|Algorithm||Sparse SQP algorithm with limited-memory quasi-Newton approximations to the Hessian of Lagrangian|
|Input Format||Optional data input from MPS files.
May be called from a driver program, typically in Fortran, C or MATLAB
|Modeling Languages link||GAMS, AMPL, CUTE interface provided|
|Commercial Status||Licensing Contact:
Hans Wiesendanger, Licensing Associate, Stanford University Office of Technology Licensing E-Mail: firstname.lastname@example.org Phone: (650) 723-0692
|Platform||Any machine with a reasonable amount of memory and a Fortran compiler|
|Remarks||SNOPT is a software package for solving large-scale optimization problems (linear and nonlinear programs). It employs a sparse SQP algorithm with limited-memory quasi-Newton approximations to the Hessian of Lagrangian.
SNOPT is especially effective for nonlinear problems whose functions and gradients are expensive to evaluate. The functions should be smooth but need not be convex.
An augmented Lagrangian merit function ensures convergence from an arbitrary point. Infeasible problems are treated methodically via elastic bounds on the nonlinear constraints.
SNOPT allows the nonlinear constraints to be violated (if necessary) and minimizes the sum of such violations.
Numerically stable algorithms. Global convergence. Needs only first derivatives. Warm start capability.
P. E. Gill, W. Murray and M. A. Saunders, SNOPT: An SQP algorithm for large-scale constrained optimization, Report SOL 97-3, Systems Optimization Laboratory, Stanford University (1997). (Same as Report NA 97-2, Dept of Mathematics, University of California, San Diego, 1997).
P. E. Gill, W. Murray and M. A. Saunders, SNOPT 5.3 User's Guide, Report NA 97-5, Dept of Mathematics, University of California, San Diego (revised 1998).