2 %> Algorithm 9.1: Direct resolution of quadratic problems. Implementation of algorithm 9.1 of \cite Bier15-book
4 %> @author <a href=
"http://people.epfl.ch/michel.bierlaire">Michel Bierlaire</a>
5 %> @date Fri Mar 20 11:03:31 2015
9 %> @note Tested with \ref run0908quad.m
12 %> Applies the direct resolution method to solve \f[\min_x \frac{1}{2} x^T Q x + b^T x\f] where \f$Q \in \mathbb{R}^n\times\mathbb{R}^n \f$ and \f$b \in \mathbb{R}^n\f$.
13 %> @param Q matrix of size \f$n \times n \f$.
14 %> @param b vector of size \f$n\f$.
15 %> @
return solution: optimal solution
function newtonLocalQuadratic(in obj, in x0, in eps, in cg, in maxiter)
Applies local Newton algorithm to solve where is the gradient of the objective function.
function quadraticDirect(in Q, in b)
Applies the direct resolution method to solve where and .