We are happy to announce that our experienced team will attend the conference and hold a technical tutorial and workshop during the conference. Don’t miss the interesting presentations by Atharv Bhosekar and Steve Dirkse!
Optimization applications combine technology and expertise from many different areas, including model-building, algorithms, and data-handling. Often, the gathering, pre/post-processing, and visualization of the data is done by a diverse organization-spanning group that shares a common bond: their skill in and appreciation for Python and the vast array of available packages it provides. For this reason, GAMS offers multiple ways to integrate with Python on the data-handling side, as well as offering some packages of our own (e.g. GAMS Transfer, GAMS Connect). In this talk, we will explore the benefits of this integration and demonstrate them using a real-world example complete with results on performance.
The General Algebraic Modeling System (GAMS) allows modelers to create optimization-based decision support applications. In this workshop, our first focus will be on model development with GAMS. We will explore what a model entails, how to solve different problem types (linear, mixed-integer, non-linear) using GAMS, as well as how to switch solvers and separate the model code from input data using GDX. Additionally, we will demonstrate how a GAMS model can be integrated and transformed into an effective application. An essential step in this process is ensuring efficient data transfer. To achieve this, we will showcase the use of the embedded code facility, GAMS Transfer API, and tools like GAMS Connect. Lastly, we will introduce the GAMS Engine, a powerful tool for solving GAMS models either on-premises or in the cloud.