工业工程 ›› 2018, Vol. 21 ›› Issue (4): 62-67.doi: 10.3969/j.issn.1007-7375.2018.04.008

• 实践与应用 • 上一篇    下一篇

基于旅客购票行为仿真的高铁票价动态调整

徐沙, 李彦瑾, 罗霞   

  1. 西南交通大学 交通运输与物流学院, 四川 成都 610031
  • 收稿日期:2017-12-25 出版日期:2018-08-30 发布日期:2018-08-27
  • 作者简介:徐沙(1994-),女,重庆市人,硕士研究生,主要研究方向为交通运输规划与管理.
  • 基金资助:
    中国铁路总公司科技研究开发计划资助项目(2014X006-A,2015G002-N);中央高校基本科研业务费专项资金资助项目(SWJTUA0920502051307-03)

Dynamic Adjustment of High-Speed Railway Ticket Price with Passenger Purchasing Behavior Simulation

XU Sha, LI Yanjin, LUO Xia   

  1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2017-12-25 Online:2018-08-30 Published:2018-08-27

摘要: 高速铁路需要一套基于市场竞争的票价调整策略,考虑旅客购票概率、高铁席位存量与时域动态票价,给出非同质旅客购票效益表达形式,采用动态规划原理推导计算席位存量和动态票价的递推公式,最终构建市场竞争环境下高铁票价动态调整模型。通过在某预售期60 d内京广高铁旅客购票仿真数据得出,非同质旅客购票到达概率满足非齐次泊松分布,与相同直达OD下的航空竞争其票价按席位存量500、375、270、207分4次完成动态调整,客票单价调整为900元、950元、1 000元、920元。研究旨在为综合运输背景下高铁客票定价提供仿真方法。

关键词: 市场竞争, 席位存量, 动态票价, 购票到达概率, 动态规划, 行为仿真

Abstract: High-speed railway needs a ticket price adjustment strategy based on market competition environment. Considering probability of passenger purchasing ticket, railway seats inventory and dynamic price in time domain, giving expression formula of passenger purchasing benefit, using dynamic programming method to deduce recursive formula between seats inventory and dynamic ticket price, a dynamic adjustment model of railway ticket price under market competition environment is eventually built. Through simulation data from Beijing-Guangzhou High-speed Railway and the air transport with same direct OD in a 60-day pre-sale period, a conclusion is reached that arriving probability of passenger purchasing ticket submits to non-homogeneous poisson distribution, finishing 4 dynamic adjustments on seats inventory:500, 375, 270, 207, and relevantly the railway ticket price is dynamically adjusted:900yuan, 950 yuan, 1 000 yuan, 920 yuan. The research results can provide simulation method for high-speed railway ticket price system under comprehensive transportation environment.

Key words: market competition, seats inventory, dynamic ticket price, arriving probability of purchasing ticket, dynamic programming, behavior simulation

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