A Recap of GOR Annual Meeting 2024 in Munich
The annual conference of the Society for Operations Research (GOR e.V.) was held in Munich from September 3-6, 2024, and hosted by the Technical University of Munich. This year’s theme: “Data, Learning, and Optimization,” brought together experts from all around the world to explore the latest advancements in operations research.
GAMS sent a large team this year, eager to connect with colleagues, exchange new ideas, and dive into the conference’s wide range of topics. On the technical side, our team gave three presentations and got to engage in many thought-provoking discussions with colleagues, field experts, and GAMS users. Outside the sessions, the conference social program offered a great opportunity to network in a more informal setting. Highlights included the Bavarian reception at the Augustiner Bräustuben and the conference dinner.
Team Presentations
We are excited to share the abstracts and presentations from our team’s talks, each offering unique perspectives on GAMSPy, artificial intelligence, and decision support as well as analytics.
- Presentation 1 - GAMSPy - Where Convenience of Python Meets GAMS’ Performance by Muhammet Abdullah Soyturk
- Presentation 2 - The Lifecycle of OR Solutions: From Rapid Prototypes to Market Deployment by Justine Broihan
- Presentation 3 - Integrating Machine Learning with GAMSPy by Hamdi Burak Usul
Each of our presentations reflected our team’s commitment to addressing the most pressing challenges and new solutions in the field. We were proud of contributing to the conversation and sharing our work with a forward-thinking audience.
A Big Thank You!
We would like to extend our heartfelt thanks to the organizers, speakers, and participants who made this year’s GOR meeting a memorable experience. It’s always a pleasure to be part of such a well-organized event that promotes collaboration, learning, and innovation.
The GOR conference continues to be a significant event in the operations research community, and we are already looking forward to next year’s gathering. Until then, let’s keep the spirit of collaboration alive and continue working towards impactful solutions. See you next year!
The abstracts:
GAMSPy - Where Convenience of Python Meets GAMS’ Performance
by Muhammet Abdullah Soyturk
OptimIzation pipelines contain many tasks such as mathematical modeling, data processing, and developing algorithms. Python and its vast array of packages provide a convenient way of data gathering, pre/post-processing of the data, the visualization of the data and developing necessary algorithms by utilizing existing ones. On the other hand, GAMS has been providing tools with great performance for the mathematical modeling part for decades. In this talk, we will talk about a new tool GAMSPy that aims to combine the best of both worlds.
The Lifecycle of OR Solutions: From Rapid Prototypes to Market Deployment
by Justine Broihan
This presentation delves into the transformative process of turning rapid prototypes into market-ready operations research (OR) applications, drawing from a variety of real-world projects. We focus on the methodical transition of prototypes to fully developed solutions, addressing recurring challenges and strategic solutions along the way. We will explore two main areas: implementing effective OR solutions that meet dynamic market needs, and extracting insights crucial for our product development. This approach shapes a toolkit that is robust and adaptable to evolving technologies. A significant part of our discussion will highlight the importance of rapid prototyping. This agile phase fosters informed discussions with clients, the end-users, guiding the refinement of prototypes to better meet their needs and expectations. Furthermore, transitioning from a prototype to a mature OR application is a comprehensive development process. It includes enhancing user interfaces, optimizing deployment strategies (like GUI and cloud computing), and ensuring superior computational performance. By sharing our experiences and best practices, this talk aims to provide participants with strategies to overcome common obstacles in OR project development. Attendees will gain a deeper understanding of how to effectively move from conceptual prototypes to advanced, market-ready applications, aligning with user needs and achieving operational efficiencies.
Integrating Machine Learning with GAMSPy
by Hamdi Burak Usul
GAMSPy seamlessly combines Python’s flexibility with the modeling prowess of GAMS. This combination offers promising avenues particularly in merging the realms of machine learning (ML) and mathematical modeling. While GAMS is proficient in indexed algebra, ML predominantly relies on matrix operations. To facilitate ML applications, our research focuses on incorporating commonly used ML operations into GAMSPy. In our presentation, we illustrate the practical implications by demonstrating the generation of adversarial images for an optical character recognition network using GAMSPy. We demonstrate the adaptability of GAMSPy and its potential utility in ML research and development endeavors. Furthermore, we explore future directions, including planned OMLT integration, highlight distinctions between GAMSPy’s approach and existing alternatives.
Check our presentation slides for more information:
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