Ipopt  3.12.9
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Macros
Public Member Functions | List of all members
HS071_NLP Class Reference

C++ Example NLP for interfacing a problem with IPOPT. More...

#include <hs071_nlp.hpp>

+ Inheritance diagram for HS071_NLP:

Public Member Functions

 HS071_NLP ()
 default constructor More...
 
virtual ~HS071_NLP ()
 default destructor More...
 
 HS071_NLP ()
 default constructor More...
 
virtual ~HS071_NLP ()
 default destructor More...
 
Overloaded from TNLP
virtual bool get_nlp_info (Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, IndexStyleEnum &index_style)
 Method to return some info about the nlp. More...
 
virtual bool get_bounds_info (Index n, Number *x_l, Number *x_u, Index m, Number *g_l, Number *g_u)
 Method to return the bounds for my problem. More...
 
virtual bool get_starting_point (Index n, bool init_x, Number *x, bool init_z, Number *z_L, Number *z_U, Index m, bool init_lambda, Number *lambda)
 Method to return the starting point for the algorithm. More...
 
virtual bool eval_f (Index n, const Number *x, bool new_x, Number &obj_value)
 Method to return the objective value. More...
 
virtual bool eval_grad_f (Index n, const Number *x, bool new_x, Number *grad_f)
 Method to return the gradient of the objective. More...
 
virtual bool eval_g (Index n, const Number *x, bool new_x, Index m, Number *g)
 Method to return the constraint residuals. More...
 
virtual bool eval_jac_g (Index n, const Number *x, bool new_x, Index m, Index nele_jac, Index *iRow, Index *jCol, Number *values)
 Method to return: 1) The structure of the jacobian (if "values" is NULL) 2) The values of the jacobian (if "values" is not NULL) More...
 
virtual bool eval_h (Index n, const Number *x, bool new_x, Number obj_factor, Index m, const Number *lambda, bool new_lambda, Index nele_hess, Index *iRow, Index *jCol, Number *values)
 Method to return: 1) The structure of the hessian of the lagrangian (if "values" is NULL) 2) The values of the hessian of the lagrangian (if "values" is not NULL) More...
 
virtual bool get_nlp_info (Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, IndexStyleEnum &index_style)
 Method to return some info about the nlp. More...
 
virtual bool get_bounds_info (Index n, Number *x_l, Number *x_u, Index m, Number *g_l, Number *g_u)
 Method to return the bounds for my problem. More...
 
virtual bool get_starting_point (Index n, bool init_x, Number *x, bool init_z, Number *z_L, Number *z_U, Index m, bool init_lambda, Number *lambda)
 Method to return the starting point for the algorithm. More...
 
virtual bool eval_f (Index n, const Number *x, bool new_x, Number &obj_value)
 Method to return the objective value. More...
 
virtual bool eval_grad_f (Index n, const Number *x, bool new_x, Number *grad_f)
 Method to return the gradient of the objective. More...
 
virtual bool eval_g (Index n, const Number *x, bool new_x, Index m, Number *g)
 Method to return the constraint residuals. More...
 
virtual bool eval_jac_g (Index n, const Number *x, bool new_x, Index m, Index nele_jac, Index *iRow, Index *jCol, Number *values)
 Method to return: 1) The structure of the jacobian (if "values" is NULL) 2) The values of the jacobian (if "values" is not NULL) More...
 
virtual bool eval_h (Index n, const Number *x, bool new_x, Number obj_factor, Index m, const Number *lambda, bool new_lambda, Index nele_hess, Index *iRow, Index *jCol, Number *values)
 Method to return: 1) The structure of the hessian of the lagrangian (if "values" is NULL) 2) The values of the hessian of the lagrangian (if "values" is not NULL) More...
 
Solution Methods
virtual void finalize_solution (SolverReturn status, Index n, const Number *x, const Number *z_L, const Number *z_U, Index m, const Number *g, const Number *lambda, Number obj_value, const IpoptData *ip_data, IpoptCalculatedQuantities *ip_cq)
 This method is called when the algorithm is complete so the TNLP can store/write the solution. More...
 
virtual void finalize_solution (SolverReturn status, Index n, const Number *x, const Number *z_L, const Number *z_U, Index m, const Number *g, const Number *lambda, Number obj_value, const IpoptData *ip_data, IpoptCalculatedQuantities *ip_cq)
 This method is called when the algorithm is complete so the TNLP can store/write the solution. More...
 
- Public Member Functions inherited from Ipopt::TNLP
 DECLARE_STD_EXCEPTION (INVALID_TNLP)
 
 TNLP ()
 
virtual ~TNLP ()
 Default destructor. More...
 
virtual void finalize_metadata (Index n, const StringMetaDataMapType &var_string_md, const IntegerMetaDataMapType &var_integer_md, const NumericMetaDataMapType &var_numeric_md, Index m, const StringMetaDataMapType &con_string_md, const IntegerMetaDataMapType &con_integer_md, const NumericMetaDataMapType &con_numeric_md)
 This method is called just before finalize_solution. More...
 
virtual bool intermediate_callback (AlgorithmMode mode, Index iter, Number obj_value, Number inf_pr, Number inf_du, Number mu, Number d_norm, Number regularization_size, Number alpha_du, Number alpha_pr, Index ls_trials, const IpoptData *ip_data, IpoptCalculatedQuantities *ip_cq)
 Intermediate Callback method for the user. More...
 
virtual Index get_number_of_nonlinear_variables ()
 
virtual bool get_list_of_nonlinear_variables (Index num_nonlin_vars, Index *pos_nonlin_vars)
 
virtual bool get_var_con_metadata (Index n, StringMetaDataMapType &var_string_md, IntegerMetaDataMapType &var_integer_md, NumericMetaDataMapType &var_numeric_md, Index m, StringMetaDataMapType &con_string_md, IntegerMetaDataMapType &con_integer_md, NumericMetaDataMapType &con_numeric_md)
 overload this method to return any meta data for the variables and the constraints More...
 
virtual bool get_scaling_parameters (Number &obj_scaling, bool &use_x_scaling, Index n, Number *x_scaling, bool &use_g_scaling, Index m, Number *g_scaling)
 overload this method to return scaling parameters. More...
 
virtual bool get_variables_linearity (Index n, LinearityType *var_types)
 overload this method to return the variables linearity (TNLP::LINEAR or TNLP::NON_LINEAR). More...
 
virtual bool get_constraints_linearity (Index m, LinearityType *const_types)
 overload this method to return the constraint linearity. More...
 
virtual bool get_warm_start_iterate (IteratesVector &warm_start_iterate)
 overload this method to provide an Ipopt iterate (already in the form Ipopt requires it internally) for a warm start. More...
 
- Public Member Functions inherited from Ipopt::ReferencedObject
 ReferencedObject ()
 
virtual ~ReferencedObject ()
 
Index ReferenceCount () const
 
void AddRef (const Referencer *referencer) const
 
void ReleaseRef (const Referencer *referencer) const
 

Private Member Functions

Methods to block default compiler methods.

The compiler automatically generates the following three methods.

Since the default compiler implementation is generally not what you want (for all but the most simple classes), we usually put the declarations of these methods in the private section and never implement them. This prevents the compiler from implementing an incorrect "default" behavior without us knowing. (See Scott Meyers book, "Effective C++")

 HS071_NLP (const HS071_NLP &)
 
HS071_NLPoperator= (const HS071_NLP &)
 
 HS071_NLP (const HS071_NLP &)
 
HS071_NLPoperator= (const HS071_NLP &)
 

Additional Inherited Members

- Public Types inherited from Ipopt::TNLP
enum  LinearityType { LINEAR, NON_LINEAR }
 Type of the constraints. More...
 
enum  IndexStyleEnum { C_STYLE =0, FORTRAN_STYLE =1 }
 overload this method to return the number of variables and constraints, and the number of non-zeros in the jacobian and the hessian. More...
 
typedef std::map< std::string,
std::vector< std::string > > 
StringMetaDataMapType
 
typedef std::map< std::string,
std::vector< Index > > 
IntegerMetaDataMapType
 
typedef std::map< std::string,
std::vector< Number > > 
NumericMetaDataMapType
 

Detailed Description

C++ Example NLP for interfacing a problem with IPOPT.

HS071_NLP implements a C++ example of problem 71 of the Hock-Schittkowski test suite. This example is designed to go along with the tutorial document and show how to interface with IPOPT through the TNLP interface.

Problem hs071 looks like this

min   x1*x4*(x1 + x2 + x3)  +  x3
s.t.  x1*x2*x3*x4                   >=  25
      x1**2 + x2**2 + x3**2 + x4**2  =  40
      1 <=  x1,x2,x3,x4  <= 5

Starting point:
   x = (1, 5, 5, 1)

Optimal solution:
   x = (1.00000000, 4.74299963, 3.82114998, 1.37940829)

Definition at line 37 of file hs071_nlp.hpp.

Constructor & Destructor Documentation

HS071_NLP::HS071_NLP ( )

default constructor

virtual HS071_NLP::~HS071_NLP ( )
virtual

default destructor

HS071_NLP::HS071_NLP ( const HS071_NLP )
private
HS071_NLP::HS071_NLP ( )

default constructor

virtual HS071_NLP::~HS071_NLP ( )
virtual

default destructor

HS071_NLP::HS071_NLP ( const HS071_NLP )
private

Member Function Documentation

virtual bool HS071_NLP::get_nlp_info ( Index n,
Index m,
Index nnz_jac_g,
Index nnz_h_lag,
IndexStyleEnum index_style 
)
virtual

Method to return some info about the nlp.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::get_bounds_info ( Index  n,
Number x_l,
Number x_u,
Index  m,
Number g_l,
Number g_u 
)
virtual

Method to return the bounds for my problem.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::get_starting_point ( Index  n,
bool  init_x,
Number x,
bool  init_z,
Number z_L,
Number z_U,
Index  m,
bool  init_lambda,
Number lambda 
)
virtual

Method to return the starting point for the algorithm.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::eval_f ( Index  n,
const Number x,
bool  new_x,
Number obj_value 
)
virtual

Method to return the objective value.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::eval_grad_f ( Index  n,
const Number x,
bool  new_x,
Number grad_f 
)
virtual

Method to return the gradient of the objective.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::eval_g ( Index  n,
const Number x,
bool  new_x,
Index  m,
Number g 
)
virtual

Method to return the constraint residuals.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::eval_jac_g ( Index  n,
const Number x,
bool  new_x,
Index  m,
Index  nele_jac,
Index iRow,
Index jCol,
Number values 
)
virtual

Method to return: 1) The structure of the jacobian (if "values" is NULL) 2) The values of the jacobian (if "values" is not NULL)

Implements Ipopt::TNLP.

virtual bool HS071_NLP::eval_h ( Index  n,
const Number x,
bool  new_x,
Number  obj_factor,
Index  m,
const Number lambda,
bool  new_lambda,
Index  nele_hess,
Index iRow,
Index jCol,
Number values 
)
virtual

Method to return: 1) The structure of the hessian of the lagrangian (if "values" is NULL) 2) The values of the hessian of the lagrangian (if "values" is not NULL)

Reimplemented from Ipopt::TNLP.

virtual void HS071_NLP::finalize_solution ( SolverReturn  status,
Index  n,
const Number x,
const Number z_L,
const Number z_U,
Index  m,
const Number g,
const Number lambda,
Number  obj_value,
const IpoptData ip_data,
IpoptCalculatedQuantities ip_cq 
)
virtual

This method is called when the algorithm is complete so the TNLP can store/write the solution.

Implements Ipopt::TNLP.

HS071_NLP& HS071_NLP::operator= ( const HS071_NLP )
private
virtual bool HS071_NLP::get_nlp_info ( Index n,
Index m,
Index nnz_jac_g,
Index nnz_h_lag,
IndexStyleEnum index_style 
)
virtual

Method to return some info about the nlp.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::get_bounds_info ( Index  n,
Number x_l,
Number x_u,
Index  m,
Number g_l,
Number g_u 
)
virtual

Method to return the bounds for my problem.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::get_starting_point ( Index  n,
bool  init_x,
Number x,
bool  init_z,
Number z_L,
Number z_U,
Index  m,
bool  init_lambda,
Number lambda 
)
virtual

Method to return the starting point for the algorithm.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::eval_f ( Index  n,
const Number x,
bool  new_x,
Number obj_value 
)
virtual

Method to return the objective value.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::eval_grad_f ( Index  n,
const Number x,
bool  new_x,
Number grad_f 
)
virtual

Method to return the gradient of the objective.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::eval_g ( Index  n,
const Number x,
bool  new_x,
Index  m,
Number g 
)
virtual

Method to return the constraint residuals.

Implements Ipopt::TNLP.

virtual bool HS071_NLP::eval_jac_g ( Index  n,
const Number x,
bool  new_x,
Index  m,
Index  nele_jac,
Index iRow,
Index jCol,
Number values 
)
virtual

Method to return: 1) The structure of the jacobian (if "values" is NULL) 2) The values of the jacobian (if "values" is not NULL)

Implements Ipopt::TNLP.

virtual bool HS071_NLP::eval_h ( Index  n,
const Number x,
bool  new_x,
Number  obj_factor,
Index  m,
const Number lambda,
bool  new_lambda,
Index  nele_hess,
Index iRow,
Index jCol,
Number values 
)
virtual

Method to return: 1) The structure of the hessian of the lagrangian (if "values" is NULL) 2) The values of the hessian of the lagrangian (if "values" is not NULL)

Reimplemented from Ipopt::TNLP.

virtual void HS071_NLP::finalize_solution ( SolverReturn  status,
Index  n,
const Number x,
const Number z_L,
const Number z_U,
Index  m,
const Number g,
const Number lambda,
Number  obj_value,
const IpoptData ip_data,
IpoptCalculatedQuantities ip_cq 
)
virtual

This method is called when the algorithm is complete so the TNLP can store/write the solution.

Implements Ipopt::TNLP.

HS071_NLP& HS071_NLP::operator= ( const HS071_NLP )
private

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