Template-Type: ReDIF-Paper 1.0
Author-Name: Dekker, M.M.
Author-Name-Last: Dekker
Author-Name-First: Mark
Author-Name: van Lieshout, R.N.
Author-Name-Last: van Lieshout
Author-Name-First: Rolf
Author-Name: Ball, R.C.
Author-Name-Last: Ball
Author-Name-First: Robin
Author-Name: Bouman, P.C.
Author-Name-Last: Bouman
Author-Name-First: Paul
Author-Name: Dekker, S.C.
Author-Name-Last: Dekker
Author-Name-First: Stefan
Author-Name: Dijkstra, H.A.
Author-Name-Last: Dijkstra
Author-Name-First: Henk
Author-Name: Goverde, R.M.P.
Author-Name-Last: Goverde
Author-Name-First: Rob
Author-Name: Huisman, D.
Author-Name-Last: Huisman
Author-Name-First: Dennis
Author-Person: phu27
Author-Name: Panja, D.
Author-Name-Last: Panja
Author-Name-First: Deb
Author-Name: Schaafsma, A.M.
Author-Name-Last: Schaafsma
Author-Name-First: Alfons
Author-Name: van den Akker, M.
Author-Name-Last: van den Akker
Author-Name-First: Marjan
Title: A Next Step in Disruption Management: Combining Operations Research and Complexity Science
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.
Length: 19
Creation-Date: 2018-06-25
File-URL: https://repub.eur.nl/pub/109054/EI2018-25.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI2018-25
Handle: RePEc:ems:eureir:109054