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A Model for the Stop Planning and Timetables of Customized Buses

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  • Jihui Ma
  • Yanqing Zhao
  • Yang Yang
  • Tao Liu
  • Wei Guan
  • Jiao Wang
  • Cuiying Song

Abstract

Customized buses (CBs) are a new mode of public transportation and an important part of diversified public transportation, providing advanced, attractive and user-led service. The operational activity of a CB is planned by aggregating space–time demand and similar passenger travel demands. Based on an analysis of domestic and international research and the current development of CBs in China and considering passenger travel data, this paper studies the problems associated with the operation of CBs, such as stop selection, line planning and timetables, and establishes a model for the stop planning and timetables of CBs. The improved immune genetic algorithm (IIGA) is used to solve the model with regard to the following: 1) multiple population design and transport operator design, 2) memory library design, 3) mutation probability design and crossover probability design, and 4) the fitness calculation of the gene segment. Finally, a real-world example in Beijing is calculated, and the model and solution results are verified and analyzed. The results illustrate that the IIGA solves the model and is superior to the basic genetic algorithm in terms of the number of passengers, travel time, average passenger travel time, average passenger arrival time ahead of schedule and total line revenue. This study covers the key issues involving operational systems of CBs, combines theoretical research and empirical analysis, and provides a theoretical foundation for the planning and operation of CBs.

Suggested Citation

  • Jihui Ma & Yanqing Zhao & Yang Yang & Tao Liu & Wei Guan & Jiao Wang & Cuiying Song, 2017. "A Model for the Stop Planning and Timetables of Customized Buses," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-28, January.
    • Handle: RePEc:plo:pone00:0168762
    DOI: 10.1371/journal.pone.0168762
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    References listed on IDEAS

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    1. Szeto, W.Y. & Jiang, Y., 2014. "Transit route and frequency design: Bi-level modeling and hybrid artificial bee colony algorithm approach," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 235-263.
    2. Weihua Gu & Michael J. Cassidy & Yuwei Li, 2015. "Models of Bus Queueing at Curbside Stops," Transportation Science, INFORMS, vol. 49(2), pages 204-212, May.
    3. Liu, Tao & Ceder, Avishai (Avi), 2015. "Analysis of a new public-transport-service concept: Customized bus in China," Transport Policy, Elsevier, vol. 39(C), pages 63-76.
    4. Arbex, Renato Oliveira & da Cunha, Claudio Barbieri, 2015. "Efficient transit network design and frequencies setting multi-objective optimization by alternating objective genetic algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 355-376.
    5. Ceder, Avishai & Wilson, Nigel H. M., 1986. "Bus network design," Transportation Research Part B: Methodological, Elsevier, vol. 20(4), pages 331-344, August.
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    Cited by:

    1. Qing Yu & Weifeng Li & Haoran Zhang & Dongyuan Yang, 2020. "Mobile Phone Data in Urban Customized Bus: A Network-based Hierarchical Location Selection Method with an Application to System Layout Design in the Urban Agglomeration," Sustainability, MDPI, vol. 12(15), pages 1-20, July.
    2. Han Zheng & Junhua Chen & Xingchen Zhang & Zixian Yang, 2019. "Designing a New Shuttle Service to Meet Large-Scale Instantaneous Peak Demands for Passenger Transportation in a Metropolitan Context: A Green, Low-Cost Mass Transport Option," Sustainability, MDPI, vol. 11(18), pages 1-28, September.
    3. Liu, Yanan & Xiao, Tong & Deng, Jihao & Li, Tianhao & Yang, Linchun & Yuan, Quan, 2024. "Heterogeneous impacts of the built environment on survival of customized bus services across the downtown and suburbs," Journal of Transport Geography, Elsevier, vol. 118(C).
    4. Zhiling Han & Yanyan Chen & Hui Li & Kuanshuang Zhang & Jiyang Sun, 2019. "Customized Bus Network Design Based on Individual Reservation Demands," Sustainability, MDPI, vol. 11(19), pages 1-25, October.
    5. Bing Zhang & Zhishan Zhong & Xun Zhou & Yongqiang Qu & Fangwei Li, 2023. "Optimization Model and Solution Algorithm for Rural Customized Bus Route Operation under Multiple Constraints," Sustainability, MDPI, vol. 15(5), pages 1-18, February.

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