We are delighted to announce the talk given by Patrick De Causmaecker
(KU Leuven).
The title is "Data Science Meets Scheduling".
The seminar will take place on Zoom on Wednesday, May 11 at 13:00 UTC.
Join Zoom Meeting
https://cesnet.zoom.us/j/99017304143?pwd=N2VaLzlWT2FWTlFaamNQWkV1N2UrZz09
Meeting ID: 990 1730 4143
Passcode: 922592
You can follow the seminar online or offline on our Youtube channel as well:
https://www.youtube.com/channel/UCUoCNnaAfw5NAntItILFn4A
The abstract follows.
The impact of techniques from data science and machine learning on
scheduling is investigated. We review a number of recently emerged
applications of these techniques that can shed a new light on
combinatorial optimization in general. We give concrete examples for
scheduling in particular. We distinguish on-line techniques, that is,
data science techniques integrated into advanced algorithms, off-line
techniques which can be used to improve, select of construct algorithms
as well as techniques that consider the problem as living in a space of
which the dimensions are set by specific properties of its instances. We
give examples of recent results obtained for specific problems in the
scheduling domain. Meeting works in two directions. We give an example
where a recent theoretical result for a combinatorial optimization
problem provides new insights in the structures on which the data
science techniques can operate. In this case, the theoretical result
allowed to locate a region of hard problem instances in the instance space.
The next talk in our series will be given by:
Stanislaw Gawiejnowicz (AMU Poznañ) | May 25 | Past, present and future
of time-dependent scheduling
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/
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