Digitalizing the Determination of Railway Infrastructure Intervention Programs: A Network Optimization Model
dc.contributor.author
Burkhalter, Marcel
dc.contributor.author
Adey, Bryan T.
dc.date.accessioned
2022-04-22T15:05:38Z
dc.date.available
2022-04-14T02:56:17Z
dc.date.available
2022-04-22T15:05:38Z
dc.date.issued
2022-06
dc.identifier.issn
1076-0342
dc.identifier.issn
1943-555X
dc.identifier.other
10.1061/(ASCE)IS.1943-555X.0000681
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/542356
dc.identifier.doi
10.3929/ethz-b-000542356
dc.description.abstract
One area of railway infrastructure management that can benefit greatly from digitalization is the determination of optimal intervention programs, i.e., when, where, and which type of interventions are to be executed. The potential benefit is considerable because of the large variety of assets required for the infrastructure to function as intended, the interconnectedness of the assets, the extensive number of different types of possible interventions, and the wide range of service measures to consider when deciding between different intervention programs - all of which are difficult, if not impossible, to consider qualitatively. In this paper, a network flow optimization model is presented that determines the optimal intervention program considering different types of assets, interventions and service measures to execute the interventions, the dependencies between interventions, and the relation between interventions and service in the short and long term. The model is developed and used to determine the intervention program that maximizes the net benefit for a 17-km railway line over a 12-year planning period, divided into three four-year blocks. The example demonstrates that the model can be used to determine optimal intervention programs on real-world railway networks, taking into consideration the intervention costs and relevant measures of service, the interrelationships between the different assets, and multiple time periods. It also demonstrates that the model is a powerful management tool for leveraging the digitalization of railway infrastructure.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
American Society of Civil Engineers
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Railway network
en_US
dc.subject
Optimization
en_US
dc.subject
Maintenance
en_US
dc.subject
Intervention program
en_US
dc.title
Digitalizing the Determination of Railway Infrastructure Intervention Programs: A Network Optimization Model
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2022-03-24
ethz.journal.title
Journal of Infrastructure Systems
ethz.journal.volume
28
en_US
ethz.journal.issue
2
en_US
ethz.journal.abbreviated
J. Infrastruct. Syst.
ethz.pages.start
04022012
en_US
ethz.size
15 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.grant
Future proofing strategies FOr RESilient transport networks against Ectreme Events
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
New York, NY
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02604 - Inst. für Bau- & Infrastrukturmanagement / Inst. Construction&Infrastructure Manag.::03859 - Adey, Bryan T. / Adey, Bryan T.
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG
*
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02604 - Inst. für Bau- & Infrastrukturmanagement / Inst. Construction&Infrastructure Manag.::03859 - Adey, Bryan T. / Adey, Bryan T.
ethz.grant.agreementno
769373
ethz.grant.fundername
EC
ethz.grant.funderDoi
10.13039/501100000780
ethz.grant.program
H2020
ethz.date.deposited
2022-04-14T02:56:23Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2022-04-22T15:05:56Z
ethz.rosetta.lastUpdated
2023-02-07T00:55:34Z
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true
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true
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