NLP interface class that adds variable and constriant permutations for variable reduction basis selections. More...

#include <NLPInterfacePack_NLPVarReductPerm.hpp>

Inheritance diagram for NLPInterfacePack::NLPVarReductPerm:

Classes
class	InvalidBasis
	Thrown if an invalid basis selection is made. More...

Private Attributes
Teuchos::AbstractFactory < AbstractLinAlgPack::Permutation > *	factory_P_var

Teuchos::AbstractFactory < AbstractLinAlgPack::Permutation > *	factory_P_equ

Public types
typedef Teuchos::RCP< const Teuchos::AbstractFactory < Permutation > >	perm_fcty_ptr_t

Abstract factories for Permutation objects
virtual const perm_fcty_ptr_t	factory_P_var () const =0

virtual const perm_fcty_ptr_t	factory_P_equ () const =0

Return ranges for the partitioning of variables and constraints
virtual Range1D	var_dep () const =0

virtual Range1D	var_indep () const =0

virtual Range1D	equ_decomp () const =0

virtual Range1D	equ_undecomp () const =0

Basis manipulation functions
virtual bool	nlp_selects_basis () const =0
	Returns true if the NLP can suggest one or more basis selections. More...

virtual bool	get_next_basis (Permutation P_var, Range1D var_dep, Permutation P_equ, Range1D equ_decomp)=0
	Returns the next basis the NLP has and sets the NLP to the returned basis. More...

virtual void	set_basis (const Permutation &P_var, const Range1D &var_dep, const Permutation P_equ, const Range1D equ_decomp)=0
	Sets the basis the that the NLP will use to permute the problem. More...

virtual void	get_basis (Permutation P_var, Range1D var_dep, Permutation P_equ, Range1D equ_decomp) const =0
	Returns the basis selection currently being used by the NLP. More...

Additional Inherited Members
Public Types inherited from NLPInterfacePack::NLP
typedef AbstractLinAlgPack::Vector	Vector

typedef AbstractLinAlgPack::VectorMutable	VectorMutable

typedef Teuchos::RCP< const VectorSpace >	vec_space_ptr_t

typedef Teuchos::RCP< const OptionsFromStreamPack::OptionsFromStream >	options_ptr_t

Public Member Functions inherited from NLPInterfacePack::NLP
const ZeroOrderInfo	zero_order_info () const
	Return pointer to set quantities. More...

const ZeroOrderInfo	zero_order_info_breve () const
	Return pointer to set `hat` quantities. More...

	NLP ()
	Initialize to no reference set to calculation quanities. More...

virtual	~NLP ()
	Destructor that cleans all the memory it owns. More...

virtual void	force_xinit_in_bounds (bool force_xinit_in_bounds)=0
	Set if the initial point must be within the bounds. More...

virtual bool	force_xinit_in_bounds () const =0
	Returns if the initial point must be within the bounds. More...

virtual void	set_options (const options_ptr_t &options)
	Set the options that `this` NLP may be interested in. More...

virtual const options_ptr_t &	get_options () const
	Get the `OptionsFromStream` object being used to extract the options from. More...

virtual void	initialize (bool test_setup=false)
	Initialize the NLP before it is used. More...

virtual bool	is_initialized () const =0
	Return if `this` is initialized. More...

virtual size_type	n () const
	Return the number of variables. More...

virtual size_type	m () const
	Return the number of general equality constraints. More...

virtual vec_space_ptr_t	space_x () const =0
	Vector space object for unknown variables x (dimension n). More...

virtual vec_space_ptr_t	space_c () const =0
	Vector space object for general equality constraints c(x) (dimension m). More...

virtual size_type	num_bounded_x () const =0
	Returns the number of variables in `x(i)` for which `xl(i)> -infinite_bound()` or `xu(i) < +infinite_bound()`. More...

virtual const Vector &	xl () const =0
	Returns the lower bounds on the variables `x`. More...

virtual const Vector &	xu () const =0
	Returns a reference to the vector of upper bounds on the variables `x`. More...

virtual value_type	max_var_bounds_viol () const =0
	Set the maximum absolute value for which the variable bounds may be violated by when computing function and gradient values. More...

virtual const Vector &	xinit () const =0
	Returns a reference to the vector of the initial guess for the solution `x`. More...

virtual void	get_init_lagrange_mult (VectorMutable lambda, VectorMutable nu) const
	Get the initial value of the Lagrange multipliers lambda. More...

virtual void	set_f (value_type *f)
	Set a pointer to an value to be updated when `this->calc_f()` is called. More...

virtual value_type *	get_f ()
	Return pointer passed to `this->set_f()`. More...

virtual value_type &	f ()
	Returns non-`const` `*this->get_f()`. More...

virtual const value_type &	f () const
	Returns `const` `*this->get_f()`. More...

virtual void	set_c (VectorMutable *c)
	Set a pointer to a vector to be updated when `this->calc_c()` is called. More...

virtual VectorMutable *	get_c ()
	Return pointer passed to `this->set_c()`. More...

virtual VectorMutable &	c ()
	Returns non-`const` `*this->get_c()`. More...

virtual const Vector &	c () const
	Returns `const` `*this->get_c()`. More...

virtual void	unset_quantities ()
	Call to unset all storage quantities (both in this class and all subclasses). More...

virtual void	scale_f (value_type scale_f)=0
	Set the scaling of the objective function. More...

virtual value_type	scale_f () const =0
	Return the scaling being used for the objective function. More...

virtual void	calc_f (const Vector &x, bool newx=true) const
	Update the value for the objective `f` at the point `x` and put it in the stored reference. More...

virtual void	calc_c (const Vector &x, bool newx=true) const
	Update the constraint residual vector for `c` at the point `x` and put it in the stored reference. More...

virtual void	report_final_solution (const Vector &x, const Vector lambda, const Vector nu, bool is_optimal)
	Used by the solver to report the final solution and multipliers. More...

virtual size_type	num_f_evals () const
	Gives the number of object function f(x) evaluations called by the solver since initialize() was called. More...

virtual size_type	num_c_evals () const
	Gives the number of constraint function c(x) evaluations called by the solver since initialize() was called. Throws exception if `this->m() == 0`. More...

virtual size_type	ns () const
	Return the number of slack variables (i.e. number of general inequalities). More...

virtual vec_space_ptr_t	space_c_breve () const
	Vector space object for the original equalities `c_breve(x_breve)` More...

virtual vec_space_ptr_t	space_h_breve () const
	Vector space object for the original inequalities `h_breve(x_breve)` More...

virtual const Vector &	hl_breve () const
	Returns a reference to the vector of lower bounds on the general inequality constraints `h_breve(x_breve)`. More...

virtual const Vector &	hu_breve () const
	Returns a reference to the vector of upper bounds on the general inequality constraints `h_breve(x_breve)`. More...

virtual void	set_c_breve (VectorMutable *c_breve)
	Set a pointer to a vector to be updated when `this->calc_c_breve()` is called. More...

virtual VectorMutable *	get_c_breve ()
	Return pointer passed to `this->set_c_breve()`. More...

virtual VectorMutable &	c_breve ()
	Returns non-`const` `*this->get_c_breve()`. More...

virtual const Vector &	c_breve () const
	Returns `const` `*this->get_c_breve()`. More...

virtual void	set_h_breve (VectorMutable *h_breve)
	Set a pointer to a vector to be updated when `this->calc_h_breve()` is called. More...

virtual VectorMutable *	get_h_breve ()
	Return pointer passed to `this->set_h_breve()`. More...

virtual VectorMutable &	h_breve ()
	Returns non-`const` `*this->get_h_breve()`. More...

virtual const Vector &	h_breve () const
	Returns `const` `*this->get_h_breve()`. More...

virtual const Permutation &	P_var () const
	Return the permutation object for the variables. More...

virtual const Permutation &	P_equ () const
	Return the permutation object for the constraints. More...

virtual void	calc_c_breve (const Vector &x, bool newx=true) const
	Update the constraint residual vector for `c_breve` at the point `x` and put it in the stored reference. More...

virtual void	calc_h_breve (const Vector &x, bool newx=true) const
	Update the constraint residual vector for `h_breve` at the point `x` and put it in the stored reference. More...

Public Member Functions inherited from Teuchos::VerboseObject< NLP >
TEUCHOSPARAMETERLIST_LIB_DLL_EXPORT RCP< const ParameterList >	getValidVerboseObjectSublist ()

TEUCHOSPARAMETERLIST_LIB_DLL_EXPORT void	setupVerboseObjectSublist (ParameterList *paramList)

TEUCHOSPARAMETERLIST_LIB_DLL_EXPORT void	readVerboseObjectSublist (ParameterList paramList, RCP< FancyOStream > oStream, EVerbosityLevel *verbLevel)

void	readVerboseObjectSublist (ParameterList paramList, VerboseObject< NLP > verboseObject)

	VerboseObject (const EVerbosityLevel verbLevel=VERB_DEFAULT, const RCP< FancyOStream > &oStream=Teuchos::null)

virtual void	initializeVerboseObject (const EVerbosityLevel verbLevel=VERB_DEFAULT, const RCP< FancyOStream > &oStream=Teuchos::null)

virtual const VerboseObject &	setVerbLevel (const EVerbosityLevel verbLevel) const

virtual const VerboseObject &	setOverridingVerbLevel (const EVerbosityLevel verbLevel) const

virtual EVerbosityLevel	getVerbLevel () const

Static Public Member Functions inherited from NLPInterfacePack::NLP
static value_type	infinite_bound ()
	Value for an infinite bound. More...

Static Public Member Functions inherited from Teuchos::VerboseObject< NLP >
static void	setDefaultVerbLevel (const EVerbosityLevel defaultVerbLevel)

static EVerbosityLevel	getDefaultVerbLevel ()

Protected Member Functions inherited from NLPInterfacePack::NLP
template<class T >
void	assert_ref_set (T *p, std::string info) const
	Assert referece has been set for a quanity. More...

virtual void	imp_calc_f (const Vector &x, bool newx, const ZeroOrderInfo &zero_order_info) const =0
	Overridden to compute f(x) (and perhaps other quantities if set). More...

virtual void	imp_calc_c (const Vector &x, bool newx, const ZeroOrderInfo &zero_order_info) const =0
	Overridden to compute c(x) and perhaps f(x) and/or h(x) (if multiple calculaiton = true). More...

virtual void	imp_calc_c_breve (const Vector &x, bool newx, const ZeroOrderInfo &zero_order_info_breve) const
	Overridden to compute c_breve(x_breve) and perhaps f(x) and/or h_breve(x_breve) More...

virtual void	imp_calc_h_breve (const Vector &x, bool newx, const ZeroOrderInfo &zero_order_info_breve) const
	Overridden to compute h_breve(x_breve) and perhaps f(x) and/or c_breve(x_breve). More...

Detailed Description

NLP interface class that adds variable and constriant permutations for variable reduction basis selections.

This class adds basis selection and manipulation. This functionality is needed by many optimization algorithms that categorize variables and constraints into specific sets according to a basis selection. To understand what sets these are, consider the following equality constraints (from the NLP interface).

           c(x)  = 0,    c(x) <: R^n -> R^m

This interface allows x and c(x) to be partitioned into different sets. The variables x are partitioned into a dependent set x(var_dep) and an independent set x(var_dep) by the permutation P_var. The equality constraints c(x) are partitioned into decomposed c(equ_decomp) and undecomposed c(equ_undecomp) sets by the permutation P_equ. These permutations permute from an original order to a new ordering. For example:

 Original Ordering      Permutation to new ordering                Partitioning
 -----------------    -------------------------------   -------------------------------------
      x_orig          P_var.permute(trans,x_orig,x)     -> x(var_dep),      x(var_indep)
      c_orig          P_equ.permute(trans,c_orig,c)     -> c(equ_decomp),   c(equ_undecomp)

Because of this partitioning, it is expected that the following vector sub-spaces will be non-null: space_x()->sub_space(var_indep), space_x()->sub_space(var_dep), space_c()->sub_space(equ_decomp), space_c()->sub_space(equ_undecomp). Other subspaces may be non-null also but these are the only ones that are required to be.

After initialization, the NLP subclass will be initialized to the first basis. This basis may be the original ordering if P_var and P_equ all return xxx_perm.is_identity(). If the concrete NLP is selecting the basis (nlp_selects_basis() == true) this basis will be that first basis. The first time that this->get_next_basis() is called it will return this initial basis (which may not be the original ordering).

The client can always see what this first basis is by calling this->get_basis(). If a basis goes singular the client can request other basis selections from the NLP by calling this->get_next_basis() (which will return true if more basis selections are available). The client can also select a basis itself and then set that basis by calling this->set_basis() to force the use of that basis selection. In this way a valid basis is automatically selected after initialization so that clients using another interface (NLP, NLPFirstOrder, or NLPSecondOrder) will be able to use the NLP object without even knowing about a basis selection.

Below are some obviouls assertions about the basis selection:

P_var.space().dim() == this->n() (throw std::length_error)
P_equ.space().dim() == this->m() (throw std::length_error)
var_dep.size() <= min( this->m() , this->n() ) (throw InvalidBasis)
var_dep.size() == equ_decomp.size() (throw InvalidBasis)
Other obvious assertions on the basis selection?

Definition at line 105 of file NLPInterfacePack_NLPVarReductPerm.hpp.

Member Typedef Documentation

typedef Teuchos::RCP< const Teuchos::AbstractFactory<Permutation> > NLPInterfacePack::NLPVarReductPerm::perm_fcty_ptr_t

Definition at line 114 of file NLPInterfacePack_NLPVarReductPerm.hpp.

Member Function Documentation

virtual const perm_fcty_ptr_t NLPInterfacePack::NLPVarReductPerm::factory_P_var ( ) const

pure virtual

Implemented in NLPInterfacePack::NLPSerialPreprocess.

virtual const perm_fcty_ptr_t NLPInterfacePack::NLPVarReductPerm::factory_P_equ ( ) const

pure virtual

Implemented in NLPInterfacePack::NLPSerialPreprocess.

virtual Range1D NLPInterfacePack::NLPVarReductPerm::var_dep ( ) const

pure virtual

Implemented in NLPInterfacePack::NLPSerialPreprocess.

virtual Range1D NLPInterfacePack::NLPVarReductPerm::var_indep ( ) const

pure virtual

Implemented in NLPInterfacePack::NLPSerialPreprocess.

virtual Range1D NLPInterfacePack::NLPVarReductPerm::equ_decomp ( ) const

pure virtual

Implemented in NLPInterfacePack::NLPSerialPreprocess.

virtual Range1D NLPInterfacePack::NLPVarReductPerm::equ_undecomp ( ) const

pure virtual

Implemented in NLPInterfacePack::NLPSerialPreprocess.

virtual bool NLPInterfacePack::NLPVarReductPerm::nlp_selects_basis ( ) const

pure virtual

Returns true if the NLP can suggest one or more basis selections.

Implemented in NLPInterfacePack::NLPSerialPreprocess, NLPInterfacePack::ExampleNLPBanded, and NLPInterfacePack::NLPWBCounterExample.

virtual bool NLPInterfacePack::NLPVarReductPerm::get_next_basis	(	Permutation *	P_var,
		Range1D *	var_dep,
		Permutation *	P_equ,
		Range1D *	equ_decomp
	)

pure virtual

Returns the next basis the NLP has and sets the NLP to the returned basis.

Parameters

P_var	[out] Variable permutations defined as `P_var'*x_old -> x_new = [ x(var_dep); x(var_indep) ]`
var_dep	[out] Range of dependent variables in `x_new(var_dep)`
P_equ	[out] Equality constraint permutations defined as `P_equ'*c_old -> c_new = [ c(equ_decomp); c(equ_undecomp) ]`
equ_decomp	[out] Range of decomposed equalities in `c_new(equ_decomp)`

Postconditions: The NLP is set to the basis returned in the arguments and this->get_basis() will return the same basis.

This member returns true if the NLP has another basis to select, and is false if not. If false is returned the client has the option of selecting another basis on its own and passing it to the NLP by calling this->set_basis().

Implemented in NLPInterfacePack::NLPSerialPreprocess, and NLPInterfacePack::NLPSerialPreprocessExplJac.

virtual void NLPInterfacePack::NLPVarReductPerm::set_basis	(	const Permutation &	P_var,
		const Range1D &	var_dep,
		const Permutation *	P_equ,
		const Range1D *	equ_decomp
	)

pure virtual

Sets the basis the that the NLP will use to permute the problem.

Parameters

P_var	[in] Variable permutations defined as `P_var'*x_old -> x_new = [ x(var_dep); x(var_indep) ]`
var_dep	[in] Range of dependent variables in `x_new(var_dep)`
P_equ	[in] Equality constraint permutations defined as `P_equ'*c_old -> c_new = [ c(equ_decomp); c(equ_undecomp) ]`
equ_decomp	[in] Range of decomposed equalities in `c_new(equ_decomp)`

Preconditions: The input basis meets the basis assertions stated above or an InvalidBasis exceptin is thrown.

Postconditions: The NLP is set to the basis given in the arguments and this->get_basis() will return this same basis.

Implemented in NLPInterfacePack::NLPSerialPreprocess, and NLPInterfacePack::NLPSerialPreprocessExplJac.

virtual void NLPInterfacePack::NLPVarReductPerm::get_basis	(	Permutation *	P_var,
		Range1D *	var_dep,
		Permutation *	P_equ,
		Range1D *	equ_decomp
	)		const

pure virtual

Returns the basis selection currently being used by the NLP.

Parameters

P_var	[out] Variable permutations defined as `P_var'*x_old -> x_new = [ x(var_dep); x(var_indep) ]`
var_dep	[out] Range of dependent variables in `x_new(var_dep)`
P_equ	[out] Equality constraint permutations defined as `P_equ'*c_old -> c_new = [ c(equ_decomp); c(equ_undecomp) ]`
equ_decomp	[out] Range of decomposed equalities in `c_new(equ_decomp)`