计算机应用 ›› 2020, Vol. 40 ›› Issue (1): 278-283.DOI: 10.11772/j.issn.1001-9081.2019061088

• 应用前沿、交叉与综合 • 上一篇    下一篇

基于客流分配的高铁票价调整策略

尹胜男, 李引珍, 张长泽   

  1. 兰州交通大学 交通运输学院, 兰州 730070
  • 收稿日期:2019-06-25 修回日期:2019-09-05 出版日期:2020-01-10 发布日期:2019-10-08
  • 作者简介:尹胜男(1996-),女,山东临沂人,硕士研究生,主要研究方向:交通运输规划与管理、收益管理;李引珍(1963-),男,甘肃天水人,教授,博士生导师,博士,主要研究方向:交通运输规划与管理、物流管理、管理科学与工程;张长泽(1995-),男,甘肃武威人,硕士研究生,主要研究方向:交通运输规划与管理。

High-speed railway fare adjustment strategy based on passenger flow assignment

YIN Shengnan, LI Yinzhen, ZHANG Changze   

  1. School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou Gansu 730070, China
  • Received:2019-06-25 Revised:2019-09-05 Online:2020-01-10 Published:2019-10-08
  • Contact: 李引珍

摘要: 针对目前高铁票价单一、客运收益率低、区段客流不均衡等问题,提出基于客流分配的高铁票价调整策略。首先,分析影响旅客出行选择行为的相关因素,构建包含经济性、快速性、便捷性和舒适性四项指标的广义出行费用函数;然后,建立兼顾高铁客运管理部门收益最大化和旅客出行费用最小化的双层规划模型,其中上层规划通过制定票价调整策略实现高铁客运收益最大化,下层规划以旅客广义出行费用最小为目标,利用区段不同车次间的竞合关系构建随机用户均衡(SUE)分配模型,同时采用基于改进Logit分配模型的相继平均法(MSA)进行求解;最后,结合案例验证了所提票价调整策略能够有效地平衡区段客流,降低旅客出行成本并在一定程度上提高客运收益。结果分析表明该票价调整策略能够为铁路客运管理部门优化票价体系、制定票价调整方案提供决策支持与方法指导。

关键词: 票价调整, 广义费用, 双层规划模型, 客流分配, 相继平均算法

Abstract: Concerning the problems of single fare, low revenue rate of passenger transport and unbalanced passenger flow in different sections of high-speed railway, an adjustment strategy of high-speed railway fare based on passenger flow assignment was proposed. Firstly, the related factors affecting passenger travel choice behavior were analyzed, and a generalized travel cost function including four indicators of economy, rapidity, convenience and comfort was constructed. Secondly, a bilevel programming model considering the maximization of revenue of railway passenger transport management department and the minimization of passenger travel cost was established, in which the upper level programming achieved the maximum revenue of high-speed railway passenger transport by formulating fare adjustment strategy, the lower-level programming took the minimum passenger generalized travel cost as the goal, and used the competition and cooperation relationship between different trains of section to construct Stochastic User Equilibrium (SUE) model, and the model was solved by Method of Successive Averages (MSA) based on the improved Logit assignment model. Finally, the case study shows that the proposed fare adjustment strategy can effectively balance the section passenger flow, reduce passenger travel cost and improve passenger transport revenue to a certain extent. The experimental results show that the fare adjustment strategy can provide decision support and methodological guidance for railway passenger transport management departments to optimize fare system and formulate fare adjustment schemes.

Key words: fare adjustment, generalized cost, bilevel programming model, passenger flow assignment, Method of Successive Averages (MSA)

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