Scheduling seminar

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schedulingseminar@rtime.felk.cvut.cz

April 2026

1 participants
2 discussions

Alena Otto (TU Munich)| April 29 | Overcoming poor data quality: Optimizing validation of precedence relation data
by Zdenek Hanzalek 28 Apr '26

28 Apr '26

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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Bruno Escoffier (LIP6, Sorbonne) | April 15 | Resource Leveling for Scheduling Problems: Some Complexity and Approximation Results
by Zdenek Hanzalek 13 Apr '26

13 Apr '26

Dear scheduling researcher, We are delighted to announce the talk given by Bruno Escoffier (LIP6, Sorbonne). The title is "Resource Leveling for Scheduling Problems: Some Complexity and Approximation Results". The seminar will take place on Zoom on Wednesday, April 15 at 13:00 UTC. Join Zoom Meeting https://cesnet.zoom.us/j/93518304259?pwd=raL1poIlb2JMYLa3rJeU746uORq1Xh.1 Meeting ID: 935 1830 4259 Passcode: 688261 You can follow the seminar online or offline on our Youtube channel as well: https://www.youtube.com/channel/UCUoCNnaAfw5NAntItILFn4A The abstract follows. Scheduling problems usually consider resource constraints as hard constraints. In resource leveling instead, a function of resource use is optimized, typically under a deadline constraint. This is motivated by the fact that, in practice, additional resources (e.g., workforce or machines) can be mobilized in order to meet a deadline, yet at some cost. In this talk we will focus on the following setting: given a (target) resource level, our goal is to schedule the jobs in such a way as to best respect this resource level, that is to say, to exceed it as little as possible. We study classical scheduling problems (with or without precedence constraints, with arbitrary or unit processing times,...) in this setting, providing both positive and negative complexity and approximability results. The next talk in our series will be Alena Otto (TU Munich)| April 29 | Overcoming poor data quality: Optimizing validation of precedence relation data. For more details, please visit https://schedulingseminar.com/ With kind regards Zdenek Hanzalek, Michael Pinedo and Guohua Wan

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