[Scheduling seminar] Alena Otto (TU Munich)| April 29 | Overcoming poor data quality: Optimizing validation of precedence relation data

Dear scheduling researcher,

We are delighted to announce the talk given by Alena Otto (TU Munich). 
The title is "Overcoming poor data quality: Optimizing validation of 
precedence relation data". The seminar will take place on Zoom on 
Wednesday, April 29 at 13:00 UTC.
Join Zoom Meeting
https://cesnet.zoom.us/j/99150961586?pwd=krrlAFGtfNcaBkrZxMxv6ITtwggNkN.1
Meeting ID: 991 5096 1586
Passcode: 856123

You can follow the seminar online or offline on our Youtube channel as 
well:
https://www.youtube.com/channel/UCUoCNnaAfw5NAntItILFn4A

The abstract follows.
This talk centers around the problem of insufficient data quality on 
precedence relations between tasks, which is relevant, for instance, in 
project scheduling and assembly line balancing. Inaccurate data on 
unnecessary precedence relations cannot be used, otherwise the 
recommendations of decision support systems may turn infeasible. So, 
unnecessary relations must be satisfied, diminishing the baseline 
problem’s solution space and the business result. Experts can validate 
the data, but their time is limited. We apply an optimization lens and 
formulate the data validation problem (DVP). Restricted by the available 
time budget, an expert dynamically receives queries about specific data 
entries and corrects or validates them. The DVP searches for an 
interview policy that states queries to the expert, each using up some 
of the time budget, in a way that maximizes the (weighted) number of 
removed precedence relations. We model the DVP as a dynamic program, 
derive optimal policies for several important special cases and design a 
heuristic interview policy LSTD. In a case study of an automobile 
manufacturer, this policy substantially reduces the stations’ idle time 
after selectively addressing about 8% of the data entries. We prove 
theoretically and numerically that data validation by experts can lead 
to significant savings. The number of queries required to validate the 
data exhaustively is much less than naive estimates. Additionally, the 
probability to remove an unnecessary precedence relation per query in a 
series of queries is high, even for simple interview policies.

The next talk in our series will be
Debiao Li (Fuzhou University) | May 13 | Feature-driven Robust 
Stochastic Scheduling for Printed Circuit Board Assembly.
For more details, please visit https://schedulingseminar.com/

With kind regards

Zdenek Hanzalek, Michael Pinedo and Guohua Wan

-- 
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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