First train timetabling and bus service bridging in intermodal bus-and-train transit networks

Subway system is the main mode of transportation for city dwellers and is a quite signif-icant backbone to a city's operations. One of the challenges of subway network operation is the scheduling of the first trains each morning and its impact on transfers. To deal with this challenge, some cit...

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Bibliographic Details
Main Authors: KANG, Liujiang, LI, Hao, SUN, Huijun, WU, Jianjun, CAO, Zhiguang, BUHIGIRO, Nsabimana
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2021
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Online Access:https://ink.library.smu.edu.sg/sis_research/8125
https://ink.library.smu.edu.sg/context/sis_research/article/9128/viewcontent/First_train_timetabling_and_bus_service_bridging_in_intermodal_bus_and_train_transit_networks.pdf
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Institution: Singapore Management University
Language: English
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Summary:Subway system is the main mode of transportation for city dwellers and is a quite signif-icant backbone to a city's operations. One of the challenges of subway network operation is the scheduling of the first trains each morning and its impact on transfers. To deal with this challenge, some cities (e.g. Beijing) use bus 'bridging' services, temporarily substitut -ing segments of the subway network. The present paper optimally identifies when to start each train and bus bridging service in an intermodal transit network. Starting from a mixed integer nonlinear programming model for the first train timetabling problem, we linearize and reformulate the model using the auxiliary binary variables. Following that, the bus bridging model is developed to cooperate with the first train operation for reducing long transfer waiting times. After realizing the low computational efficiency of solving the inte-grated model, a tailored algorithm is designed to optimally solve the first train timetabling and bus service bridging problems. The exact models and algorithms are applied to the Beijing subway network to test their effectiveness and computational efficiency. Numerical results show that our approaches decrease the total passenger waiting time by 53.4% by a combined effect of adjusting the first train departure times and operating 27 bridging buses on 7 routes.