Copyright © 2012 Meiling Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
A filter algorithm with inexact line search is proposed
for solving nonlinear programming problems. The filter is constructed by employing
the norm of the gradient of the Lagrangian function to the infeasibility
measure. Transition to superlinear local convergence is showed for the proposed
filter algorithm without second-order correction. Under mild conditions, the
global convergence can also be derived. Numerical experiments show the efficiency
of the algorithm.