Class implementing the TNLP for strengthening one cut. More...

Public Member Functions
	StrengtheningTNLP (SmartPtr< TMINLP > tminlp, const CoinPackedVector &cut, bool lower_bound, Index n, const Number starting_point, const double x_l_orig, const double x_u_orig, Index constr_index, Index nvar_constr, const Index jCol)
	Contructor.
	~StrengtheningTNLP ()
	Destructor.
Number	StrengthenedBound () const
	Method for asking for the strengthened bound.
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.
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.
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.
virtual bool	eval_f (Index n, const Number *x, bool new_x, Number &obj_value)
	Method to return the objective value.
virtual bool	eval_grad_f (Index n, const Number x, bool new_x, Number grad_f)
	Method to return the gradient of the objective.
virtual bool	eval_g (Index n, const Number x, bool new_x, Index m, Number g)
	Method to return the constraint residuals.
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)
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)
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.
Private Member Functions
void	update_x_full (const Number *x)
	Auxilliary method for updating the full x variable.
Methods to block default compiler methods.
	StrengtheningTNLP ()
	StrengtheningTNLP (const StrengtheningTNLP &)
StrengtheningTNLP &	operator= (const StrengtheningTNLP &)
Private Attributes
const SmartPtr< TMINLP >	tminlp_
	TMINLP (with current bounds) for which the cut it to be generated.
Number *	obj_grad_
	Gradient of the (linear) objective function.
const Index	n_orig_
	Dimension of original problem.
Index	m_orig_
	Number of constraints in original problem.
Number *	starting_point_
	Starting point.
Number *	x_full_
	Full dimentional x which is used to call the TMINLP evaluation routines.
Number *	x_l_
	Lower bounds for constraint variables.
Number *	x_u_
	Upper bounds for constraint variables.
const Index	constr_index_
	Index of the constraint.
const Index	nvar_constr_
	Number of variables appearing in the constraint.
Index *	var_indices_
	List of variables appearing on the constraints.
bool	lower_bound_
	Flag indicating if the cut has a lower or upper bound.
bool	have_final_bound_
	Flag indicating if we TNLP has been solved successfully.
Number	strengthened_bound_
	Final strengthened bound.
Number *	grad_f_
	space for original gradient if objective function is handled

Detailed Description

Class implementing the TNLP for strengthening one cut.

We assume that the cut has a lower bound.

Definition at line 38 of file BonCutStrengthener.hpp.

Constructor & Destructor Documentation

Bonmin::CutStrengthener::StrengtheningTNLP::StrengtheningTNLP	(	SmartPtr< TMINLP >	tminlp,
		const CoinPackedVector &	cut,
		bool	lower_bound,
		Index	n,
		const Number *	starting_point,
		const double *	x_l_orig,
		const double *	x_u_orig,
		Index	constr_index,
		Index	nvar_constr,
		const Index *	jCol
	)

Contructor.

Parameters:

nvar_constr Number of variables in constraint

Bonmin::CutStrengthener::StrengtheningTNLP::~StrengtheningTNLP ( )

Destructor.

Bonmin::CutStrengthener::StrengtheningTNLP::StrengtheningTNLP ( ) [private]

Bonmin::CutStrengthener::StrengtheningTNLP::StrengtheningTNLP ( const StrengtheningTNLP & ) [private]

Member Function Documentation

virtual bool Bonmin::CutStrengthener::StrengtheningTNLP::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.

virtual bool Bonmin::CutStrengthener::StrengtheningTNLP::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.

virtual bool Bonmin::CutStrengthener::StrengtheningTNLP::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.

virtual bool Bonmin::CutStrengthener::StrengtheningTNLP::eval_f	(	Index	n,
		const Number *	x,
		bool	new_x,
		Number &	obj_value
	)		`[virtual]`

Method to return the objective value.

virtual bool Bonmin::CutStrengthener::StrengtheningTNLP::eval_grad_f	(	Index	n,
		const Number *	x,
		bool	new_x,
		Number *	grad_f
	)		`[virtual]`

Method to return the gradient of the objective.

virtual bool Bonmin::CutStrengthener::StrengtheningTNLP::eval_g	(	Index	n,
		const Number *	x,
		bool	new_x,
		Index	m,
		Number *	g
	)		`[virtual]`

Method to return the constraint residuals.

virtual bool Bonmin::CutStrengthener::StrengtheningTNLP::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)

virtual bool Bonmin::CutStrengthener::StrengtheningTNLP::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)

virtual void Bonmin::CutStrengthener::StrengtheningTNLP::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]`