IDEAS home Printed from https://ideas.repec.org/a/hin/jnddns/5649020.html
   My bibliography  Save this article

Collaborative Optimization of Stop Schedule Plan and Ticket Allotment for the Intercity Train

Author

Listed:
  • Xichun Chen
  • Junli Wang

Abstract

As regards the ticket allotment issue of the intercity passenger corridor designed for different train grades, the matching relationship between the ticket allotment and the passenger flow demand is studied. The passenger flow conversion equation which is based on the collaborative optimization of the intercity train stop schedule plan and ticket allotment is established. Then the mathematical model aiming at the maximum revenue of intercity train system and the highest satisfaction from the passengers is established. The particle swarm harmony search algorithm is designed to solve the model. The example verifies the effectiveness of the model and algorithm, which indicates that, through the collaborative optimization of the stop schedule plan and ticket allotment for different grades intercity trains, the sectional utilization rate of the train can be improved; meanwhile, the optimum matching between the intercity train revenue and the passenger satisfaction can be realized.

Suggested Citation

  • Xichun Chen & Junli Wang, 2016. "Collaborative Optimization of Stop Schedule Plan and Ticket Allotment for the Intercity Train," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-7, January.
  • Handle: RePEc:hin:jnddns:5649020
    DOI: 10.1155/2016/5649020
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/DDNS/2016/5649020.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/DDNS/2016/5649020.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2016/5649020?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
    ---><---

    Citations

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


    Cited by:

    1. Jin Qin & Yijia Zeng & Xia Yang & Yuxin He & Xuanke Wu & Wenxuan Qu, 2019. "Time-Dependent Pricing for High-Speed Railway in China Based on Revenue Management," Sustainability, MDPI, vol. 11(16), pages 1-18, August.
    2. Xu, Guangming & Liu, Yihan & Gao, Yihan & Liu, Wei, 2023. "Integrated optimization of train stopping plan and seat allocation scheme for railway systems under equilibrium travel choice and elastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).

    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:hin:jnddns:5649020. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.