We present an algorithm for large-scale equality constrained optimization. The method is based on a characterization of inexact sequential quadratic programming (SQP) steps that ca...
Abstract We present a matrix-free line search algorithm for large-scale equality constrained optimization that allows for inexact step computations. For sufficiently convex problem...
Abstract. Optimization problems constrained by nonlinear partial differential equations have been the focus of intense research in scientific computing lately. Current methods for...
Ernesto E. Prudencio, Richard H. Byrd, Xiao-Chuan ...
We present a class of inexact adaptive multilevel trust-region SQP-methods for the efficient solution of optimization problems governed by nonlinear partial differential equations...
The aim of the paper is to provide a theoretical basis for approximate reduced SQP methods. In contrast to inexact reduced SQP methods, the forward and the adjoint problem accuraci...
Kazufumi Ito, Karl Kunisch, Volker Schulz, Ilia Gh...