IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/8420206.html
   My bibliography  Save this article

Optimal Differential Pricing for Intercity High-Speed Railway Services with Time-Dependent Demand and Passenger Choice Behaviors under Capacity Constraints

Author

Listed:
  • Huanyin Su
  • Shuting Peng
  • Lianbo Deng
  • Weixiang Xu
  • Qiongfang Zeng
  • Luca D'Acierno

Abstract

Differential pricing of trains with different departure times caters to the taste heterogeneity of the time-dependent (departure time) demand and then improves the ticket revenue of railway enterprises. This paper studies optimal differential pricing for intercity high-speed railway services. The distribution features of the passenger demand regarding departure times are analyzed, and the time-dependent demand is formulated; a passenger assignment method considering departure periods and capacity constraints is constructed to evaluate the prices by simulating the ticket-booking process. Based on these, an optimization model is constructed with the aim of maximizing the ticket revenue and the decision variables for pricing train legs. A modified direct search simulated annealing algorithm is designed to solve the optimization model, and three random generation methods of new solutions are developed to search the solution space efficiently. Experimental analysis containing dozens of trains is performed on Wuhan-Shenzhen high-speed railway in China, and price solutions with different elastic demand coefficients (ϕ) are compared. The following results are found: (i) the optimization algorithm converges stably and efficiently and (ii) differentiation is shown in the price solutions, and the optimized ticket revenue is influenced greatly by ϕ, increasing by 7%–21%.

Suggested Citation

  • Huanyin Su & Shuting Peng & Lianbo Deng & Weixiang Xu & Qiongfang Zeng & Luca D'Acierno, 2021. "Optimal Differential Pricing for Intercity High-Speed Railway Services with Time-Dependent Demand and Passenger Choice Behaviors under Capacity Constraints," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-13, November.
    • Handle: RePEc:hin:jnlmpe:8420206
    DOI: 10.1155/2021/8420206
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/8420206.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/mpe/8420206.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/8420206?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. Huanyin Su & Shuting Peng & Shanglin Mo & Kaixin Wu, 2022. "Neural Network-Based Hybrid Forecasting Models for Time-Varying Passenger Flow of Intercity High-Speed Railways," Mathematics, MDPI, vol. 10(23), pages 1-21, December.
    2. Wenliang Zhou & Xiang Li & Xin Shi, 2023. "Joint Optimization of Time-Dependent Line Planning and Differential Pricing with Passenger Train Choice in High-Speed Railway Networks," Mathematics, MDPI, vol. 11(6), pages 1-28, March.
    3. Yu Wang & Jiafa Zhu, 2023. "Pricing Analysis for Railway Multi-Ride Tickets: An Optimization Approach for Uncertain Demand within an Agreed Time Limit," Mathematics, MDPI, vol. 11(23), pages 1-21, November.

    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:jnlmpe:8420206. 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.