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.

Gill, P. E., Murray, W., and Saunders, M. A. 2002.
SNOPT: An SQP algorithm for large-scale constrained optimization.
SIAM Journal on Optimization12: 979-1006.

Gill, P. E., Murray, W., and Saunders, M. A. 2005.
SNOPT: An SQP algorithm for large-scale constrained optimization.
SIAM Review47: 99-131.

The problem must be specified in a model file. A data file and commands
files may also be provided. If the commands file is specified, it must
contain the AMPL solve command; however, it must not contain
the model or data commands. The model and data
files are renamed internally by NEOS.

The commands file may include option settings for the solver. To specify
solver options, add

Enter the location of the AMPL data file (local file)

Commands File

Enter the location of the AMPL commands file (local file)

Comments

Additional Settings

Dry run: generate job XML instead of submitting it to NEOS
Short Priority: submit to higher priority queue with maximum CPU time
of 5 minutes
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