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

Mark M. Dekker, Rolf N. van 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, Marjan van den Akker

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)
40 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)5-26
Number of pages22
JournalPublic Transport
Volume14
Issue number1
DOIs
Publication statusPublished - 2021

Keywords

  • Complexity science
  • Operations research
  • Railway disruption management
  • Rescheduling

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