A next step in disruption management: combining operations research and complexity science

Mark M. Dekker, Rolf N. Lieshout (), Robin C. Ball, Paul C. Bouman, Stefan C. Dekker, Henk A. Dijkstra, Rob M. P. Goverde, Dennis Huisman, Debabrata Panja, Alfons A. M. Schaafsma and Marjan Akker
Additional contact information
Mark M. Dekker: Utrecht University
Rolf N. Lieshout: Erasmus University Rotterdam
Robin C. Ball: University of Warwick
Paul C. Bouman: Erasmus University Rotterdam
Stefan C. Dekker: Utrecht University
Henk A. Dijkstra: Utrecht University
Rob M. P. Goverde: Delft University of Technology
Dennis Huisman: Erasmus University Rotterdam
Debabrata Panja: Utrecht University
Alfons A. M. Schaafsma: Innovation and Development, ProRail
Marjan Akker: Utrecht University

Public Transport, 2022, vol. 14, issue 1, No 2, 5-26

Abstract: Abstract Railway systems occasionally get into a state of being out-of-control, meaning that barely any train is running, even though the required resources (infrastructure, rolling stock and crew) are available. Because of the large number of affected resources and the absence of detailed, timely and accurate information, currently existing disruption management techniques cannot be applied in out-of-control situations. Most of the contemporary approaches assume that there is only one single disruption with a known duration, that all information about the resources is available, and that all stakeholders in the operations act as expected. Another limitation is the lack of knowledge about why and how disruptions accumulate and whether this process can be predicted. To tackle these problems, we develop a multidisciplinary framework combining techniques from complexity science and operations research, aiming at reducing the impact of these situations and—if possible—avoiding them. The key elements of this framework are (i) the generation of early warning signals for out-of-control situations, (ii) isolating a specific region such that delay stops propagating, and (iii) the application of decentralized decision making, more suited for information-sparse out-of-control situations.

Keywords: Railway disruption management; Rescheduling; Complexity science; Operations research (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.1007/s12469-021-00261-5

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