Date of Original Version
Abstract or Table of Contents
Abstract: "We propose a quasi-Newton algorithm for solving optimization problems with nonlinear equality constraints. It is designed for problems with few degrees of freedom and does not require the calculation of Lagrange multipliers. It can also be extended to large-scale systems through the use of sparse matrix factorizations. The algorithm has the same superlinear and global properties as the reduced Hessian method developed in our previous paper (Biegler, Nocedal and Schmid, 1995). This report directly reworks the theory presented in that paper to consider the multiplier free case."