MINOS is an established choice for both linear and nonlinear optimization problems. It incorporates proven methods for large-scale sparse nonlinear constraints, and its methods are especially effective for nonlinear objectives subject to linear and near-linear constraints.
MINOS 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: 5.51
Problem types supported: Linear, quadratic, and smooth nonlinear objectives and constraints in continuous variables.
Algorithms available: Primal simplex for linear problems; reduced gradient for nonlinear objectives; projected augmented Lagrangian for nonlinear constraints.
Special features: Linear constraints are handled separately from nonlinear ones, for greater efficiency.
Systems Optimization Laboratory website
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