TNLP Class Reference

#include <IpTNLP.hpp>

Inheritance diagram for TNLP:

Detailed Description

Base class for all NLP's that use standard triplet matrix form and dense vectors.

This is the standard base class for all NLP's that use the standard triplet matrix form (as for Harwell routines) and dense vectors. The class TNLPAdapter then converts this interface to an interface that can be used directly by ipopt.

This interface presents the problem form:

min f(x)

s.t. gL <= g(x) <= gU

xL <= x <= xU

In order to specify an equality constraint, set gL_i = gU_i = rhs. The value that indicates "infinity" for the bounds (i.e. the variable or constraint has no lower bound (-infinity) or upper bound (+infinity)) is set through the option nlp_lower_bound_inf and nlp_upper_bound_inf. To indicate that a variable has no upper or lower bound, set the bound to -ipopt_inf or +ipopt_inf respectively

methods to gather information about the NLP

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...

virtual bool get_nlp_info (Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, IndexStyleEnum &index_style)=0

overload this method to return the number of variables and constraints, and the number of non-zeros in the jacobian and the hessian.

virtual bool get_bounds_info (Index n, Number *x_l, Number *x_u, Index m, Number *g_l, Number *g_u)=0

overload this method to return the information about the bound on the variables and constraints.

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.

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)=0

overload this method to return the starting point.

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.

virtual bool eval_f (Index n, const Number *x, bool new_x, Number &obj_value)=0

overload this method to return the value of the objective function

virtual bool eval_grad_f (Index n, const Number *x, bool new_x, Number *grad_f)=0

overload this method to return the vector of the gradient of the objective w.r.t.

virtual bool eval_g (Index n, const Number *x, bool new_x, Index m, Number *g)=0

overload this method to return the vector of constraint values

virtual bool eval_jac_g (Index n, const Number *x, bool new_x, Index m, Index nele_jac, Index *iRow, Index *jCol, Number *values)=0

overload this method to return the jacobian of the constraints.

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)

overload this method to return the hessian of the lagrangian.

Public Member Functions

DECLARE_STD_EXCEPTION (INVALID_TNLP)

Constructors/Destructors

TNLP ()

Default destructor.

virtual ~TNLP ()

Default destructor.

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)=0

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

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.

Methods for quasi-Newton approximation. If the second

derivatives are approximated by Ipopt, it is better to do this only in the space of nonlinear variables.
The following methods are call by Ipopt if the quasi-Newton approximation is selected. If -1 is returned as number of nonlinear variables, Ipopt assumes that all variables are nonlinear. Otherwise, it calls get_list_of_nonlinear_variables with an array into which the indices of the nonlinear variables should be written - the array has the lengths num_nonlin_vars, which is identical with the return value of get_number_of_nonlinear_variables(). It is assumed that the indices are counted starting with 1 in the FORTRAN_STYLE, and 0 for the C_STYLE.

virtual Index get_number_of_nonlinear_variables ()

virtual bool get_list_of_nonlinear_variables (Index num_nonlin_vars, Index *pos_nonlin_vars)

Member Enumeration Documentation

enum IndexStyleEnum

overload this method to return the number of variables and constraints, and the number of non-zeros in the jacobian and the hessian.

The index_style parameter lets you specify C or Fortran style indexing for the sparse matrix iRow and jCol parameters. C_STYLE is 0-based, and FORTRAN_STYLE is 1-based.

Enumerator:

C_STYLE
FORTRAN_STYLE

Constructor & Destructor Documentation

TNLP ( ) [inline]

Default destructor.

virtual ~TNLP ( ) [inline, virtual]

Default destructor.

Member Function Documentation

DECLARE_STD_EXCEPTION ( INVALID_TNLP )

virtual bool get_nlp_info	(	Index &	n,
		Index &	m,
		Index &	nnz_jac_g,
		Index &	nnz_h_lag,
		IndexStyleEnum &	index_style
	)			`[pure virtual]`

overload this method to return the number of variables and constraints, and the number of non-zeros in the jacobian and the hessian.

The index_style parameter lets you specify C or Fortran style indexing for the sparse matrix iRow and jCol parameters. C_STYLE is 0-based, and FORTRAN_STYLE is 1-based.

Implemented in StdInterfaceTNLP.

virtual bool get_bounds_info	(	Index	n,
		Number *	x_l,
		Number *	x_u,
		Index	m,
		Number *	g_l,
		Number *	g_u
	)			`[pure virtual]`

overload this method to return the information about the bound on the variables and constraints.

The value that indicates that a bound does not exist is specified in the parameters nlp_lower_bound_inf and nlp_upper_bound_inf. By default, nlp_lower_bound_inf is -1e19 and nlp_upper_bound_inf is 1e19. (see TNLPAdapter)

Implemented in StdInterfaceTNLP.

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
	)			`[inline, virtual]`

overload this method to return scaling parameters.

This is only called if the options are set to retrieve user scaling. There, use_x_scaling (or use_g_scaling) should get set to true only if the variables (or constraints) are to be scaled. This method should return true only if the scaling parameters could be provided.

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
	)			`[pure virtual]`

overload this method to return the starting point.

The bools init_x and init_lambda are both inputs and outputs. As inputs, they indicate whether or not the algorithm wants you to initialize x and lambda respectively. If, for some reason, the algorithm wants you to initialize these and you cannot, set the respective bool to false.

Implemented in StdInterfaceTNLP.

virtual bool get_warm_start_iterate ( IteratesVector & warm_start_iterate ) [inline, virtual]

overload this method to provide an Ipopt iterate (already in the form Ipopt requires it internally) for a warm start.

Since this is only for expert users, a default dummy implementation is provided and returns false.

virtual bool eval_f	(	Index	n,
		const Number *	x,
		bool	new_x,
		Number &	obj_value
	)			`[pure virtual]`

overload this method to return the value of the objective function

Implemented in StdInterfaceTNLP.

virtual bool eval_grad_f	(	Index	n,
		const Number *	x,
		bool	new_x,
		Number *	grad_f
	)			`[pure virtual]`

overload this method to return the vector of the gradient of the objective w.r.t.

x

Implemented in StdInterfaceTNLP.

virtual bool eval_g	(	Index	n,
		const Number *	x,
		bool	new_x,
		Index	m,
		Number *	g
	)			`[pure virtual]`

overload this method to return the vector of constraint values

Implemented in StdInterfaceTNLP.

virtual bool eval_jac_g	(	Index	n,
		const Number *	x,
		bool	new_x,
		Index	m,
		Index	nele_jac,
		Index *	iRow,
		Index *	jCol,
		Number *	values
	)			`[pure virtual]`

overload this method to return the jacobian of the constraints.

The vectors iRow and jCol only need to be set once. The first call is used to set the structure only (iRow and jCol will be non-NULL, and values will be NULL) For subsequent calls, iRow and jCol will be NULL.

Implemented in StdInterfaceTNLP.

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
	)			`[inline, virtual]`

overload this method to return the hessian of the lagrangian.

The vectors iRow and jCol only need to be set once (during the first call). The first call is used to set the structure only (iRow and jCol will be non-NULL, and values will be NULL) For subsequent calls, iRow and jCol will be NULL. This matrix is symmetric - specify the lower diagonal only. A default implementation is provided, in case the user wants to se quasi-Newton approximations to estimate the second derivatives and doesn't not neet to implement this method.

Reimplemented in StdInterfaceTNLP.

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
	)			`[pure virtual]`

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

Implemented in StdInterfaceTNLP.

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
	)			`[inline, virtual]`

Intermediate Callback method for the user.

Providing dummy default implementation. For details see IntermediateCallBack in IpNLP.hpp.

virtual Index get_number_of_nonlinear_variables ( ) [inline, virtual]

virtual bool get_list_of_nonlinear_variables	(	Index	num_nonlin_vars,
		Index *	pos_nonlin_vars
	)			`[inline, virtual]`

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

IpTNLP.hpp


methods to gather information about the NLP
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...
virtual bool	get_nlp_info (Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, IndexStyleEnum &index_style)=0
	overload this method to return the number of variables and constraints, and the number of non-zeros in the jacobian and the hessian.
virtual bool	get_bounds_info (Index n, Number x_l, Number x_u, Index m, Number g_l, Number g_u)=0
	overload this method to return the information about the bound on the variables and constraints.
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.
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)=0
	overload this method to return the starting point.
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.
virtual bool	eval_f (Index n, const Number *x, bool new_x, Number &obj_value)=0
	overload this method to return the value of the objective function
virtual bool	eval_grad_f (Index n, const Number x, bool new_x, Number grad_f)=0
	overload this method to return the vector of the gradient of the objective w.r.t.
virtual bool	eval_g (Index n, const Number x, bool new_x, Index m, Number g)=0
	overload this method to return the vector of constraint values
virtual bool	eval_jac_g (Index n, const Number x, bool new_x, Index m, Index nele_jac, Index iRow, Index jCol, Number values)=0
	overload this method to return the jacobian of the constraints.
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)
	overload this method to return the hessian of the lagrangian.
Public Member Functions
	DECLARE_STD_EXCEPTION (INVALID_TNLP)
Constructors/Destructors
	TNLP ()
	Default destructor.
virtual	~TNLP ()
	Default destructor.
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)=0
	This method is called when the algorithm is complete so the TNLP can store/write the solution.
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.
Methods for quasi-Newton approximation. If the second
derivatives are approximated by Ipopt, it is better to do this only in the space of nonlinear variables. The following methods are call by Ipopt if the quasi-Newton approximation is selected. If -1 is returned as number of nonlinear variables, Ipopt assumes that all variables are nonlinear. Otherwise, it calls get_list_of_nonlinear_variables with an array into which the indices of the nonlinear variables should be written - the array has the lengths num_nonlin_vars, which is identical with the return value of get_number_of_nonlinear_variables(). It is assumed that the indices are counted starting with 1 in the FORTRAN_STYLE, and 0 for the C_STYLE.
virtual Index	get_number_of_nonlinear_variables ()
virtual bool	get_list_of_nonlinear_variables (Index num_nonlin_vars, Index *pos_nonlin_vars)