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# A Julia implementation of Algorithm NCL for constrained optimization

## Ding Ma, Dominique Orban, and Michael A. Saunders

BibTeX reference
Algorithm NCL is designed for general smooth optimization problems
where first and second derivatives are available,
including problems whose constraints may not be linearly independent at
a solution (i.e., do not satisfy the LICQ).
It is equivalent to the LANCELOT augmented Lagrangian method,
reformulated as a short sequence of nonlinearly constrained
subproblems that can be solved efficiently by IPOPT and KNITRO, with
warm starts on each subproblem.  We give numerical results
from a Julia implementation of Algorithm NCL on tax policy models that do not satisfy the LICQ, and on nonlinear least-squares problems and general problems from the CUTEst test set.


, 19 pages

### Document

G2102.pdf (700 KB)