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Passenger railway network protection: A model with variable post-disruption demand service

Starita, Stefano, Scaparra, Maria Paola (2017) Passenger railway network protection: A model with variable post-disruption demand service. Journal of the Operational Research Society, 69 (4). pp. 603-618. ISSN 0160-5682. E-ISSN 1476-9360. (doi:10.1057/s41274-017-0255-y)

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http://dx.doi.org/10.1057/s41274-017-0255-y

Abstract

Protecting transportation infrastructures is critical to avoid loss of life and to guard against economic upheaval. This paper addresses the problem of identifying optimal protection plans for passenger rail transportation networks, given a limited budget. We propose a bi-level protection model which extends and refines the model previously introduced by Scaparra et al, (Railway infrastructure security, Springer, New York, 2015). In our extension, we still measure the impact of rail disruptions in terms of the amount of unserved passenger demand. However, our model captures the post-disruption user behaviour in a more accurate way by assuming that passenger demand for rail services after disruptions varies with the extent of the travel delays. To solve this complex bi-level model, we develop a simulated annealing algorithm. The efficiency of the heuristic is tested on a set of randomly generated instances and compared with the one of a more standard exact decomposition algorithm. To illustrate how the modelling approach might be used in practice to inform protection planning decisions, we present a case study based on the London Underground. The case study also highlights the importance of capturing flow demand adjustments in response to increased travel time in a mathematical model.

Item Type: Article
DOI/Identification number: 10.1057/s41274-017-0255-y
Uncontrolled keywords: Railway networks, disruption, protection, bi-level models, decomposition, simulated annealing
Divisions: Faculties > Social Sciences > Kent Business School > Management Science
Faculties > Social Sciences > Kent Business School > Centre for Logistics and Heuristic Organisation (CLHO)
Depositing User: Maria Paola Scaparra
Date Deposited: 19 May 2017 10:53 UTC
Last Modified: 15 Jul 2019 12:51 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/61788 (The current URI for this page, for reference purposes)
Scaparra, Maria Paola: https://orcid.org/0000-0002-2725-5439
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