OR 2024
Data, Learning, and Optimization
Welcome to the International Conference on Operations Research, jointly organized by the German Operations Research Society (GOR), the Austrian Society for Operations Research (ÖGOR), and the Swiss Operations Research Society (SVOR/ASRO).
This conference is a place to exchange ideas and interact with other academics, researchers, and practitioners in the fields of Operations Research, Management Science, Data Science, and Analytics. The OR 2024 will take place from September 3-6, 2024 on the downtown campus of the Technical University of Munich.
You can find the program of the OR here
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Our GAMS team will attend with a booth. Do not miss out to pay us a visit to talk about our recent development.
Our team will also have some very interesting talks in Munich:
by Muhammet Abdullah Soyturk, Justine Broihan
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, Frederik Fiand
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.
