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A Next Step in Disruption Management: Combining Operations Research and Complexity Science

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  • Dekker, M.M.
  • van Lieshout, R.N.
  • Ball, R.C.
  • Bouman, P.C.
  • Dekker, S.C.
  • Dijkstra, H.A.
  • Goverde, R.M.P.
  • Huisman, D.
  • Panja, D.
  • Schaafsma, A.M.
  • van den Akker, M.

Abstract

Railway systems occasionally get into a state of out-of-control, meaning that there is barely any train is running, even though the required resources (infrastructure, rolling stock and crew) are available. These situations can either be caused by large disruptions or unexpected propagation and accumulation of delays. Because of the large number of aected resources and the absence of detailed, timely and accurate information, currently existing methods 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 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 using tools from complexity science and (ii) a set of rescheduling measures robust against the features of out-of-control situations, using tools from operations research.

Suggested Citation

  • Dekker, M.M. & van Lieshout, R.N. & Ball, R.C. & Bouman, P.C. & Dekker, S.C. & Dijkstra, H.A. & Goverde, R.M.P. & Huisman, D. & Panja, D. & Schaafsma, A.M. & van den Akker, M., 2018. "A Next Step in Disruption Management: Combining Operations Research and Complexity Science," Econometric Institute Research Papers EI2018-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:109054
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    References listed on IDEAS

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    Cited by:

    1. van Lieshout, R.N. & Bouman, P.C. & van den Akker, M. & Huisman, D., 2020. "A Self-Organizing Policy for Vehicle Dispatching in Public Transit Systems with Multiple Lines," Econometric Institute Research Papers EI2020-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. van Lieshout, R.N. & Bouman, P.C. & Huisman, D., 2018. "Determining and Evaluating Alternative Line Plans in (Near) Out-of-Control Situations," Econometric Institute Research Papers EI2018-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Tang, Junqing & Xu, Lei & Luo, Chunling & Ng, Tsan Sheng Adam, 2021. "Multi-disruption resilience assessment of rail transit systems with optimized commuter flows," Reliability Engineering and System Safety, Elsevier, vol. 214(C).

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