From a TMINLP, this class adapts to another TMINLP where the original objective is transformed into a constraint by adding an extra variable which is minimized. More...

#include <BonTMINLPLinObj.hpp>

Inheritance diagram for Bonmin::TMINLPLinObj:

List of all members.

Public Member Functions
	TMINLPLinObj ()
	Default constructor.
virtual	~TMINLPLinObj ()
	destructor.
void	setTminlp (Ipopt::SmartPtr< TMINLP > tminlp)
	set reference TMINLP
virtual bool	get_variables_linearity (Ipopt::Index n, Ipopt::TNLP::LinearityType *c)
	overload this method to provide the variables linearity.
virtual const BranchingInfo *	branchingInfo () const
	Use tminlp_ function.
virtual const SosInfo *	sosConstraints () const
	Use tminlp_ function.
virtual const PerturbInfo *	perturbInfo () const
	Use tminlp_ function.
virtual bool	hasUpperBoundingObjective ()
	Use tminlp_ function.
virtual bool	eval_upper_bound_f (Ipopt::Index n, const Ipopt::Number *x, Ipopt::Number &obj_value)
	Use tminlp_ function.
virtual bool	hasLinearObjective ()
	Say if problem has a linear objective (for OA)
Ipopt::SmartPtr< TMINLP >	tminlp ()
	return pointer to tminlp_.
methods to gather information about the MINLP
virtual bool	get_nlp_info (Ipopt::Index &n, Ipopt::Index &m, Ipopt::Index &nnz_jac_g, Ipopt::Index &nnz_h_lag, Ipopt::TNLP::IndexStyleEnum &index_style)
	Return the number of variables and constraints, and the number of non-zeros in the jacobian and the hessian.
virtual bool	get_scaling_parameters (Ipopt::Number &obj_scaling, bool &use_x_scaling, Ipopt::Index n, Ipopt::Number x_scaling, bool &use_g_scaling, Ipopt::Index m, Ipopt::Number g_scaling)
	Return scaling parameters.
virtual bool	get_variables_types (Ipopt::Index n, VariableType *var_types)
	Get the variable type.
virtual bool	get_constraints_linearity (Ipopt::Index m, Ipopt::TNLP::LinearityType *const_types)
	Return the constraints linearity.
virtual bool	get_bounds_info (Ipopt::Index n, Ipopt::Number x_l, Ipopt::Number x_u, Ipopt::Index m, Ipopt::Number g_l, Ipopt::Number g_u)
	Return the information about the bound on the variables and constraints.
virtual bool	get_starting_point (Ipopt::Index n, bool init_x, Ipopt::Number x, bool init_z, Ipopt::Number z_L, Ipopt::Number z_U, Ipopt::Index m, bool init_lambda, Ipopt::Number lambda)
	Return the starting point.
virtual bool	eval_f (Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Number &obj_value)
	Return the value of the objective function.
virtual bool	eval_grad_f (Ipopt::Index n, const Ipopt::Number x, bool new_x, Ipopt::Number grad_f)
	Return the vector of the gradient of the objective w.r.t.
virtual bool	eval_g (Ipopt::Index n, const Ipopt::Number x, bool new_x, Ipopt::Index m, Ipopt::Number g)
	Return the vector of constraint values.
virtual bool	eval_jac_g (Ipopt::Index n, const Ipopt::Number x, bool new_x, Ipopt::Index m, Ipopt::Index nele_jac, Ipopt::Index iRow, Ipopt::Index jCol, Ipopt::Number values)
	Return the jacobian of the constraints.
virtual bool	eval_h (Ipopt::Index n, const Ipopt::Number x, bool new_x, Ipopt::Number obj_factor, Ipopt::Index m, const Ipopt::Number lambda, bool new_lambda, Ipopt::Index nele_hess, Ipopt::Index iRow, Ipopt::Index jCol, Ipopt::Number *values)
	Return the hessian of the lagrangian.
virtual bool	eval_gi (Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Index i, Ipopt::Number &gi)
	Compute the value of a single constraint.
virtual bool	eval_grad_gi (Ipopt::Index n, const Ipopt::Number x, bool new_x, Ipopt::Index i, Ipopt::Index &nele_grad_gi, Ipopt::Index jCol, Ipopt::Number *values)
	Compute the structure or values of the gradient for one constraint.
Solution Methods
virtual void	finalize_solution (TMINLP::SolverReturn status, Ipopt::Index n, const Ipopt::Number *x, Ipopt::Number obj_value)
	Use tminlp_ function.
Private Member Functions
void	gutsOfDestructor ()
	Reset all data.
Private Attributes
Ipopt::SmartPtr< TMINLP >	tminlp_
	Reference TMINLP which is to be relaxed.
int	m_
	Ipopt::Number of constraints in the transformed MINLP.
int	n_
	Ipopt::Number of variables in the transformed MINLP.
int	nnz_jac_
	number of non-zeroes in the jacobian of the transformed MINLP.
int	offset_
	offset for jacobian.

Detailed Description

From a TMINLP, this class adapts to another TMINLP where the original objective is transformed into a constraint by adding an extra variable which is minimized.

More precisely

$\begin{array}{l} \min f(x)\\ s.t\\ g_l \leq g(x) \leq g_u\\ x_l \leq x \leq u \end{array}$

is transformed ino {array}{l} \ s.t\ - f(x) - 0\ g_l g(x) g_u\ x_l x u {array} ] The objective is put as first constraint of the problem and the extra variable is the last one.

Definition at line 39 of file BonTMINLPLinObj.hpp.

Constructor & Destructor Documentation

Bonmin::TMINLPLinObj::TMINLPLinObj ( )

Default constructor.

virtual Bonmin::TMINLPLinObj::~TMINLPLinObj ( ) [virtual]

destructor.

Member Function Documentation

void Bonmin::TMINLPLinObj::setTminlp ( Ipopt::SmartPtr< TMINLP > tminlp )

set reference TMINLP

virtual bool Bonmin::TMINLPLinObj::get_nlp_info	(	Ipopt::Index &	n,
		Ipopt::Index &	m,
		Ipopt::Index &	nnz_jac_g,
		Ipopt::Index &	nnz_h_lag,
		Ipopt::TNLP::IndexStyleEnum &	index_style
	)		`[virtual]`

Return the number of variables and constraints, and the number of non-zeros in the jacobian and the hessian.

Call tminlp_ one but number of constraints and non-zeroes in the jacobian is stored internally.

Implements Bonmin::TMINLP.

virtual bool Bonmin::TMINLPLinObj::get_scaling_parameters	(	Ipopt::Number &	obj_scaling,
		bool &	use_x_scaling,
		Ipopt::Index	n,
		Ipopt::Number *	x_scaling,
		bool &	use_g_scaling,
		Ipopt::Index	m,
		Ipopt::Number *	g_scaling
	)		`[virtual]`

Return scaling parameters.

If tminlp_ method returns true, translate constraint scaling (if asked).

Reimplemented from Bonmin::TMINLP.

virtual bool Bonmin::TMINLPLinObj::get_variables_types	(	Ipopt::Index	n,
		VariableType *	var_types
	)		`[inline, virtual]`

Get the variable type.

Just call tminlp_'s method;.

Implements Bonmin::TMINLP.

Definition at line 68 of file BonTMINLPLinObj.hpp.

References Bonmin::TMINLP::CONTINUOUS, n_, and tminlp_.

virtual bool Bonmin::TMINLPLinObj::get_constraints_linearity	(	Ipopt::Index	m,
		Ipopt::TNLP::LinearityType *	const_types
	)		`[virtual]`

Return the constraints linearity.

Call tminlp_'s method and translate.

Implements Bonmin::TMINLP.

virtual bool Bonmin::TMINLPLinObj::get_bounds_info	(	Ipopt::Index	n,
		Ipopt::Number *	x_l,
		Ipopt::Number *	x_u,
		Ipopt::Index	m,
		Ipopt::Number *	g_l,
		Ipopt::Number *	g_u
	)		`[virtual]`

Return the information about the bound on the variables and constraints.

Call tminlp_'s method and translate constraints bounds.

Implements Bonmin::TMINLP.

virtual bool Bonmin::TMINLPLinObj::get_starting_point	(	Ipopt::Index	n,
		bool	init_x,
		Ipopt::Number *	x,
		bool	init_z,
		Ipopt::Number *	z_L,
		Ipopt::Number *	z_U,
		Ipopt::Index	m,
		bool	init_lambda,
		Ipopt::Number *	lambda
	)		`[virtual]`

Return the starting point.

Have to translate z_L and z_U.

Implements Bonmin::TMINLP.

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

Return the value of the objective function.

Just call tminlp_ method.

Implements Bonmin::TMINLP.

Definition at line 96 of file BonTMINLPLinObj.hpp.

References n_.

virtual bool Bonmin::TMINLPLinObj::eval_grad_f	(	Ipopt::Index	n,
		const Ipopt::Number *	x,
		bool	new_x,
		Ipopt::Number *	grad_f
	)		`[inline, virtual]`

Return the vector of the gradient of the objective w.r.t.

x. Just call tminlp_ method.

Implements Bonmin::TMINLP.

Definition at line 104 of file BonTMINLPLinObj.hpp.

References n_, and tminlp_.

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

Return the vector of constraint values.

Use tminlp_ functions and use mapping to get the needed values.

Implements Bonmin::TMINLP.

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

Return the jacobian of the constraints.

In first call nothing to change. In later just fix the values for the simple concaves and remove entries corresponding to nonConvex constraints.

Implements Bonmin::TMINLP.

virtual bool Bonmin::TMINLPLinObj::eval_h	(	Ipopt::Index	n,
		const Ipopt::Number *	x,
		bool	new_x,
		Ipopt::Number	obj_factor,
		Ipopt::Index	m,
		const Ipopt::Number *	lambda,
		bool	new_lambda,
		Ipopt::Index	nele_hess,
		Ipopt::Index *	iRow,
		Ipopt::Index *	jCol,
		Ipopt::Number *	values
	)		`[virtual]`

Return the hessian of the lagrangian.

Here we just put lambda in the correct format and call tminlp_'s function.

Implements Bonmin::TMINLP.

virtual bool Bonmin::TMINLPLinObj::eval_gi	(	Ipopt::Index	n,
		const Ipopt::Number *	x,
		bool	new_x,
		Ipopt::Index	i,
		Ipopt::Number &	gi
	)		`[virtual]`

Compute the value of a single constraint.

The constraint number is i (starting counting from 0.

Reimplemented from Bonmin::TMINLP.

virtual bool Bonmin::TMINLPLinObj::eval_grad_gi	(	Ipopt::Index	n,
		const Ipopt::Number *	x,
		bool	new_x,
		Ipopt::Index	i,
		Ipopt::Index &	nele_grad_gi,
		Ipopt::Index *	jCol,
		Ipopt::Number *	values
	)		`[virtual]`

Compute the structure or values of the gradient for one constraint.

The constraint * number is i (starting counting from 0. Other things are like with eval_jac_g.

Reimplemented from Bonmin::TMINLP.

virtual bool Bonmin::TMINLPLinObj::get_variables_linearity	(	Ipopt::Index	n,
		Ipopt::TNLP::LinearityType *	var_types
	)		`[inline, virtual]`

overload this method to provide the variables linearity.

array should be allocated with length at least n.

Implements Bonmin::TMINLP.

Definition at line 145 of file BonTMINLPLinObj.hpp.

References n_, and tminlp_.

virtual void Bonmin::TMINLPLinObj::finalize_solution	(	TMINLP::SolverReturn	status,
		Ipopt::Index	n,
		const Ipopt::Number *	x,
		Ipopt::Number	obj_value
	)		`[inline, virtual]`