Nonlinear constrained optimization problem can be effectively solved by
minimizing a sequence of unconstrained or linearly constrained
subproblems, where the augmented Lagrangian function plays a vital role.
This talk introduces a generalized Hestenes-Powell augmented Lagrangian
function, which can be seen as a continuum of many well-known methods as
specific cases. A new primal dual sequential quadratic programming (pdSQP)
method will be given for minimizing the given augmented Lagrangian.
Tuesday, May 17, 2016
11:00AM AP&M 2402
Center for Computational Mathematics9500 Gilman Dr. #0112La Jolla, CA 92093-0112Tel: (858)534-9056