The objective of global optimization (GO) is to find the best solution in nonlinear decision models that may have a multitude of global and local optima. GO is an active research area, with a broad range of practical applications in engineering, economics, and the sciences. 

We will provide a concise review of the most important GO model types and solution approaches, and then discuss adaptive partition strategies and stochastic search methods in more detail. Both of these general approaches are globally convergent, can be implemented efficiently, and easily combine with other methods.

We continue with discussing several current implementations of global and convex optimization software. These specifically include the following products:

Modeling tips and numerical examples are also discussed during the 'live' software demonstrations. We will also review a range of practical applications and case studies.

The presentation is offered in an interactive atmosphere: questions, test problems, numerical challenges, and new applications are all welcome. Participants are encouraged to send models and test problems of interest also before the workshop, possibly to include in the discussion. 

Lecture notes and demo software will be provided to attendees, on CD media. Participants are also offered a 20% discount regarding the LGO, LGO IDE, MathOptimizer, and MathOptimizer Professional software products. 

The cost of attendance is $150, and pre-registration by April 1st ($125) is preferred. Registration for this tutorial is available at the SCS Home Page in concert with the ASTC'04.

Sponsored by The Society for Modeling and Simulation International
P.O. Box 17900
San Diego, California 92177
Phone 858-277-3888
Fax 858-277-3930
E-mail scs@scs.org

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