IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0168762.html
   My bibliography  Save this article

A Model for the Stop Planning and Timetables of Customized Buses

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0168762
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0168762&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0168762?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ahern, Zeke & Paz, Alexander & Corry, Paul, 2022. "Approximate multi-objective optimization for integrated bus route design and service frequency setting," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 1-25.
    2. Tian, Qingyun & Wang, David Z.W. & Lin, Yun Hui, 2021. "Service operation design in a transit network with congested common lines," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 81-102.
    3. Javier Durán-Micco & Pieter Vansteenwegen, 2022. "A survey on the transit network design and frequency setting problem," Public Transport, Springer, vol. 14(1), pages 155-190, March.
    4. Nayan, Ashish & Wang, David Z.W., 2017. "Optimal bus transit route packaging in a privatized contracting regime," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 146-157.
    5. Canca, David & Barrena, Eva & De-Los-Santos, Alicia & Andrade-Pineda, José Luis, 2016. "Setting lines frequency and capacity in dense railway rapid transit networks with simultaneous passenger assignment," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 251-267.
    6. Manser, Patrick & Becker, Henrik & Hörl, Sebastian & Axhausen, Kay W., 2020. "Designing a large-scale public transport network using agent-based microsimulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 1-15.
    7. Cancela, Héctor & Mauttone, Antonio & Urquhart, María E., 2015. "Mathematical programming formulations for transit network design," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 17-37.
    8. Kumar, Pramesh & Khani, Alireza, 2022. "Planning of integrated mobility-on-demand and urban transit networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 499-521.
    9. Sunhyung Yoo & Jinwoo Brian Lee & Hoon Han, 2023. "A Reinforcement Learning approach for bus network design and frequency setting optimisation," Public Transport, Springer, vol. 15(2), pages 503-534, June.
    10. Ahmed, Leena & Mumford, Christine & Kheiri, Ahmed, 2019. "Solving urban transit route design problem using selection hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 274(2), pages 545-559.
    11. Philipp Heyken Soares, 2021. "Zone-based public transport route optimisation in an urban network," Public Transport, Springer, vol. 13(1), pages 197-231, March.
    12. Mohsen Momenitabar & Jeremy Mattson, 2021. "A Multi-Objective Meta-Heuristic Approach to Improve the Bus Transit Network: A Case Study of Fargo-Moorhead Area," Sustainability, MDPI, vol. 13(19), pages 1-25, September.
    13. Ibarra-Rojas, O.J. & Delgado, F. & Giesen, R. & Muñoz, J.C., 2015. "Planning, operation, and control of bus transport systems: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 38-75.
    14. Christina Iliopoulou & Konstantinos Kepaptsoglou & Eleni Vlahogianni, 2019. "Metaheuristics for the transit route network design problem: a review and comparative analysis," Public Transport, Springer, vol. 11(3), pages 487-521, October.
    15. Philipp Heyken Soares & Christine L. Mumford & Kwabena Amponsah & Yong Mao, 2019. "An adaptive scaled network for public transport route optimisation," Public Transport, Springer, vol. 11(2), pages 379-412, August.
    16. Xuekai Cen & Kanghui Ren & Yiying Cai & Qun Chen, 2023. "Designing Flexible-Bus System with Ad-Hoc Service Using Travel-Demand Clustering," Mathematics, MDPI, vol. 11(4), pages 1-27, February.
    17. Duran-Micco, Javier & Vermeir, Evert & Vansteenwegen, Pieter, 2020. "Considering emissions in the transit network design and frequency setting problem with a heterogeneous fleet," European Journal of Operational Research, Elsevier, vol. 282(2), pages 580-592.
    18. Wu, Jiaming & Kulcsár, Balázs & Selpi, & Qu, Xiaobo, 2021. "A modular, adaptive, and autonomous transit system (MAATS): A in-motion transfer strategy and performance evaluation in urban grid transit networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 81-98.
    19. Wang, Chao & Ma, Changxi & Xu, Xuecai(Daniel), 2020. "Multi-objective optimization of real-time customized bus routes based on two-stage method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    20. Luo, Sida & Nie, Yu (Marco), 2019. "Impact of ride-pooling on the nature of transit network design," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 175-192.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0168762. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.