This paper describes a software implementation of R. H. Byrd’s
[Robust trust region methods for constrained optimization, Third SIAM Conference on Optimization, Houston,TX, May 1987] and E. O. Omojokun’s
[Trust region algorithms for optimization with nonlinear equality and inequality constraints, Ph.D. thesis, Univ. of Colorado, Boulder (1989)] trust region algorithm for solving nonlinear equality constrained optimization problems. The code is designed for the efficient solution of large problems and provides the user with a variety of linear algebra techniques for solving the subproblems occurring in the algorithm. Second derivative information can be used, but when it is not available, limited memory quasi-Newton approximations are made. The performance of the code is studied using a set of difficult problems from the CUTE collection.