Monday, February 27, 2023

[DMANET] [Scheduling seminar] Hyun-Jung Kim (KAIST) | March 1 | Scheduling with Machine Learning

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
Meeting ID: 957 0776 3175
Passcode: 047586

You can follow the seminar online or offline on our Youtube channel as well:

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

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

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