A second order method for unconstrained optimization

Abstract

An algorithm using second derivatives for solving unconstrained optimization problems is presented. In this brief note the descent direction of the algorithm is based on a modification of the Newton direction, while the Armijo rule for choosing the stepsize is used. The rate of convergence of the algorithm is shown to be superlinear. Our computational experience shows that the method performs quite well and our numerical results are presented in Section 4.

Keywords:

• Nonlinear programming
• unconstrained optimization
• superlinear convergence

C.R. Categories:

• G.1.6