Here at GAMS we are proud to work closely with our customers and help them solve their problems. Below you will find a selection of case studies that demonstrate the diverse application areas of mathematical optimization with GAMS.
To support their carbon neutrality ambitions, the global energy company TotalEnergies developed a complex optimization model for Carbon Capture and Storage (CCS). This highly sophisticated model, capable of managing the complex CO2 logistics, struggled with slow runtimes and complex code that limited its practical use. GAMS Consulting stepped in to streamline the model, reducing simulation runtimes from hours to minutes and enabling long-term scenario analysis. Also, we developed a user-friendly Python and Excel interface that allowed engineers to run and analyze the model without the need for deep programming expertise. This collaboration has transformed the model into a robust decision-support tool, helping TotalEnergies scale up CCS projects for a net-zero future.
Problem Type: MINLP Industry: Energy
The Austrian Power Grid (APG) partnered with our consulting team to optimize its electricity transmission model. As a result, model-solving time was slashed by over 60%, memory usage dropped by 80%, and various infeasibilities were resolved—ensuring APG’s model is now more stable, efficient, and fully capable of executing their energy strategy with enhanced reliability and optimal performance.
Problem Type: LP Industry: Energy
Alpro, a European leader in plant-based food products, faced the challenge of optimizing its factory’s energy management. With the help of our consulting team, the company implemented two custom models and a graphical user interface, streamlining its operational pipeline from data gathering to daily energy trading and consumption.
Problem Type: MIP Industry: Energy
Rhodium Group is a renowned research organization specializing in comprehensive analysis of global trends. With a strong focus on energy, climate, and economic issues, they provide critical insights that inform decision-making at the highest levels. Tasked with delivering a detailed climate outlook ahead of the COP28 summit in Dubai, and then again ahead of COP29 in Azerbaijan, Rhodium Group aimed to account for the numerous uncertainties that could influence future climate trajectories. Their approach involved leveraging advanced modeling techniques and robust computational resources to generate reliable projections.
Problem Type: Large-scale Monte Carlo Industry: Climate Modeling, Policy
The EIP Energy Investment Planner© optimizes energy supply and demand networks and helps in evaluating investment decisions with an interactive web-based user interface
Problem Type: LP/MIP Industry: Energy
Global Dairy Trade trading event auctions are the leading global online marketplace for trading large volume dairy ingredients and for reference price discovery. The GDT Trading Events and GDT Pulse Auctions are powered by CRA’s Trading System for Efficient Markets (TSEM™) platform and rely on a series of GAMS models.
Problem Type: LP / QP Industry: Agriculture, Dairy
VIOOH is a leading global digital out of home (OOH) marketplace. Launched in 2018 and with headquarters in London, VIOOH’s platform connects buyers and sellers in a premium marketplace, making OOH easily accessible.
Problem Type: MILP Industry: Out-Of-Home-Advertising
The ICCT asked GAMS to develop, test. and run a partial equilibrium model of the transportation sector in the EU. Renewable fuel policy is complex, and the impacts of policy changes are not always intuitive. Quantitative modeling, as demonstrated here, can be a useful tool in objectively analyzing a broad set of effects from changes in guidelines, and allows policy makers to make informed decisions.
Problem Type: MCP Industry: Economic Modeling and Policy
Stadtwerke München have recently lifted their computationally expensive GAMS model into the cloud. This white paper gives a high level overview of the techniques used and the benefits of a cloud deployment over a traditional on-premise solution.
Problem Type: LP Industry: Energy Market
As a medium sized fashion producer and retailer, Goertz regularly faces the challenge of how to redistribute stock across 150 retail stores. A newly developed solution with a GAMS model at its core helps Goertz to intelligently redistribute stock multiple times during the sales season. With the new solution, Goertz has been able to increase stock availability and at the same time shave off an average of seven days of each redistribution cycle.
Problem Type: MIP Industry: Fashion Retail