IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v165y2025icp107-126.html
   My bibliography  Save this article

Comprehensive optimization of dynamic pricing and passenger flow assignment for differentiated high-speed train products

Author

Listed:
  • Jiren, Cao
  • Zhangjiaxuan, Liu
  • Zhenhuan, He
  • Lu, Tong
  • Lei, Nie

Abstract

In the context of high-speed railway marketization, devising a scientific dynamic fare strategy to achieve an efficient match between train supply and passenger demand is a pressing issue. Dynamic pricing and passenger flow assignment were placed into the same framework to achieve collaborative optimization. On the demand side, the space-time service network for the train timetable was constructed. A bidirectional breadth-first reasonable route search algorithm and passenger travel choice cost formula were proposed. The passenger choice behavior parameters were derived from revealed preference (RP) and stated preference (SP) surveys. On the supply side, differentiated train products were classified by the station level and the station number and were connected to the fare adjustment strategy. To solve the comprehensive optimization problem of dynamic pricing and passenger flow assignment, a differential pricing biobjective comprehensive optimization model was developed, and a multidimensional passenger flow assignment strategy was employed. Based on real data, the Beijing–Shanghai high-speed railway was used as a case study, and the station level, OD (Origin-Destination) level, train classification, fare adjustment strategy, enterprise revenue, train indices and OD fare were analyzed. The case study verified the effectiveness of the fare adjustment strategy based on differentiated train products and provided a novel approach for the marketization of high-speed railways.

Suggested Citation

  • Jiren, Cao & Zhangjiaxuan, Liu & Zhenhuan, He & Lu, Tong & Lei, Nie, 2025. "Comprehensive optimization of dynamic pricing and passenger flow assignment for differentiated high-speed train products," Transport Policy, Elsevier, vol. 165(C), pages 107-126.
  • Handle: RePEc:eee:trapol:v:165:y:2025:i:c:p:107-126
    DOI: 10.1016/j.tranpol.2025.01.043
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X25000551
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tranpol.2025.01.043?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
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Enjian Yao & Qirong Yang & Yongsheng Zhang & Xun Sun, 2013. "A Study on High-Speed Rail Pricing Strategy in the Context of Modes Competition," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-6, December.
    2. Cascetta, Ennio & Coppola, Pierluigi, 2016. "Assessment of schedule-based and frequency-based assignment models for strategic and operational planning of high-speed rail services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 93-108.
    3. van Vuuren, Daniel, 2002. "Optimal pricing in railway passenger transport: theory and practice in The Netherlands," Transport Policy, Elsevier, vol. 9(2), pages 95-106, April.
    4. Hetrakul, Pratt & Cirillo, Cinzia, 2014. "A latent class choice based model system for railway optimal pricing and seat allocation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 68-83.
    5. Chou, Jui-Sheng & Chien, Ya-Ling & Nguyen, Ngoc-Mai & Truong, Dinh-Nhat, 2018. "Pricing policy of floating ticket fare for riding high speed rail based on time-space compression," Transport Policy, Elsevier, vol. 69(C), pages 179-192.
    6. Yongsheng Zhang & Enjian Yao & Kangning Zheng & Hao Xu, 2020. "Metro passenger’s path choice model estimation with travel time correlations derived from smart card data," Transportation Planning and Technology, Taylor & Francis Journals, vol. 43(2), pages 141-157, February.
    7. 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.
    8. Takahiko Kusakabe & Takamasa Iryo & Yasuo Asakura, 2010. "Estimation method for railway passengers’ train choice behavior with smart card transaction data," Transportation, Springer, vol. 37(5), pages 731-749, September.
    9. Jinzi Zheng, 2020. "Research on Passenger Flow Assignment of High-Speed Trains Based on Personalized Itinerary Choice," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-8, May.
    10. Frejinger, E. & Bierlaire, M., 2007. "Capturing correlation with subnetworks in route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 363-378, March.
    11. Cirillo, Cinzia & Bastin, Fabian & Hetrakul, Pratt, 2018. "Dynamic discrete choice model for railway ticket cancellation and exchange decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 137-146.
    12. Binder, Stefan & Maknoon, Yousef & Bierlaire, Michel, 2017. "Exogenous priority rules for the capacitated passenger assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 19-42.
    13. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    14. Huiling Fu & Benjamin R. Sperry & Lei Nie, 2013. "Operational Impacts of Using Restricted Passenger Flow Assignment in High-Speed Train Stop Scheduling Problem," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-8, December.
    15. Anciaes, Paulo & Metcalfe, Paul & Heywood, Chris & Sheldon, Rob, 2019. "The impact of fare complexity on rail demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 224-238.
    16. Bharill, Rohit & Rangaraj, Narayan, 2008. "Revenue management in railway operations: A study of the Rajdhani Express, Indian Railways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(9), pages 1195-1207, November.
    17. Yu, Liping & Liu, Huiran & Fang, Zhiming & Ye, Rui & Huang, Zhongyi & You, Yayun, 2023. "A new approach on passenger flow assignment with multi-connected agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    18. Xu, Guangming & Zhong, Linhuan & Hu, Xinlei & Liu, Wei, 2022. "Optimal pricing and seat allocation schemes in passenger railway systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    Full references (including those not matched with items on IDEAS)

    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. Xueyi Guan & Jin Qin & Chenghui Mao & Wenliang Zhou, 2023. "A Literature Review of Railway Pricing Based on Revenue Management," Mathematics, MDPI, vol. 11(4), pages 1-17, February.
    2. Jin Qin & Xiqiong Li & Kang Yang & Guangming Xu, 2022. "Joint Optimization of Ticket Pricing Strategy and Train Stop Plan for High-Speed Railway: A Case Study," Mathematics, MDPI, vol. 10(10), pages 1-17, May.
    3. Xu, Guangming & Zhong, Linhuan & Liu, Wei & Guo, Jing, 2024. "A flexible train composition strategy with extra-long trains for high-speed railway corridors with time-varying demand," Transportation Research Part B: Methodological, Elsevier, vol. 179(C).
    4. Robenek, Tomáš & Azadeh, Shadi Sharif & Maknoon, Yousef & de Lapparent, Matthieu & Bierlaire, Michel, 2018. "Train timetable design under elastic passenger demand," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 19-38.
    5. 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.
    6. Haque, Md Tabish & Hamid, Faiz, 2023. "Social distancing and revenue management—A post-pandemic adaptation for railways," Omega, Elsevier, vol. 114(C).
    7. Chen, Pengfang & Zhang, Xiaoqiang & Gao, Dongsheng, 2024. "Preference heterogeneity analysis on train choice behaviour of high-speed railway passengers: A case study in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 188(C).
    8. Zhan, Shuguang & Wong, S.C. & Lo, S.M., 2020. "Social equity-based timetabling and ticket pricing for high-speed railways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 165-186.
    9. Jiren CAO & Lei NIE & Lu TONG & Zhenhuan HE & Zhangjiaxuan LIU, 2024. "Dynamic pricing optimization for high-speed railway based on passenger flow assignment," PLOS ONE, Public Library of Science, vol. 19(12), pages 1-25, December.
    10. Biswas, Mehek & Bhat, Chandra R. & Ghosh, Sulagna & Pinjari, Abdul Rawoof, 2024. "Choice models with stochastic variables and random coefficients," Journal of choice modelling, Elsevier, vol. 51(C).
    11. Xu, Guangming & Liu, Wei & Wu, Runfa & Yang, Hai, 2021. "A double time-scale passenger assignment model for high-speed railway networks with continuum capacity approximation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    12. 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.
    13. Peer, Stefanie & Knockaert, Jasper & Verhoef, Erik T., 2016. "Train commuters’ scheduling preferences: Evidence from a large-scale peak avoidance experiment," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 314-333.
    14. Jianqiang Wang & Wenlong Zhao & Chenglin Liu & Zhipeng Huang, 2023. "A System Optimization Approach for Trains’ Operation Plan with a Time Flexible Pricing Strategy for High-Speed Rail Corridors," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    15. Papola, Andrea & Tinessa, Fiore & Marzano, Vittorio, 2018. "Application of the Combination of Random Utility Models (CoRUM) to route choice," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 304-326.
    16. 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).
    17. Wenliang Zhou & Ziyu Zou & Naijie Chai & Guangming Xu, 2023. "Optimization of Differential Pricing and Seat Allocation in High-Speed Railways for Multi-Class Demands: A Chinese Case Study," Mathematics, MDPI, vol. 11(6), pages 1-17, March.
    18. Kruse, Tobias & Atkinson, Giles, 2022. "Understanding public support for international climate adaptation payments: Evidence from a choice experiment," Ecological Economics, Elsevier, vol. 194(C).
    19. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    20. David Hensher & John Rose & Zheng Li, 2012. "Does the choice model method and/or the data matter?," Transportation, Springer, vol. 39(2), pages 351-385, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:eee:trapol:v:165:y:2025:i:c:p:107-126. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/30473/description#description .

    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.