Modeling and Optimization with GAMS (advanced)

with Josef Kallrath (University of Florida, Gainesville, FL)

This two-days course helps the mathematically inclined participants to learn advanced techniques for better using GAMS to model and solve larger or complicated optimization problems, especially, mixed integer optimization problems. The participants will increase their knowledge on using GAMS efficiently and will learn more about procedural and modular language features, background on the solvers embedded in GAMS, how to interface to systems outside GAMS and how to use and create Function Libraries. The course assumes the participants to have some basic knowledge on GAMS and familiarity with the GAMS-IDE or GAMS Studio. For the mathematical part of this course, it is beneficial for participants to have a decent mathematical background.

The participants will learn more about the MILP, NLP and MINLP solvers as well as on global optimization techniques. We stress that difficult and large optimization problems require a tight connection between modeling and algorithms aspects. This leads to sequence of models, nested solve statements, and decomposition techniques – detailed examples will be discussed. An important aspect of the course is the development of industrial applications software. The course will provide tricks-of-the-trade not covered by the GAMS documentation or other public sources.

As a new addition to the course: we will be looking at how ChatGPT/CoPilot could be used for the generation or analysis of GAMS code.

The course offers ample opportunity for discussion and analysis of participants’ own problems, in addition to the presentation, examples, and hands-on activities.

Early-registration discount until Sep 27, 2024

More information and registration