PaGMO  1.1.5
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pagmo::problem::base_stochastic Class Reference

Base Stochastic Optimization Problem. More...

#include <base_stochastic.h>

Inheritance diagram for pagmo::problem::base_stochastic:
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Public Member Functions

 base_stochastic (int, unsigned int=0u)
 Constructor from global dimension and random seed. More...
 
 base_stochastic (int, int, int, int, int, const double &, unsigned int)
 Constructor from global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...
 
 base_stochastic (int, int, int, int, int, const std::vector< double > &, unsigned int)
 Constructor from global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance vector. More...
 
unsigned int get_seed () const
 Gets the pseudo random generator seed. More...
 
void set_seed (unsigned int) const
 Sets the pseudo random generator seed. 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...
 
virtual base_ptr clone () const =0
 Clone method. 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_vectorget_lb () const
 Lower bounds getter. More...
 
const decision_vectorget_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...
 
virtual std::string get_name () const
 Get problem's name. 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 Attributes

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_seed
 Seed of the random number generator.
 

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.
 
- 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 void compute_constraints_impl (constraint_vector &, const decision_vector &) const
 Implementation of constraint computation. 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...
 
virtual void objfun_impl (fitness_vector &f, const decision_vector &x) const =0
 Objective function implementation. More...
 

Detailed Description

Base Stochastic Optimization Problem.

A stochastic optimization problem is a problem that seeks to optimize $ J(\mathbf x) = E_s(\mathbf x,s) $, i.e. the expected value of some stochastic quantity dependant from the doecision vector.

These types of problems, in PaGMO, need to iherit from this base class and reimplement the pagmo::problem::base class virtual method objfun_impl starting with the following lines setting the rngs seed: m_drng.seed(m_seed); m_urng.seed(m_seed);

Look at pagmo::problem::inventory and pagmo::problem::spheres for a typical example.

Optimization techniques (pagmo::algorithm) that want to deal with these types of problems need to take care to change appropriately the seed during the optimization process as to avoid overfitting (that is to avoid solving the problem only for one pseudo random sequence, and not for any). This is done by a call to the change_seed() method.

See pagmo::algorithm::pso_stochastic for a good example of such techniques.

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

Definition at line 56 of file base_stochastic.h.

Constructor & Destructor Documentation

pagmo::problem::base_stochastic::base_stochastic ( int  dim,
unsigned int  seed = 0u 
)

Constructor from global dimension and random seed.

Lower and upper bounds are set to 0 and 1 respectively. The problem built is unconstrained, single objective and with no integer dimension.

Parameters
[in]dimglobal dimension of the problem.
[in]seedrandom number generator seed

Definition at line 39 of file base_stochastic.cpp.

pagmo::problem::base_stochastic::base_stochastic ( int  n,
int  ni,
int  nf,
int  nc,
int  nic,
const double &  c_tol,
unsigned int  seed 
)

Constructor from global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance.

Parameters
[in]nglobal dimension of the problem.
[in]nidimension of the combinatorial part of the problem.
[in]nfdimension of the fitness vector of the problem.
[in]ncglobal number of constraints.
[in]nicnumber of inequality constraints.
[in]c_tolconstraints tolerance (equal for all constraints)
[in]seedrandom number generator seed

Definition at line 53 of file base_stochastic.cpp.

pagmo::problem::base_stochastic::base_stochastic ( int  n,
int  ni,
int  nf,
int  nc,
int  nic,
const std::vector< double > &  c_tol,
unsigned int  seed 
)

Constructor from global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance vector.

Parameters
[in]nglobal dimension of the problem.
[in]nidimension of the combinatorial part of the problem.
[in]nfdimension of the fitness vector of the problem.
[in]ncglobal number of constraints.
[in]nicnumber of inequality constraints.
[in]c_tolconstraints tolerance std::vector
[in]seedrandom number generator seed

Definition at line 67 of file base_stochastic.cpp.

Member Function Documentation

unsigned int pagmo::problem::base_stochastic::get_seed ( ) const

Gets the pseudo random generator seed.

Gets the pseudo random generator seed.

Returns
random number generator seed

Definition at line 89 of file base_stochastic.cpp.

void pagmo::problem::base_stochastic::set_seed ( unsigned int  seed) const

Sets the pseudo random generator seed.

Sets the pseudo random generator seed.

Parameters
[in]seedrandom number generator seed

Definition at line 77 of file base_stochastic.cpp.


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