Robust Tactical Crew Scheduling Under Uncertain Demand

Christian Rählmann (), Felix Wagener () and Ulrich W. Thonemann ()
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Christian Rählmann: University of Cologne, D-50923 Cologne, Germany
Felix Wagener: University of Cologne, D-50923 Cologne, Germany
Ulrich W. Thonemann: University of Cologne, D-50923 Cologne, Germany

Transportation Science, 2021, vol. 55, issue 6, 1392-1410

Abstract: We analyze a tactical freight railway crew scheduling problem, when train drivers must be informed several weeks before operations about the start and end times and locations of their duties. Between informing the train drivers and start of operations, trip demand changes due to cancellations, new bookings, and reroutings of trains, which might result in mismatches between train driver capacity at a location and demand. We analyze an approach that incorporates uncertain trip demand as scenarios, such that the start and end times and locations of the duties of a crew schedule are recoverable robust against deviations in trip demand. We develop a column generation solution method that dynamically aggregates trips to duties and decomposes the subproblems into smaller, computationally tractable instances. Our model determines duty frames that cover duties in many scenarios, creating recoverable robust crew schedules. We test our model on three real data sets of a major European freight railway operator. Our results show that our schedules are considerably more recoverable robust than those of the nominal solution, resulting in smaller mismatches between train driver capacity and demand.

Keywords: railway crew planning; column generation; recoverable robustness (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:55:y:2021:i:6:p:1392-1410

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