DNOPT (Dense Nonlinear OPTimizer) is a software package for solving constrained optimization problems (nonlinear programs). It employs a dense SQP algorithm and is especially effective for nonlinear problems whose functions and gradients are expensive to evaluate. The functions should be smooth but need not be convex. An augmented Lagrangian merit function ensures convergence from an arbitrary point.
@article{GilSWdnopt,
AUTHOR = {Philip E. Gill, Michael A. Saunders, and Elizabeth Wong},
TITLE = {User's Guide for {DNOPT}: Software for Medium-Scale
Nonlinear Programming},
INSTITUTION = {Center for Computational Mathematics, University of
California, San Diego},
ADDRESS = {La Jolla, CA},
TYPE = {Center for Computational Mathematics Report},
NUMBER = {CCoM 17-3},
YEAR = {2017},
}