Dear scheduling researcher,
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