高铁列车差异化动态定价与席位分配协同优化方法

doi:10.16097/j.cnki.1009-6744.2026.01.017

交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (1): 184-193.DOI: 10.16097/j.cnki.1009-6744.2026.01.017

高铁列车差异化动态定价与席位分配协同优化方法

许景¹，景云^*1，邓连波²，梁辉¹，蒋子文¹

1. 北京交通大学，交通运输学院，北京100044；2.中南大学，交通运输工程学院，长沙410075

收稿日期:2025-09-03 修回日期:2025-11-19 接受日期:2025-11-28 出版日期:2026-02-25 发布日期:2026-02-15
作者简介:许景（1998—），女，山西大同人，博士后。
基金资助:
国家自然科学基金(52372300)；北京交通大学自然科学类思源博士后科研启动基金(KTXKBH25001532)。

Joint Optimization of Differentiated Dynamic Pricing and Seat Allocation for High-speed Trains

XU Jing¹, JING Yun^*1, DENG Lianbo², LIANG Hui¹, JIANG Ziwen¹

1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China; 2. School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China

Received:2025-09-03 Revised:2025-11-19 Accepted:2025-11-28 Online:2026-02-25 Published:2026-02-15
Supported by:
National Natural Science Foundation of China(52372300)；Beijing Jiaotong University Natural Science Siyuan Postdoctoral Research Initiation Foundation(KTXKBH25001532)。

摘要/Abstract

摘要： 针对既有高铁动态定价研究中预售时段划分方式较为单一的问题（主要采用“一刀切”方式），本文提出考虑不同列车购票时段分布差异的高铁列车差异化动态定价与席位分配协同优化方法。考虑到预售期内各列车购票时段分布差异性，将分布特征相似的列车归为一类，针对不同类型列车设置差异化的动态定价时段划分方案，同类列车采用相同预售时段划分方案。为预售期每天建立旅客弹性需求函数，考虑列车席位能力、需求及票价上下界等约束，以最大化铁路客票总收益为目标，建立高铁列车差异化动态定价与席位分配协同优化非线性混合整数模型，并通过线性松弛和外近似技术对其进行线性化处理，利用Gurobi求解。采用广深高铁实际算例验证所提出优化模型和方法的有效性，相较于不划分预售时段和不采取动态定价的传统固定价格模式，优化后铁路客票总收益和旅客周转量分别提高13.49%和4.79%。本文可为铁路部门制定动态定价方案提供理论支持与实践参考，助力实现高铁收益最大化目标。

关键词: 铁路运输, 收益管理, 差异化动态定价, 席位分配, 高铁列车, 线性化

Abstract: To overcome the simplistic division of presale periods in current high-speed rail dynamic pricing research, this study proposes a joint optimization of differentiated dynamic pricing and seat allocation for high-speed trains based on the distinct ticket purchase period distributions of different trains. Considering the differences in the distribution of ticket purchase period for each train during the booking horizon, the trains with similar distribution characteristics are grouped into the same category. Differentiated pre-sale period division schemes of dynamic pricing are designed for different types of trains, while the same presale period division scheme is adopted for trains within the same category. A passenger demand elastic demand function is established for each day during the booking horizon. Considering the constraints, such as the train seat capacity, demand, and ticket price bounds, a nonlinear mixed-integer optimization model is developed to maximize the total railway ticket revenue for the joint optimization problem of differentiated dynamic pricing and seat allocation for high-speed trains. The model is then linearized through linear relaxation and outer approximation techniques, and solved with Gurobi solver. Numerical cases based on the Guangzhou-Shenzhen high-speed rail is used to validate the proposed optimization method. The results show that, compared with the traditional fixed pricing strategy without pre-sale period division or dynamic pricing, the optimized total railway ticket revenue and passenger turnover increased by 13.49% and 4.79%, respectively. This study provides a theoretical support and practical guidance for railway operators in formulating dynamic pricing strategies, contributing to the achievement of revenue maximization goals.

Key words: railway transportation, revenue management, differentiated dynamic pricing, seat allocation, high-speed trains, linearization

中图分类号:

U293.1

许景, 景云, 邓连波, 梁辉, 蒋子文. 高铁列车差异化动态定价与席位分配协同优化方法[J]. 交通运输系统工程与信息, 2026, 26(1): 184-193.

XU Jing, JING Yun, DENG Lianbo, LIANG Hui, JIANG Ziwen. Joint Optimization of Differentiated Dynamic Pricing and Seat Allocation for High-speed Trains[J]. Journal of Transportation Systems Engineering and Information Technology, 2026, 26(1): 184-193.

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http://www.tseit.org.cn/CN/Y2026/V26/I1/184

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高铁列车差异化动态定价与席位分配协同优化方法

Joint Optimization of Differentiated Dynamic Pricing and Seat Allocation for High-speed Trains

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