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

IRIX version compatibility: 6.2

Greg Mead

Sales Manager
Aptech Systems, Inc.
23804 S.E. Kent-Kangley Rd.
Maple Valley, WA 98038
USA
206-432-7855
206-432-7832 (fax)
gregm@aptech.com

For applications in related solution areas, see the following indices: Computer Aided Modeling, Molecular Biology, Physics, Software Development Tools, Statistics & Data Analysis, the developer index for Aptech Systems, Inc. and the product category index for Math, Physics, Other Sciences.