Constrained Optimization (CO)

Constrained Optimization minimizes an arbitrary function including linear and nonlinear, equality and inequality constraints on parameters using the Sequential Quadratic Programming method. The descent methods include the Gauss-Newton, BFGS, and DFP methods. Derivatives and Jocobians may be computed numerically, or procedures may be provided by the user. Features:

- Linear and nonlinear constraints on parameters

- Equality and inequality constraints on parameters.

The GAUSS Application - Constrained Optimization is provided in GAUSS source code, allowing the user flexibility to customize and extend it's capabilities.

Greg Mead

Sales Manager