Dear scheduling researcher, We are delighted to announce the talk given by Hyun-Jung Kim (KAIST). The title is "Scheduling with Machine Learning". The seminar will take place on Zoom on Wednesday, March 1 at 14:00 UTC.
Join Zoom Meeting https://cesnet.zoom.us/j/95707763175?pwd=aTdmWDN1RG0ySlk0a1dZWUdUdXZJUT09 Meeting ID: 957 0776 3175 Passcode: 047586
You can follow the seminar online or offline on our Youtube channel as well: https://www.youtube.com/channel/UCUoCNnaAfw5NAntItILFn4A
The abstract follows. Manufacturing companies have recently shown a growing interest in using machine learning to improve scheduling problems. In this talk, we will present three real-life industrial scheduling problems faced by industries with a specific focus on the application of machine learning. First, in semiconductor manufacturing, multiple weighted dispatching rules are used to determine a sequence of jobs. Engineers assign these weights based on their previous experience. We propose a machine learning approach to determine the best weight set for all rules, especially when there is not enough time to derive it. Second, we propose an integration method of machine learning and mathematical formulation for scheduling problems in steel manufacturing. This approach reflects the engineers’ preferences and improves the performance of scheduling at the same time. Finally, we will present a hybrid flow shop scheduling problem for insulation manufacturing where machine learning with the NEH algorithm has been applied. We will also discuss the challenges of implementing machine learning or other heuristic algorithms in practical settings.
The next talk in our series will be: Xiangtong Qi (HKUST) | March 15 | Cooperative Games Models for Scheduling Problems. For more details, please visit https://schedulingseminar.com/
With kind regards
Zdenek, Mike and Guohua