The NEOS Server offers SNOPT for the solution of nonlinearly
constrained optimization problems in
SNOPT is suitable for large nonlinearly constrained problems
with a modest number of degrees of freedom.
SNOPT implements a sequential programming algorithm that
uses a smooth augmented Lagrangian merit function and
makes explicit provision for infeasibility in the original
problem and in the quadratic programming subproblems.
Additional information on SNOPT can be found in the
User's Guide for SNOPT (Version 5.3)
SNOPT was developed by
Philip E. Gill,
Using the NEOS Server for SNOPT
The user must submit a model in
format to solve a nonlinearly constrained optimization problem.
Examples of models in AMPL format can be found in the
The model is specified by a model file, and optionally,
a data file and a commands file.
If the command file is specified it must contain
the AMPL solve command.
The commands file can contain any AMPL command
options for SNOPT
with, for example,
option snopt_options "timing=3 outlev=2";
Printing directed to standard out is returned
to the user with the output.
Enter the location of the ampl model (local file)
Enter the location of the ampl data file (local file)
Enter the location of the ampl commands file (local file)
Dry run: generate job XML instead of submitting it to NEOS
Please do not click the 'Submit to NEOS' button more than once.