Numerical study of a matrix-free trust-region SQP method for equality constrained optimization
Denis Ridzal, USDOE National Nuclear Security Administration (NNSA), Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States), Miguel A. Aguiló, Matthias Heinkenschloss · 2011
This is a companion publication to the paper 'A Matrix-Free Trust-Region SQP Algorithm for Equality Constrained Optimization' [11]. In [11], we develop and analyze a trust-region sequential quadratic programming (SQP) method that supports the matrix-free (iterative, in-exact) solution of linear systems. In this report, we document the numerical behavior of the algorithm applied to a variety of equality constrained optimization problems, with constraints given by partial differential equations (PDEs).