GAMS at the OR2022 in Karlsruhe

Scalable Optimization in the Cloud with GAMS and GAMS Engine

• by Stefan Mann, Frederik Proske and Michael Bussieck

The common type of infrastructure to run GAMS models on for most users was and is their laptops or local workstations. This approach works, but has some limitations, which become more apparent as model sizes increase, or the number of model users increases. To overcome the lack of scalability of local computers, many users have begun to implement their own cloud based solutions around GAMS, but this requires a substantial investment in time and resources to implement.

To fill this gap we have recently developed a Kubernetes based, scalable and cloud native solution to solve GAMS models, which we call GAMS Engine. Engine scales both horizontally (many parallel instances), and vertically (instances can grow to TB of memory and 100s of CPUs). Engine also includes a job scheduler, quota and permission management.

In this presentation we will describe how we implemented the solution and how it is different from more traditional uses of Kubernetes. We will also talk about how GAMS Engine enables customers to fully automate their business optimization processes with little development effort.

Model Deployment in GAMS

• by Robin Schuchmann

In most cases, using GAMS in the typical fashion - i.e. defining and solving models and evaluating the results within the given interfaces is a sufficient way to deploy optimization models. The underlying field of mathematical optimization, in which the focus is not so much on visualization as on the problem structure itself, has remained a kind of niche market to this day. In the large and very extensive segment of business analytics, however, intuitive deployment and visualization is indispensable. Since these two areas increasingly overlap, the way optimization software is used has also changed significantly. Whereas applications used to be invoked via the command line on a local computer, today many users want to log into an online service and perform their optimization on a centralized compute resource. In this talk, reallife examples are used to show what modern software solutions with GAMS can look like. We present how to turn a GAMS model into an interactive web application in just a few steps. In addition, the generation, organization, and sensitivity analysis of multiple scenarios of an optimization model is addressed. We demonstrate how a model written in GAMS can be deployed with this application on either a local machine or a remote server. While data manipulation and visualization as well as scenario management can be done via the web interface, the model itself is not changed. Therefore, the Operations Research analyst can keep focusing on the optimization problem while end users have a powerful tool to work with the data in a structured way and interactively explore the results.

Research & Development Activities at GAMS

• by Frederik Fiand and Michael Bussieck

GAMS has been providing its users with cutting edge optimization technology for several decades. To this end, it is necessary to keep a constant eye on new promising technologies and developments. In recent years, GAMS has therefore increasingly participated in multidisciplinary research projects that bring together specialists from areas such as mathematical optimization, high-performance computing, machine learning, visualization and quantum computing. The application areas are also diverse and address relevant challenges of our time, such as logistic planning problems or energy system analysis, a very active research area in which numerous scientists are developing sustainable solutions for tomorrow’s energy systems. This presentation gives an overview of various recent research projects with GAMS participation. We give insights how projects funded by the Federal Ministry for Economic Affairs and Climate Action such as BEAM-ME, UNSEEN, and ProvideQ, the research campus MODAL funded by the Federal Ministry for Education and Research, or our cooperation with the Energy Technology Systems Analysis Program (ETSAP) of the International Energy Agency (IEA) led to concrete developments giving our project partners access to pioneering technologies through GAMS.