Providing rail-replacement bus services is a common strategy applied to handle track blockage situations in railway networks. Previously, a great deal of research has focused on modelling this strategy, particularly in the case of unplanned disruptions. However, little attention has been paid to planned disruptions where passengers know the situation in advance and the duration of the disruption is significantly longer. In this study, the authors propose a model that can be used to investigate the optimal solution of implementing a replacement bus service to minimise the impact of infrastructure possessions. The model is developed based on a discrete-event simulation technique and uses a genetic algorithm to minimise passenger delays and the cost of operations. The interaction between trains and buses is taken into account. Thus, the passenger flow within the network can be simulated in microscopic detail. Finally, an application of the proposed model is presented using the Liverpool railway network in the UK.
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16 September 2020
Research Article|
July 19 2019
Optimising rail-replacement bus services during infrastructure possessions Available to Purchase
Ratthaphong Meesit, BEng, MEng, MSc
;
Resilience Engineering Research Group, Faculty of Engineering, University of Nottingham, Nottingham, UK
(corresponding author: ratthaphong.m@gmail.com)
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John Andrews, BSc, PhD, MIMA, CMath, MSaRS, FIMechE, CEng
John Andrews, BSc, PhD, MIMA, CMath, MSaRS, FIMechE, CEng
Professor, Infrastructure Asset Management; Director
Resilience Engineering Research Group, Faculty of Engineering, University of Nottingham, Nottingham, UK
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(corresponding author: ratthaphong.m@gmail.com)
Publisher: Emerald Publishing
Received:
October 21 2018
Accepted:
July 02 2019
Online ISSN: 2053-0250
Print ISSN: 2053-0242
ICE Publishing: All rights reserved
2020
Infrastructure Asset Management (2020) 7 (3): 221–238.
Article history
Received:
October 21 2018
Accepted:
July 02 2019
Citation
Meesit R, Andrews J (2020), "Optimising rail-replacement bus services during infrastructure possessions". Infrastructure Asset Management, Vol. 7 No. 3 pp. 221–238, doi: https://doi.org/10.1680/jinam.18.00042
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