LPSolver Class Reference

To solve a linear programming problem. More...

#include <LPSolver.h>

Public Types
enum	Setting {   OBJECTIVE = 0 ,   LE_CONSTRAINT = 1 ,   GE_CONSTRAINT = 2 ,   EQ_CONSTRAINT = 3 }

Public Member Functions
	LPSolver ()
	Default constructor.
	LPSolver (int nv, int nb_le, int nb_ge, int nb_eq)
	Constructor using Linear Program data.
	~LPSolver ()
	Destructor.
void	setSize (int nv, int nb_le, int nb_ge, int nb_eq)
	Set optimization parameters.
void	set (Vect< real_t > &x)
	vector of optimization variables
void	set (Setting opt, const Vect< real_t > &a, real_t b=0.0)
	Set optimization data.
int	run ()
	Run the linear program solver.
real_t	getObjective () const
	Return objective.

Detailed Description

To solve a linear programming problem.

The Linear Program reads:

Minimise: d(1)*x(1) + ... + d(n)*x(n) + e
Subject to the constraints:
       A(i,1)*x(1) + ... + A(i,n)*x(n) <= a(i)  i=1,...,n_le
       B(i,1)*x(1) + ... + B(i,n)*x(n) >= b(i)  i=1,...,n_ge
       C(i,1)*x(1) + ... + C(i,n)*x(n) =  c(i)  i=1,...,n_eq
       x(i) >= 0, 1<=i<=n

Solution is held by the Simplex method Reference: "Numerical Recipes By W.H. Press, B. P. Flannery, S.A. Teukolsky and W.T. Vetterling, Cambridge University Press, 1986"

C-implementation copied from J-P Moreau, Paris

Author

Rachid Touzani

Copyright

GNU Lesser Public License

Member Enumeration Documentation

Setting

enum Setting

Selects setting option: Objective or Constraints

Enumerator
OBJECTIVE	Objective function coefficients
LE_CONSTRAINT	'Less or Equal' constraint coefficients
GE_CONSTRAINT	'Greater or Equal' constraint coefficients
EQ_CONSTRAINT	'Equality' constraint coefficients

Constructor & Destructor Documentation

LPSolver()

LPSolver	(	int	nv,
		int	nb_le,
		int	nb_ge,
		int	nb_eq
	)

Constructor using Linear Program data.

Parameters

[in]	nv	Number of optimization variables
[in]	nb_le	Number of '<=' inequality constraints
[in]	nb_ge	Number of '>=' inequality constraints
[in]	nb_eq	Number of '=' equality constraints

Member Function Documentation

getObjective()

real_t getObjective

(

)

const

Return objective.

Once execution is complete, this function returns optimal value of objective

run()

int run

(

)

Run the linear program solver.

This function runs the linear programming solver using the Simplex algorithm

Returns

0 if process is complete, >0 otherwise

set() [1/2]

void set	(	Setting	opt,
		const Vect< real_t > &	a,
		real_t	b = 0.0
	)

Set optimization data.

This function enables providing all optimization data. It has to be used for the objectice function and once for each constraint.

Parameters

[in]	opt	Option for data, to choose among enumerated values: OBJECTIVE To set objective function to minimize LE_CONSTRAINT To set a '<=' inequality constraint GE_CONSTRAINT To set a '>=' inequality constraint EQ_CONSTRAINT To set an equality constraint
[in]	a	Vector coefficients if the chosen function. If opt==OBJECTIVE, vector components are the coefficients multiplying the variables in the objective function. if xx_CONSTRAINT, vector components are the coefficients multiplying the variables in the corresponding constraint.
[in]	b	Constant value in the objective function or in a constraint. Its default value is 0.0

set() [2/2]

void set

(

Vect< real_t > &

x

)

vector of optimization variables

Parameters

[in]

x

Vector of optimization variables. Its size must be at least equal to number of optimization variables

setSize()

void setSize	(	int	nv,
		int	nb_le,
		int	nb_ge,
		int	nb_eq
	)

Set optimization parameters.

Parameters

[in]	nv	Number of optimization variables
[in]	nb_le	Number of '<=' inequality constraints
[in]	nb_ge	Number of '>=' inequality constraints
[in]	nb_eq	Number of '=' equality constraints