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#ifndef QLP_HH
#define QLP_HH
#include "matrix.hh"
/// inequality constrained quadratic program
class Ineq_constrained_qp {
friend class Active_constraints;
svec<Vector> cons;
svec<Real> consrhs;
public:
Matrix quad;
Vector lin;
Real const_term;
///
void assert_solution(Vector sol) const;
/**
use a KKT method to assert optimality of sol
*/
/// solve the problem using a projected gradient method
Vector solve(Vector start) const;
int dim() const{
return lin.dim();
}
/** return the number of variables in the problem */
///
void add_inequality_cons(Vector c, double r);
/**
add a constraint
c*vars >= r
PRE
c.dim() == dim();
*/
///
Ineq_constrained_qp(int novars);
/** set up matrices to go with the problem. */
Real eval(Vector v);
/**
evaluate the quadratic function for input #v#
*/
void eliminate_var(int idx, Real value);
void OK()const;
void print() const;
};
/// Quadratic programming with mixed linear constraints
class Mixed_qp :public Ineq_constrained_qp {
svec<int> eq_cons;
svec<Real> eq_consrhs;
public:
Mixed_qp(int n);
void OK() const;
void print() const;
Vector solve(Vector start) const;
void add_fixed_var(int i , Real value);
///
void add_equality_cons(Vector c, double r);
/**
add a constraint,
c*vars == r
PRE
c.dim()==dim();
*/
};
/**
problem definition of a quadratic optimisation problem with linear
inequality and equality constraints
x^T QUAD x /2 + b^T x
*/
#endif
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