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Article: Train schedule optimization based on schedule-based stochastic passenger assignment

TitleTrain schedule optimization based on schedule-based stochastic passenger assignment
Authors
KeywordsMixed itinerary-size weibit model
Schedule-based
Train scheduling
Issue Date2020
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description
Citation
Transportation Research Part E: Logistics and Transportation Review, 2020, v. 136, p. article no. 101882 How to Cite?
AbstractIn this study, we propose a new schedule-based itinerary-choice model, the mixed itinerary-size weibit model, to address the independently and identically distributed assumptions that are typically used in random utility models and heterogeneity of passengers’ perceptions. Specifically, the Weibull distributed random error term resolves the perception variance with respect to various itinerary lengths, an itinerary-size factor term is suggested to solve the itinerary overlapping problem, and random coefficients are used to model heterogeneity of passengers. We also apply the mixed itinerary-size weibit model to a train-scheduling model to generate a passenger-oriented schedule plan. We test the efficiency and applicability of the train-scheduling model in the south China high-speed railway network, and we find that it works well and can be applied to large real-world problems.
Persistent Identifierhttp://hdl.handle.net/10722/280953
ISSN
2023 Impact Factor: 8.3
2023 SCImago Journal Rankings: 2.884
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXIE, J-
dc.contributor.authorWong, SC-
dc.contributor.authorZhan, S-
dc.contributor.authorLo, SM-
dc.contributor.authorChen, A-
dc.date.accessioned2020-02-25T07:43:12Z-
dc.date.available2020-02-25T07:43:12Z-
dc.date.issued2020-
dc.identifier.citationTransportation Research Part E: Logistics and Transportation Review, 2020, v. 136, p. article no. 101882-
dc.identifier.issn1366-5545-
dc.identifier.urihttp://hdl.handle.net/10722/280953-
dc.description.abstractIn this study, we propose a new schedule-based itinerary-choice model, the mixed itinerary-size weibit model, to address the independently and identically distributed assumptions that are typically used in random utility models and heterogeneity of passengers’ perceptions. Specifically, the Weibull distributed random error term resolves the perception variance with respect to various itinerary lengths, an itinerary-size factor term is suggested to solve the itinerary overlapping problem, and random coefficients are used to model heterogeneity of passengers. We also apply the mixed itinerary-size weibit model to a train-scheduling model to generate a passenger-oriented schedule plan. We test the efficiency and applicability of the train-scheduling model in the south China high-speed railway network, and we find that it works well and can be applied to large real-world problems.-
dc.languageeng-
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description-
dc.relation.ispartofTransportation Research Part E: Logistics and Transportation Review-
dc.subjectMixed itinerary-size weibit model-
dc.subjectSchedule-based-
dc.subjectTrain scheduling-
dc.titleTrain schedule optimization based on schedule-based stochastic passenger assignment-
dc.typeArticle-
dc.identifier.emailWong, SC: hhecwsc@hku.hk-
dc.identifier.authorityWong, SC=rp00191-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.tre.2020.101882-
dc.identifier.scopuseid_2-s2.0-85079375895-
dc.identifier.hkuros309241-
dc.identifier.volume136-
dc.identifier.spagearticle no. 101882-
dc.identifier.epagearticle no. 101882-
dc.identifier.isiWOS:000523602300002-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl1366-5545-

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