Robust optimization model of dynamic pricing for high-speed railway

SONG Wenbo; ZHAO Peng; LI Bo; WANG Pan

doi:10.11918/j.issn.0367-6234.201706073

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Robust optimization model of dynamic pricing for high-speed railway

更新时间：2026-10-23

- Robust optimization model of dynamic pricing for high-speed railway
- Vol. 50, Issue 9, Pages: 25-30(2018)
- 作者机构：
  
  1. 北京交通大学交通运输学院,北京,100044
  2. 中国铁路成都局集团有限公司绵阳车务段,四川,绵阳,621000
- 作者简介：
- 基金信息：
- DOI：10.11918/j.issn.0367-6234.201706073
  CLC： U293.22
- Published：2018
- 稿件说明：
移动端阅览
SONG Wenbo, ZHAO Peng, LI Bo, et al. Robust optimization model of dynamic pricing for high-speed railway[J]. 2018, 50(9): 25-30.
DOI：

SONG Wenbo, ZHAO Peng, LI Bo, et al. Robust optimization model of dynamic pricing for high-speed railway[J]. 2018, 50(9): 25-30. DOI： 10.11918/j.issn.0367-6234.201706073.

摘要

针对目前高速铁路票价单一，不能用来调节客流、提高收益的问题，在分析高速铁路不同售票时段旅客对价格敏感性的基础上，基于收益管理理论，结合高速铁路运输组织特点，以收益最大化为目标，构建高速铁路分时段动态定价稳健模型，并针对需求函数系数的不确定性，运用稳健优化方法对模型求解.以京沪高铁列车为对象进行案例分析，并与单一全价票下的票额分配方案进行对比，最后通过仿真模拟验证了模型的稳健性.结果表明：考虑收益管理的动态定价稳健模型能够通过动态调整价格来调节不同售票时段的客流需求从而提高收益；并且相比名义模型，该模型能够更好适应需求波动且能够保证将更多的车票以更高的价格销售，所构建模型为高速铁路实施动态定价策略提供优化方法.

Abstract

Ticket price of high-speed railway in China is unitary and changeless

which cannot adjust passenger flow and improve revenue. Based on the analysis of passenger's sensitivity towards ticket price in different booking periods

a robust optimization model of multi-period dynamic pricing for high-speed railway was developed aiming to maximize the revenue on the basis of revenue management theory and the transportation organization characteristics of high-speed railway. Considering the uncertainty of demand function

the model was solved with a robust optimization method. Beijing-Shanghai high-speed train was taken as an example to test the effectiveness of the model. The results showed that compared with the seat allocation scheme under the unitary ticket fare

the proposed model can dynamically adjust ticket fare to regulate the passenger flow in different booking periods and improve revenue. In addition

the robustness of the model was verified by the simulation test. Compared with the nominal model

the proposed model can better adapt to the fluctuation of the demand and ensure that more tickets are sold at a higher price. The proposed model provides an optimization method for dynamic pricing of high-speed railway.

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Related Institution

School of Civil Engineering, Beijing Jiaotong University

Railway Engineering Consulting Group Co., Ltd.

China State Railway Group Co., Ltd.

Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety (Tongji University)

Key Laboratory of Road and Traffic Engineering of Ministry of Education(Tongji University)

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