Joint optimization of ticket pricing and stop plan for high-speed railway

被引：0

作者：

Qin J. ^{[1
,2
]}

Zhang Z. ^{[1
]}

Li X. ^{[1
]}

Hu X. ^{[1
]}

Xu G. ^{[1
,2
]}

Yang K. ^{[1
]}

Zou H. ^{[1
]}

机构：

[1] School of Traffic & Transportation Engineering, Central South University, Changsha

[2] Rail Data Research and Application Key Laboratory of Hunan Province, Changsha

来源：

Journal of Railway Science and Engineering | 2023年 / 20卷 / 03期

关键词：

dynamic pricing; high-speed railway; joint decision; seat allocation; train stop plan;

D O I：

10.19713/j.cnki.43-1423/u.T20220599

中图分类号：

学科分类号：

摘要：

In the market-oriented operation of the high-speed railway (HSR), the ticket price has a direct impact on passenger demand, while the train stop plan can affect the distribution of transport capacity. However, the HSR lacks a scientific and flexible market-based mechanism to adjust the ticket price, and always formulates the train stop plan without considering the impact of price adjustment on passenger demand. To better balance passenger demand and HSR transport supply and improve HSR’s market-oriented operation level and competitiveness, it is necessary to study the dynamic pricing method of HSR based on passenger demand and train service level. Considering the price elasticity of passenger demand and the impact of stop plan on passenger demand and transport supply, the pre-sale period was divided into multiple stages. A joint model that incorporates the stop plan into HSR dynamic pricing and seat allocation problem was proposed. The objective was to maximize the operating revenue of railway enterprises and minimize the travel time value loss of passengers under the constraints of price ranges, train capacity, direct service of OD pairs, etc. A bi-level simulated annealing algorithm was designed to solve the model. Finally, a case study using the ticket data of Beijing-Shanghai HSR was carried out. The results show that the optimized comprehensive plan can increase the transport revenue of HSR by more than 3%, and reduce the travel time value loss of passengers by more than 8%. The dynamic pricing strategy is to set low discount coefficients for the early pre-sale stages and set high coefficients for the later stages, which can effectively guide more passengers to buy tickets earlier while increasing ticket revenue. The optimized stop plan achieves a better combination of trains’ stopping patterns, satisfying as much passenger demand as possible while maintaining a high passenger flow level. © 2023, Central South University Press. All rights reserved.

引用

页码：812 / 823

页数：11

共 17 条

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