In recent years, much work has been done on implementing a variety of algorithms in nonlinear programming software. In this paper, we analyze the performance of several state-of-the-art optimization codes on large-scale nonlinear optimization problems. Extensive numerical results are presented on different classes of problems, and features of each code that make it efficient or inefficient for each class are examined.
ORFE 01-04, Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ 08544, December 2001.
View A Comparative Study of Large-Scale Nonlinear Optimization Algorithms