A line search filter algorithm with inexact step computations for equality constrained optimization
A new inexact Newton-like algorithm for equality constrained optimization in the framework of a standard line search method is presented. The main feature of this algorithm is to combine inexact step computations with filter techniques proposed by \textit{R. Fletcher} and \textit{S. Leyffer} [Math. Program. 91, No. 2 (A), 239--269 (2002; Zbl 1049.90088)]. It can also be regarded as an inexact version of generic sequential quadratic programming methods. The trial step is obtained by truncatedly solving the primal-dual system based on any robust and efficient linear system solver such as a Krylov subspace method. Practical termination tests for the linear system solver are established to ensure global convergence. Preliminary numerical results demonstrate the approach is potentially usefull.
scientific article; zbMATH DE number 6015739