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Stochastic seat allocation models for passenger rail transportation under customer choice

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  • Wang, Xinchang
  • Wang, Hua
  • Zhang, Xiaoning

Abstract

We study the seat allocation problem for passenger rail revenue management, in which a rail operator attempts to determine the optimal quantity of seats to be allocated to each cabin class for each train service. We formulate the problem with single-stage and multi-stage decisions as two stochastic programming models that incorporate passengers’ choice behavior. We transform the stochastic models into equivalent deterministic mathematical programs that are easy to solve. Then, we form a variety of seat allocation polices from the optimal solutions to the seat allocation models. A number of simulation tests are offered to test the policies.

Suggested Citation

  • Wang, Xinchang & Wang, Hua & Zhang, Xiaoning, 2016. "Stochastic seat allocation models for passenger rail transportation under customer choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 95-112.
  • Handle: RePEc:eee:transe:v:96:y:2016:i:c:p:95-112
    DOI: 10.1016/j.tre.2016.10.003
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    Cited by:

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    2. Haque, Md Tabish & Hamid, Faiz, 2023. "Social distancing and revenue management—A post-pandemic adaptation for railways," Omega, Elsevier, vol. 114(C).
    3. 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).
    4. Yu Wang & Xinghua Shan & Hongye Wang & Junfeng Zhang & Xiaoyan Lv & Jinfei Wu, 2022. "Ticket Allocation Optimization of Fuxing Train Based on Overcrowding Control: An Empirical Study from China," Sustainability, MDPI, vol. 14(12), pages 1-12, June.
    5. Haque, Md Tabish & Hamid, Faiz, 2022. "An optimization model to assign seats in long distance trains to minimize SARS-CoV-2 diffusion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 104-120.
    6. 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).
    7. 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.
    8. Wuyang Yuan & Lei Nie & Xin Wu & Huiling Fu, 2018. "A dynamic bid price approach for the seat inventory control problem in railway networks with consideration of passenger transfer," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-23, August.
    9. 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).
    10. 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).
    11. Xiang Zhao & Xinghua Shan & Jinfei Wu, 2023. "The Impact of Seat Resource Fragmentation on Railway Network Revenue Management," Networks and Spatial Economics, Springer, vol. 23(1), pages 135-177, March.
    12. 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.

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