The International Conference on Operations Research, the annual conference of the German Operations Research Society (GOR), looks forward to welcoming you to Bielefeld, Germany.
The OR 2025 is an opportunity for academics, researchers and practitioners to discuss methods and applications of Operations Research, management science, data science and analytics. How can quantitative methods help to find solutions to problems in a closely networked world? This often requires interdisciplinary approaches typical of Operations Research applications.
The conference will take place from September 2-5, 2025 at Bielefeld University. We invite academics, researchers and practitioners from all over the world to participate in this inspiring OR 2025 conference and to submit an abstract and optionally a paper for the proceedings.
You can find the program of the OR here
Our GAMS team will attend with a booth at the venue. Do not miss out to pay us a visit to talk about our recent development.
Authors: Stefan Vigerske and more
In this year, the SCIP Optimization Suite reaches its first double-digit major version number. Starting with an algebraic modeling language, a simplex solver, and a constraint integer programming framework, it has evolved over the last 20+ years into a swiss army knife for anything where relaxations are subdivided, trimmed, generated dynamically, and eventually solved, be it on embedded, ordinary, or super-computers. The newest iteration brings major updates for the presolving library PaPILO, the generic decomposition solver GCG, and the branch-cut-and-price framework SCIP itself. In this talk, we will give a short overview on the current SCIP Optimization Suite ecosystem and catch a glimpse on the new features contributed by over 15 developers in the newest major release.
Stream: Software for Operations Research
Authors: Frederik Fiand, Michael, Bussieck, Hamdi Burak Usul
GAMSPy is a powerful mathematical optimization package which integrates Python’s flexibility with GAMS’s modeling performance. Python features many widely used packages to specify, train, and use machine learning (ML) models like neural networks. GAMSPy bridges the gap between ML and conventional mathematical modeling by providing helper classes for many commonly used neural network layer formulations and activation functions. These allow a compact description of the network architecture that gets automatically reformulated into model expressions for the GAMSPy model.
In this talk, we demonstrate how GAMSPy can seamlessly embed a pretrained neural network into an optimization model. We also explore the utility of GAMSPy’s automated reformulations for neural networks in various applications, such as adversarial input generation, model verification, customized training, and leveraging predictive capabilities within optimization models.
Stream: Software for Operations Research
Authors: Lutz Westermann, Michael Bussieck
Following GAMS’ recent acquisition of CONOPT from ARKI Consulting & Development A/S, this presentation delves into the continuous evolution of this robust nonlinear optimization solver, emphasizing the advancements introduced in the latest release and the strategic implications of the new ownership.
The latest iteration of CONOPT introduces new APIs, e.g, for C++ and Python, opening up new possibilities for a clean, efficient, and robust integration into various software environments and projects requiring nonlinear optimization.
Finally, we will demonstrate the practical application of providing derivatives to CONOPT, an important step that is often necessary to achieve the best possible performance.
Stream: Software for Operations Research
Stay tuned for updates!
