An exterior newton method for strictly convex quadratic programming

We propose an exterior Newton method for strictly convex quadratic programm ing (QP) problems. This method is based on a dual formulation: a sequence o f points is generated which monotonically decreases the dual objective func tion. We show that the generated sequence converges globally and quadratica lly to the solution (if the QP is feasible and certain nondegeneracy assump tions are satisfied). Measures for detecting infeasibility are provided. Th e major computation in each iteration is to solve a KKT-like system. Theref ore, given an effective symmetric sparse linear solver, the proposed method is suitable for large sparse problems. Preliminary numerical results are r eported.