SNOPT

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

• Gill, P. E., Murray, W., and Saunders, M. A. 2002. SNOPT: An SQP algorithm for large-scale constrained optimization. SIAM Journal on Optimization 12: 979-1006.
• Gill, P. E., Murray, W., and Saunders, M. A. 2005. SNOPT: An SQP algorithm for large-scale constrained optimization. SIAM Review 47: 99-131.

Using the NEOS Server for SNOPT/AMPL

The user must submit a model in AMPL format. Examples are provided in the examples section of the AMPL website.

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

  option snopt_options 'OPTIONS';