Optimization of High-speed Rail Seat Allocation Considering Multi-dimensional Travel Demand of Passengers

doi:10.16097/j.cnki.1009-6744.2025.05.017

Abstract

Abstract: Combined with the characteristics of the multi-dimensional travel demand from high-speed railway passengers in China, the key to the optimal allocation of transportation capacity and the improvement of high-speed rail operation efficiency and service quality is to study the scientific and reasonable seat allocation method. In order to solve the problem of seat allocation in the high-speed railway (HSR) network, based on the time-space network that integrates passenger preferences, this paper constructs a two-level planning seat allocation model to distinguish passenger categories under elastic demand. The model was re-represented into a single-layer mixed integer linear programming model (MILP) by using the model transformation, large M method and piecewise linear method. The GUROBI was used to solve the problem. The results of the Beijing-Shanghai high-speed railway case show that under the same potential demand, the flexible demand seat allocation scheme considering passenger classification increases the actual passenger demand by 1.97% and the seat revenue by 4.49% compared with the seat sharing scheme. Compared with the scheme of non-passenger classification, the demand of actual passenger increased by 1.16% and the seat revenue increased by 2.27%. It indicates that the seat allocation model considering passenger classification under flexible demand can provide a reference for high-speed rail enterprises to optimize the seat allocation structure, attract potential passengers, and obtain more seat revenue under the condition of limited resources.

Key words: railway transportation, seat allocation, linearization method, high-speed trains, multi-dimensional travel demand

摘要： 结合我国高速铁路旅客多维出行需求的特征，研究科学合理的票额分配方法是实现运力资源优化配置、提升高铁运营效率和服务质量的关键所在。本文针对高速铁路(HSR)网络中的票额分配问题，基于融合乘客偏好的时空网络，构建弹性需求下区分旅客类别的双层规划票额分配模型。运用模型转化、大M法和分段线性方法，将模型重新表述为单层混合整数线性规划模型(MILP)，采用GUROBI求解器求解。京沪高铁案例结果显示：在相同潜在需求下，考虑旅客分类的弹性需求票额分配方案相比票额共用方案，旅客实际需求增加1.97%，客票收益增加4.49%；相比无旅客分类方案，旅客实际需求增加1.16%，客票收益增加2.27%。这表明弹性需求下考虑旅客分类的票额分配模型可以为高铁企业在资源有限的情况下，优化票额配置结构，吸引潜在旅客，获得更多客票收益提供参考。

关键词: 铁路运输, 票额分配, 线性化方法, 高铁列车, 多维出行需求

CLC Number:

U293.2

JING Yun, WANG Qi, WANG Siyuan, WU Mingze. Optimization of High-speed Rail Seat Allocation Considering Multi-dimensional Travel Demand of Passengers[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(5): 193-204.

景云, 王琪, 王思源, 吴明泽. 考虑旅客多维出行需求的高速铁路票额分配优化研究[J]. 交通运输系统工程与信息, 2025, 25(5): 193-204.

Add to citation manager EndNote|Ris|BibTeX

URL: http://www.tseit.org.cn/EN/10.16097/j.cnki.1009-6744.2025.05.017

http://www.tseit.org.cn/EN/Y2025/V25/I5/193

References

[1] CIANCHMINO A, INZERILLO G, LUCIDI S, et al. A mathematical programming approach for the solution of the railway yield management problem[J]. Transportation Science, 1999, 33(2): 168-181.

[2] 骆泳吉,刘军,赖晴鹰. 考虑通售席位的旅客列车票额优化方法[J]. 铁道学报, 2016, 38(5): 11-15. [LUO Y J, LIU J, LAI Q Y. Optimization of seat inventory allocation for passenger trains with first-come-first-serve seats[J]. Journal of the China Railway Society, 2016, 38(5): 11-15.]

[3] 包云, 刘军, 刘江川, 等. 基于随机需求的单列车票额分配方法[J]. 中国铁道科学, 2015, 36(2): 96-102. [BAO Y, LIU J, LIU J C, et al. Seat allotment method for single train based on stochastic demand[J]. China Railway Science, 2015, 36(2): 96-102.]

[4] 张琦, 王玉, 李华. 多列车限售策略和铁路票额预分方案的优化设计[J]. 中国铁道科学, 2019, 40(2): 138-144. [ZHANG Q, WANG Y, LI H, Optimization design of multi-train limited sale strategy and pre-allocation plan for railway tickets[J]. China Railway Science, 2019, 40 (2): 138-144.]

[5] CHOU J S, ONCKOWIJOYO C S, NGO N T, et al. Evolutionary bi-level model for optimizing ticket fares and operations profit of Taiwan high-speed rail[J]. Research in Transportation Business & Management, 2020, 37: 100548.

[6] 陈远华. 多等级票价策略下的高铁席位存量控制研究[D]. 成都: 西南交通大学, 2023. [CHEN Y H. Research on seat inventory control for high-speed railway under multi-level fare strategy[D]. Chengdu: Southwest Jiaotong University, 2023]

[7] 秦进, 郝丽娜, 毛成辉, 等. 基于收益管理的高速铁路票价与坐席分配联合优化[J]. 铁道学报, 2020, 42 (12): 10–17. [QIN J, HAO L N, MAO C H, et al. Joint optimization method of high-speed rail ticket price and seat allocation based on revenue management[J]. Journal of the China Railway Society, 2020, 42(12): 10–17.]

[8] 周文梁, 蒋志刚, 柴乃杰, 等. 高速铁路列车开行方案与票价票额综合优化[J]. 交通运输系统工程与信息, 2024, 24(3): 151–163. [ZHOU W L, JIANG Z G, CHAI N J, et al. Comprehensive optimization of line planning, ticket pricing and seat allocation of high-speed railway [J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(3): 151–163.]

[9] XU G M, YANG H, LIU W, et al. Itinerary choice and advance ticket booking for high-speed railway network services[J]. Transportation Research Part C: Emerging Technologies, 2018, 95: 82–104.

[10] YAN Z, LI X, ZHANG Q, et al. Seat allocation model for high-speed railway passenger transportation based on flexible train composition[J]. Computers & Industrial Engineering, 2020, 142: 106383.

[11] 孙国锋, 景云,李和壁,等.基于旅客多维出行需求的列车开行方案与票价联合优化方法[J]. 中国铁道科学, 2024, 45(6): 224–235. [SUN G F, JING Y, LI H B, et al. Joint optimization method of train line planning and ticket pricing based on multi-dimensional travel demand of passengers[J]. China Railway Science, 2024, 45(6): 224–235.]

[12] 徐彦. 基于收益管理的高铁动态定价方法[J]. 铁道科学与工程学报, 2019, 16(2): 319–325. [XU Y. Dynamic pricing method for high-speed railway based on revenue management[J]. Journal of Railway Science and Engineering, 2019, 16(2): 319–325.]

[13] ZHAN S, WONG S C, LO S M. Social equity-based timetabling and ticket pricing for high-speed railways[J]. Transportation Research Part A: Policy and Practice, 2020, 137: 165–186.

[14] PICOU A. The Economics of Welfare (1st Ed.) [M]. London: Routledge, 2002.

[15] ROBENEK T, AZADEH S S, MAKNOON Y, et al. Train timetable design under elastic passenger demand[J]. Transportation Research Part B: Methodological, 2018, 111: 19–38.

[16] ZHAO S, WU R F, SHI F. A line planning approach for high-speed railway network with time-varying demand [J]. Computers & Industrial Engineering, 2021, 160: 107547.