Author(s)

M. El-Sayed, S. Anderson and K. Zumwalt

Abstract

Constrained optimization methods classically fall into the categories of zero- or first-order algorithms. In this paper, a second order constrained optimization method, sequential quadratic programming with quadratic constraints (SQPQC), is developed. This method uses first- and second-order derivative information to build a second-order Taylor's series expansion to the constrained optimization problem. By using duality, the resulting subproblem, to find the search direction, is transformed into an unconstrained optimization problem with respect to the dual variables. Comparisons with robust feasible directions (RFD), for a curved plate shape optimization test case, is presented. 1. Introduction Many numerical methods exist to solve all the classes of the

Keywords