This class maps a IpoptNLP into one that is used for the restoration phase of Ipopt. More...

#include <IpRestoIpoptNLP.hpp>

Inheritance diagram for Ipopt::RestoIpoptNLP:

Public Member Functions
virtual bool	Initialize (const Journalist &jnlst, const OptionsList &options, const std::string &prefix)
	Initialization method.

virtual bool	InitializeStructures (SmartPtr< Vector > &x, bool init_x, SmartPtr< Vector > &y_c, bool init_y_c, SmartPtr< Vector > &y_d, bool init_y_d, SmartPtr< Vector > &z_L, bool init_z_L, SmartPtr< Vector > &z_U, bool init_z_U, SmartPtr< Vector > &v_L, SmartPtr< Vector > &v_U)
	Initialize (create) structures for the iteration data.

virtual bool	GetWarmStartIterate (IteratesVector &)
	Method accessing the GetWarmStartIterate of the NLP.

void	FinalizeSolution (SolverReturn, const Vector &, const Vector &, const Vector &, const Vector &, const Vector &, const Vector &, const Vector &, Number, const IpoptData , IpoptCalculatedQuantities )

virtual void	GetSpaces (SmartPtr< const VectorSpace > &x_space, SmartPtr< const VectorSpace > &c_space, SmartPtr< const VectorSpace > &d_space, SmartPtr< const VectorSpace > &x_l_space, SmartPtr< const MatrixSpace > &px_l_space, SmartPtr< const VectorSpace > &x_u_space, SmartPtr< const MatrixSpace > &px_u_space, SmartPtr< const VectorSpace > &d_l_space, SmartPtr< const MatrixSpace > &pd_l_space, SmartPtr< const VectorSpace > &d_u_space, SmartPtr< const MatrixSpace > &pd_u_space, SmartPtr< const MatrixSpace > &Jac_c_space, SmartPtr< const MatrixSpace > &Jac_d_space, SmartPtr< const SymMatrixSpace > &Hess_lagrangian_space)
	Accessor method for vector/matrix spaces pointers.

virtual void	AdjustVariableBounds (const Vector &new_x_L, const Vector &new_x_U, const Vector &new_d_L, const Vector &new_d_U)
	Method for adapting the variable bounds.

bool	IntermediateCallBack (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, SmartPtr< const IpoptData > ip_data, SmartPtr< IpoptCalculatedQuantities > ip_cq)
	User callback method.

Number	Rho () const
	Accessor Method for obtaining the Rho penalization factor for the ell_1 norm.

Number	Eta (Number mu) const
	Method to calculate eta, the factor for the regularization term.

SmartPtr< const Vector >	DR_x () const
	Method returning the scaling factors for the 2-norm penalization term.

Constructors/Destructors
	RestoIpoptNLP (IpoptNLP &orig_ip_nlp, IpoptData &orig_ip_data, IpoptCalculatedQuantities &orig_ip_cq)

	~RestoIpoptNLP ()
	Destructor.


virtual bool	objective_depends_on_mu () const
	Accessor methods for model data.

virtual Number	f (const Vector &x)
	Objective value (incorrect version for restoration phase)

virtual Number	f (const Vector &x, Number mu)
	Objective value.

virtual SmartPtr< const Vector >	grad_f (const Vector &x)
	Gradient of the objective (incorrect version for restoration phase)

virtual SmartPtr< const Vector >	grad_f (const Vector &x, Number mu)
	Gradient of the objective.

virtual SmartPtr< const Vector >	c (const Vector &x)
	Equality constraint residual.

virtual SmartPtr< const Matrix >	jac_c (const Vector &x)
	Jacobian Matrix for equality constraints.

virtual SmartPtr< const Vector >	d (const Vector &x)
	Inequality constraint residual (reformulated as equalities with slacks.

virtual SmartPtr< const Matrix >	jac_d (const Vector &x)
	Jacobian Matrix for inequality constraints.

virtual SmartPtr< const SymMatrix >	h (const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd)
	Hessian of the Lagrangian (incorrect version for restoration phase)

virtual SmartPtr< const SymMatrix >	h (const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd, Number mu)
	Hessian of the Lagrangian.

virtual SmartPtr< const SymMatrix >	uninitialized_h ()
	Provides a Hessian matrix from the correct matrix space with uninitialized values.

virtual SmartPtr< const Vector >	x_L () const
	Lower bounds on x.

virtual SmartPtr< const Matrix >	Px_L () const
	Permutation matrix (x_L_ -> x)

virtual SmartPtr< const Vector >	x_U () const
	Upper bounds on x.

virtual SmartPtr< const Matrix >	Px_U () const
	Permutation matrix (x_U_ -> x.

virtual SmartPtr< const Vector >	d_L () const
	Lower bounds on d.

virtual SmartPtr< const Matrix >	Pd_L () const
	Permutation matrix (d_L_ -> d)

virtual SmartPtr< const Vector >	d_U () const
	Upper bounds on d.

virtual SmartPtr< const Matrix >	Pd_U () const
	Permutation matrix (d_U_ -> d.

virtual SmartPtr< const SymMatrixSpace >	HessianMatrixSpace () const
	Accessor method to obtain the MatrixSpace for the Hessian matrix (or it's approximation)

virtual SmartPtr< const VectorSpace >	x_space () const
	x_space

Accessor method for the information of the original NLP.
These methods are not overloaded from IpoptNLP.
IpoptNLP &	OrigIpNLP () const

IpoptData &	OrigIpData () const

IpoptCalculatedQuantities &	OrigIpCq () const

Counters for the number of function evaluations.
virtual Index	f_evals () const

virtual Index	grad_f_evals () const

virtual Index	c_evals () const

virtual Index	jac_c_evals () const

virtual Index	d_evals () const

virtual Index	jac_d_evals () const

virtual Index	h_evals () const

Public Member Functions inherited from Ipopt::IpoptNLP
SmartPtr< NLPScalingObject >	NLP_scaling () const
	Returns the scaling strategy object.

	IpoptNLP (const SmartPtr< NLPScalingObject > nlp_scaling)

virtual	~IpoptNLP ()
	Destructor.

	DECLARE_STD_EXCEPTION (Eval_Error)
	thrown if there is any error evaluating values from the nlp

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

Static Public Member Functions
static void	RegisterOptions (SmartPtr< RegisteredOptions > roptions)

Private Member Functions
Default Compiler Generated Methods
(Hidden to avoid implicit creation/calling). These methods are not implemented and we do not want the compiler to implement them for us, so we declare them private and do not define them. This ensures that they will not be implicitly created/called.
	RestoIpoptNLP ()
	Default Constructor.

	RestoIpoptNLP (const RestoIpoptNLP &)
	Copy Constructor.

void	operator= (const RestoIpoptNLP &)
	Default Assignment Operator.

Private Attributes
bool	initialized_
	Flag indicating if initialization method has been called.

Pointers for the original NLP information.
SmartPtr< IpoptNLP >	orig_ip_nlp_
	Pointer to the original IpoptNLP.

SmartPtr< IpoptData >	orig_ip_data_
	Pointer to the original IpoptData.

SmartPtr< IpoptCalculatedQuantities >	orig_ip_cq_
	Pointer to the original IpoptCalculatedQuantities.


SmartPtr< CompoundVectorSpace >	x_space_
	Necessary Vector/Matrix spaces.

SmartPtr< CompoundVectorSpace >	c_space_

SmartPtr< CompoundVectorSpace >	d_space_

SmartPtr< CompoundVectorSpace >	x_l_space_

SmartPtr< CompoundMatrixSpace >	px_l_space_

SmartPtr< CompoundVectorSpace >	x_u_space_

SmartPtr< CompoundMatrixSpace >	px_u_space_

SmartPtr< CompoundVectorSpace >	d_l_space_

SmartPtr< CompoundMatrixSpace >	pd_l_space_

SmartPtr< CompoundVectorSpace >	d_u_space_

SmartPtr< CompoundMatrixSpace >	pd_u_space_

SmartPtr< CompoundMatrixSpace >	jac_c_space_

SmartPtr< CompoundMatrixSpace >	jac_d_space_

SmartPtr< CompoundSymMatrixSpace >	h_space_

Storage for Model Quantities
SmartPtr< CompoundVector >	x_L_
	Lower bounds on x.

SmartPtr< CompoundMatrix >	Px_L_
	Permutation matrix (x_L_ -> x)

SmartPtr< CompoundVector >	x_U_
	Upper bounds on x.

SmartPtr< CompoundMatrix >	Px_U_
	Permutation matrix (x_U_ -> x)

SmartPtr< CompoundVector >	d_L_
	Lower bounds on d.

SmartPtr< CompoundMatrix >	Pd_L_
	Permutation matrix (d_L_ -> d)

SmartPtr< CompoundVector >	d_U_
	Upper bounds on d.

SmartPtr< CompoundMatrix >	Pd_U_
	Permutation matrix (d_U_ -> d.

Values particular to the restoration phase problem statement
Number	rho_
	Penalty parameter for the $l_1$ norm, given by resto_penalty_parameter.

Number	eta_factor_
	scaling factor for eta calculation

Number	eta_mu_exponent_
	exponent for mu in eta calculation

SmartPtr< const Vector >	dr_x_
	Scaling factors for the $x$ part of the regularization term.

SmartPtr< const Vector >	dr2_x_
	Squared scaling factors for the $x$ part of the regularization term, for grad_f.

SmartPtr< const DiagMatrix >	DR2_x_
	Matrix with squared scaling factors, for h()

SmartPtr< const Vector >	x_ref_
	$x$ part of the reference point in the regularization term

Algorithmic parameter
bool	evaluate_orig_obj_at_resto_trial_
	Flag indicating if evaluation of the objective should be performed for every restoration phase objective function evaluation.

HessianApproximationType	hessian_approximation_
	Flag indicating how Hessian information is obtained.

Counters for the function evaluations
Index	f_evals_

Index	grad_f_evals_

Index	c_evals_

Index	jac_c_evals_

Index	d_evals_

Index	jac_d_evals_

Index	h_evals_

Detailed Description

This class maps a IpoptNLP into one that is used for the restoration phase of Ipopt.

Given a IpoptNLP

\begin{eqnarray*} \mathrm{min} && f(x), \\ \mathrm{s.t.} && c(x) = 0, &\qquad y_c\\ && d_L \leq d(x) \leq d_U, &\qquad y_d \\ && x_L \leq x \leq x_U, &\qquad z_L, z_U \end{eqnarray*}

parameters $\rho$, $\eta$, and a reference point $x_r$, a RestoIpoptNLP is the NLP

\begin{eqnarray*} \mathrm{min} && \rho (p_c^Te + n_c^Te + p_d^Te + n_d^Te) + \frac{\eta}{2} \Vert D_r (x-x_r) \Vert_2^2, \\ \mathrm{s.t.} && c(x) - p_c + n_c = 0, &\qquad y_c\\ && d_L \leq d(x) - p_d + n_d \leq d_U, &\qquad y_d \\ && x_L \leq x \leq x_U, &\qquad z_L, z_U \\ && p_c, n_c, p_d, n_d \geq 0. &\qquad ... \end{eqnarray*}

where $D_r = \mathrm{diag}(\frac{1}{\max\{1,|x_{r,i}|\}},\ldots,\frac{1}{\max\{1,|x_{r,n}|\}})$.

Parameter $\rho$ is determined by option resto_penalty_parameter (default = 1000). Parameter $\eta = \eta_f \sqrt{\mu}$, where $\eta_f$ is determined by option resto_proximity_weight (default = 1).

Definition at line 47 of file IpRestoIpoptNLP.hpp.

Constructor & Destructor Documentation

◆ RestoIpoptNLP() [1/3]

Ipopt::RestoIpoptNLP::RestoIpoptNLP	(	IpoptNLP &	orig_ip_nlp,
		IpoptData &	orig_ip_data,
		IpoptCalculatedQuantities &	orig_ip_cq
	)

◆ ~RestoIpoptNLP()

Ipopt::RestoIpoptNLP::~RestoIpoptNLP ( )

Destructor.

◆ RestoIpoptNLP() [2/3]

Ipopt::RestoIpoptNLP::RestoIpoptNLP ( )

private

Default Constructor.

◆ RestoIpoptNLP() [3/3]

Ipopt::RestoIpoptNLP::RestoIpoptNLP ( const RestoIpoptNLP & )

private

Copy Constructor.

Member Function Documentation

◆ Initialize()

virtual bool Ipopt::RestoIpoptNLP::Initialize	(	const Journalist &	jnlst,
		const OptionsList &	options,
		const std::string &	prefix
	)

virtual

Initialization method.

Set the internal options and initialize internal data structures.

Reimplemented from Ipopt::IpoptNLP.

◆ InitializeStructures()

virtual bool Ipopt::RestoIpoptNLP::InitializeStructures	(	SmartPtr< Vector > &	x,
		bool	init_x,
		SmartPtr< Vector > &	y_c,
		bool	init_y_c,
		SmartPtr< Vector > &	y_d,
		bool	init_y_d,
		SmartPtr< Vector > &	z_L,
		bool	init_z_L,
		SmartPtr< Vector > &	z_U,
		bool	init_z_U,
		SmartPtr< Vector > &	v_L,
		SmartPtr< Vector > &	v_U
	)

virtual

Initialize (create) structures for the iteration data.

Public Member Functions

Static Public Member Functions

Private Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ RestoIpoptNLP() [1/3]

◆ ~RestoIpoptNLP()

◆ RestoIpoptNLP() [2/3]

◆ RestoIpoptNLP() [3/3]

Member Function Documentation

◆ Initialize()

◆ InitializeStructures()

◆ GetWarmStartIterate()

◆ FinalizeSolution()

◆ objective_depends_on_mu()

◆ f() [1/2]

◆ f() [2/2]

◆ grad_f() [1/2]

◆ grad_f() [2/2]

◆ c()

◆ jac_c()

◆ d()

◆ jac_d()

◆ h() [1/2]

◆ h() [2/2]

◆ uninitialized_h()

◆ x_L()

◆ Px_L()

◆ x_U()

◆ Px_U()

◆ d_L()

◆ Pd_L()

◆ d_U()

◆ Pd_U()

◆ HessianMatrixSpace()

◆ x_space()

◆ GetSpaces()

◆ AdjustVariableBounds()

◆ IntermediateCallBack()

◆ OrigIpNLP()

◆ OrigIpData()

◆ OrigIpCq()

◆ Rho()

◆ f_evals()

◆ grad_f_evals()

◆ c_evals()

◆ jac_c_evals()

◆ d_evals()

◆ jac_d_evals()

◆ h_evals()

◆ Eta()

◆ DR_x()

◆ RegisterOptions()

◆ operator=()

Member Data Documentation

◆ orig_ip_nlp_

◆ orig_ip_data_

◆ orig_ip_cq_

◆ x_space_

◆ c_space_

◆ d_space_

◆ x_l_space_

◆ px_l_space_

◆ x_u_space_

◆ px_u_space_

◆ d_l_space_

◆ pd_l_space_

◆ d_u_space_

◆ pd_u_space_

◆ jac_c_space_

◆ jac_d_space_

◆ h_space_

◆ x_L_

◆ Px_L_

◆ x_U_

◆ Px_U_

◆ d_L_

◆ Pd_L_

◆ d_U_