The NEOS Server offers SNOPT for the solution of nonlinearly constrained optimization problems. Problems can be submitted to SNOPT on the NEOS server in AMPL or GAMS format.
SNOPT is a solver for nonlinearly constrained optimization problems; it is suitable for large-scale linear and quadratic programming, for linearly constrained optimization and for general nonlinear programs. SNOPT finds solutions that are locally optimal. SNOPT implements a sequential quadratic programming (SQP) algorithm. Search directions are obtained from quadratic programming subproblems that minimize a quadratic model of the Lagrangian function subject to linearized constraints. An augmented Lagrangian merit function is reduced along each search direction to ensure convergence from any starting point. SNOPT is especially effective for nonlinear programs whose functions and gradients are expensive to evaluate. The functions should be smooth but do not need to be convex.
SNOPT was developed by Philip E. Gill, Walter Murray, and Michael Saunders. Additional information on SNOPT can be found in the User's Guide for SNOPT Version 7. References
The user must submit a model in NL format. The NEOS Server will automatically handle an NL model in either binary or text format. NL files in either format can additionally be zipped, gzipped, or tarred prior to submission if desired.
An options file can optionally be specified. Please note that certain options may be restricted, altered, or removed by the NEOS server prior to solving. For example, users are limited to a max of four solver threads -- requests for more threads in the options file will not be honored.