Arrive in Time by Train with High Probability

Mohammad Hossein Keyhani (), Mathias Schnee () and Karsten Weihe ()
Additional contact information
Mohammad Hossein Keyhani: Technische Universität Darmstadt, 64289 Darmstadt, Germany
Mathias Schnee: Technische Universität Darmstadt, 64289 Darmstadt, Germany
Karsten Weihe: Technische Universität Darmstadt, 64289 Darmstadt, Germany

Transportation Science, 2017, vol. 51, issue 4, 1122-1137

Abstract: Very often, a train passenger must meet a deadline at the destination, for example, to catch a plane or to arrive at an important meeting on time. Train delays and broken connections let the passenger arrive later than scheduled. Events of this kind are usually not foreseeable before the journey commences. To be on the safe side, a connection should be prebooked such that, in case the connection breaks anywhere, alternative continuations guarantee arrival prior to the deadline with acceptably high probability. For busy people, the challenge is to commence the journey as late as possible, provided the risk of failing to meet the deadline is negligible. This scenario translates into the problem to find the latest connection plus alternative continuations such that the probability of meeting the deadline is not lower than a given required probability of success (close to 100%). We present a dynamic-programming approach to this optimization problem and report on an empirical study based on comprehensive real-world data from Deutsche Bahn AG, the German national railways company. Our algorithm efficiently computes optimal results.

Keywords: stochastic networks; reliable train connections; probability of success (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://doi.org/10.1287/trsc.2017.0758 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:51:y:2017:i:4:p:1122-1137

Access Statistics for this article

More articles in Transportation Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().