A filter line search algorithm based on an inexact Newton method for nonconvex equality constrained optimization

We propose an inexact Newton method with a filter line search algorithm for nonconvex equality constrained optimization. Inexact Newton’s methods are needed for large-scale applications which the iteration matrix cannot be explicitly formed or factored. We incorporate inexact Newton strategies in filter line search, yielding algorithm that can ensure global convergence. An analysis of the global behavior of the algorithm and numerical results on a collection of test problems are presented.