SNOPT is a widely used large-scale optimizer for difficult large-scale nonlinear problems. It incorporates proven methods that have wide applicability and are especially effective for nonlinear problems whose functions and gradients are expensive to evaluate.

Getting started with SNOPT

SNOPT downloads are available from the My Downloads page of your account at the AMPL Portal, and are included in the bundles that are used for free trials.


Developer: Stanford Systems Optimization Laboratory

Current version: 7.5-1.2

Problem types supported: Linear, quadratic, and smooth nonlinear objectives and constraints in continuous variables.

Algorithms available: Primal simplex for linear problems; sequential quadratic with augmented Lagrangian for nonlinear objectives and constraints.

Special features: Particularly great efficiency is achieved when many variables enter linearly in the constraints, or when many constraints are active (hence there are relatively few degrees of freedom) at an optimum. An elastic constraint formulation is used to deal with infeasibility.

Further Information

Systems Optimization Laboratory website

SNOPT 7 User’s Guide with complete option descriptions