection Travelling Salesman Problem.

This is a class representing a new variant of the TSP which was firstly introduced (by us) in the context of asteroid/space debris selection problems.

Given a fully connected graph (V,E), where E is a list of weighted edges and V a list of valued vertices, the problem is that of finding a path of length $ l<l^* $ accumulating the largest possible vertex value. We encode a solution to this problem as an Hamiltonian path and evaluate its merit finding, along it, the best sequence satisfying the constraint. Denoting its cumulated vertex value with $ P $ we also compute, the length of the whole Hamiltonian path, $ L $ .

The problem will then be that of finding the Hamiltonian path maximizing $ P $ and having the largest $ L $ .

NOTE: if $ l^* $ is larger than than the shortest Hamiltonian path (i.e. the solution to the static TSP), the solution to this problem is the solution to the static TSP. If $ l^* $ is, instead, smaller than the minimum weight across edges, the solution to this problem is trivial and its global minimum is exactly $\max V$ (corrsponding to $P=\max V$ .

Author: Dario Izzo (dario.nosp@m..izz.nosp@m.o@gma.nosp@m.il.c.nosp@m.om)

Definition at line 57 of file tsp_cs.h.

Constructor & Destructor Documentation

pagmo::problem::tsp_cs::tsp_cs ( )

Constructors.

Default constructor.

This constructs a 3-cities symmetric problem (naive TSP_CS) with weight matrix [[0,1,1], [1,0,1], [1,1,0]], value vector [1,1,1] maximum path length of 1 and RANDOMKEYS encoding

Definition at line 36 of file tsp_cs.cpp.

pagmo::problem::tsp_cs::tsp_cs	(	const std::vector< std::vector< double > > &	weights,
		const std::vector< double > &	values,
		const double	max_path_length,
		const base_tsp::encoding_type &	encoding = `CITIES`
	)

Constructor.

Constructs a City-Selction TSP from the weights/values definition, a maximum path length and the chosen encoding

Parameters

[in]	weights	an std::vector of std::vector representing the edges weights
[in]	values	an std::vector representing the vertices values
[in]	max_path_length	the maximum path length allowed (for the travelling salesman)
[in]	encoding	a pagmo::problem::tsp::encoding representing the chosen encoding

Definition at line 61 of file tsp_cs.cpp.

Member Function Documentation

base_ptr pagmo::problem::tsp_cs::clone ( ) const

virtual

Copy constructor for polymorphic objects.

Clone method.

Implements pagmo::problem::base.

Definition at line 85 of file tsp_cs.cpp.

void pagmo::problem::tsp_cs::find_subsequence	(	const decision_vector &	tour,
		double &	retval_p,
		double &	retval_l,
		decision_vector::size_type &	retval_it_l,
		decision_vector::size_type &	retval_it_r
	)		const

Computes the best subpath of an hamilonian path satisfying the max_path_length constraint.

Computes the best subpath of an hamilonian path satisfying the max_path_length constraint. If the input tour does not represent an Hamiltonian path, (i.e. its an unfeasible chromosome) the algorithm behaviour is undefined

Parameters

[in]	tour	the hamiltonian path encoded with a CITIES encoding (i.e. the list of cities ids)
[out]	retval_p	the total cumulative value of the subpath
[out]	retval_l	the total saved cumulative length of the subpath
[out]	retval_it_l	the id of the city where the subpath starts
[out]	retval_it_r	the id of the city where the subpath ends

Exceptions

value_error if the input tour length is not equal to the city number

Definition at line 199 of file tsp_cs.cpp.

double pagmo::problem::tsp_cs::get_max_path_length ( ) const

Getter for m_max_path_value.

Returns: m_max_path_value

Definition at line 390 of file tsp_cs.cpp.

const std::vector< double > & pagmo::problem::tsp_cs::get_values ( ) const

Getter for m_values.

Returns: const reference to m_values

Definition at line 381 of file tsp_cs.cpp.

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

Getter for m_weights.

Returns: const reference to m_weights

Definition at line 372 of file tsp_cs.cpp.

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

virtual

Extra human readable info for the problem.

Returns: a std::string containing a list of vertices and edges

Reimplemented from pagmo::problem::base.

Definition at line 405 of file tsp_cs.cpp.

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

Public Member Functions

Friends

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation