#include <CGAL/QP_models.h>
$$
(QP)$$  minimize$$  c^{T}x+c_{0} 
subject to$$  Ax ~ b,  
x 0 
in $$n real variables $$x=(x_{0},...,x_{n1}). Here,
This class is simply a wrapper for existing iterators, and it does not copy the program data.
It frequently happens that all values in one of the vectors from above are the same, for example if the system $$Ax ~ b is actually a system of equations $$Ax=b. To get an iterator over such a vector, it is not necessary to store multiple copies of the value in some container; an instance of the class Const_oneset_iterator<T>, constructed from the value in question, does the job more efficiently.
 
constructs lp from given randomaccess iterators and the constant
c0. The passed iterators are merely stored, no copying of the program
data takes place. How these iterators are supposed to encode the nonnegative
linear program is described in NonnegativeLinearProgram.

QP_solver/first_nonnegative_lp_from_iterators.cpp
QP_solver/solve_convex_hull_containment_lp.h
QP_solver/convex_hull_containment.cpp