Dear scheduling researcher, We are delighted to announce the talk given by Changhyun Kwon (KAIST/Omelet, Inc.). The title is " Learning-Based Approaches to Combinatorial Optimization in Transportation ". The seminar will take place on Zoom on Wednesday, October 15 at 13:00 UTC. Join Zoom Meeting https://cesnet.zoom.us/j/96320878964?pwd=0IzVyJYar5VdTRAJIYtRHU8qxkSNes.1 Meeting ID: 963 2087 8964 Passcode: 883125 You can follow the seminar online or offline on our Youtube channel as well: https://www.youtube.com/channel/UCUoCNnaAfw5NAntItILFn4A The abstract follows. Combinatorial optimization problems arising in transportation are often NP-hard, making them computationally challenging to solve at scale. Recent advances in machine learning have opened new avenues for tackling such problems, either as standalone solution strategies or by enhancing traditional optimization algorithms. This talk surveys a spectrum of learning-based approaches for transportation optimization, including: (i) end-to-end learning models, (ii) integration within exact algorithms, (iii) learning to guide local search, (iv) accelerating metaheuristics, (v) embedding within optimization formulations, and (vi) test-time search strategies. This talk will discuss the principles behind each approach, highlight representative applications, and reflect on both their current potential and open challenges for the future of transportation optimization. The next talk in our series will be: Zijie Zhou (IEDA, HKUST) | October 29 | Efficient and Robust Large Language Model (LLM) Inference Scheduling Optimization For more details, please visit https://schedulingseminar.com/ With kind regards Zdenek Hanzalek, Michael Pinedo and Guohua Wan -- Zdenek Hanzalek Industrial Informatics Department, Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Jugoslavskych partyzanu 1580/3, 160 00 Prague 6, Czech Republic https://rtime.ciirc.cvut.cz/~hanzalek/