Numerical Experience with a Reduced Hessian Methodfor Large Scale Constrained Optimization
Computational Optimization and Applications
On the development of a trust region interior-point method for large scale nonlinear programs
Proceedings of the 2003 conference on Diversity in computing
CUTEr and SifDec: A constrained and unconstrained testing environment, revisited
ACM Transactions on Mathematical Software (TOMS)
Computational Optimization and Applications
Steering exact penalty methods for nonlinear programming
Optimization Methods & Software - Dedicated to Professor Michael J.D. Powell on the occasion of his 70th birthday
A Truncated SQP Method Based on Inexact Interior-Point Solutions of Subproblems
SIAM Journal on Optimization
Numerical experiments with an inexact Jacobian trust-region algorithm
Computational Optimization and Applications
A line search filter algorithm with inexact step computations for equality constrained optimization
Applied Numerical Mathematics
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This paper describes a software implementation of Byrd and Omojokun's 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 test problems from the CUTE collection.