Ender Ozcan (Uni of Nottingham) | Jun 12 | Machine Learning meets Selection Hyper-heuristics
Dear scheduling researcher, We are delighted to announce the talk given by Ender Ozcan (Uni of Nottingham). The title is "Machine Learning meets Selection Hyper-heuristics". The seminar will take place on Zoom on Wednesday, June 12 at 13:00 UTC. Join Zoom Meeting https://cesnet.zoom.us/j/91588200395?pwd=sySE3R77BKsPZfaOOQ8O7EyeuhfLT3.1 Meeting ID: 915 8820 0395 Passcode: 557258 You can follow the seminar online or offline on our Youtube channel as well: https://www.youtube.com/channel/UCUoCNnaAfw5NAntItILFn4A The abstract follows. Hyper-heuristics are powerful search methodologies that operate on low level heuristics or heuristic components to tackle computationally hard optimisation problems. The current state-of-the-art in hyper-heuristic research contains classes of algorithms that focus on intelligently selecting or generating a suitable heuristic for a given situation. Hence, there are two main types of hyper-heuristics: selection and generation hyper-heuristics. A typical selection hyper-heuristic chooses a low-level heuristic and applies it to the current solution at each step of a search, before deciding whether to accept or reject the newly created solution. Generation hyper-heuristics, in contrast, automatically build heuristics or heuristic components during the search process. Machine learning is revolutionising various fields, and its integration with hyper-heuristics holds immense potential. This talk will first offer a concise overview of hyper-heuristics, followed by illustrative case studies demonstrating how we have successfully applied machine learning to automatically design more effective selection hyper-heuristics. The next talk in our series will be: For more details, please visit https://schedulingseminar.com/ With kind regards Zdenek, Mike and Guohua -- 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/
participants (1)
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Zdeněk Hanzálek