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灵活编组高铁列车的售票时间窗优化
引用本文:闫振英,韩宝明,李晓娟,曹瑾鑫.灵活编组高铁列车的售票时间窗优化[J].东北大学学报(自然科学版),2022,43(10):1513-1520.
作者姓名:闫振英  韩宝明  李晓娟  曹瑾鑫
作者单位:(1. 内蒙古大学 交通学院, 内蒙古 呼和浩特010020; 2. 北京交通大学 交通运输学院, 北京100044; 3. 内蒙古自治区科学技术研究院, 内蒙古 呼和浩特010070)
基金项目:国家自然科学基金资助项目(72061028,71961024); 内蒙古自治区关键技术攻关计划项目(2019GG287); 内蒙古自治区自然科学基金资助项目(2022MS07020).
摘    要:灵活编组使高铁列车席位容量具备了有限柔性,相比传统固定容量下的控制技术,柔性容量的售票控制优化能实现更高效的供需匹配.基于高铁线路多列车、多停站的服务网络,根据收益管理原理设置不同价格等级的客票.采用偏好序模型刻画旅客购票选择行为,使用售票时间窗控制客票预售过程,以获利最大为目标建立灵活编组方案与售票时间窗的联合优化模型.根据售票需要设计客票排序,将模型转化为线性规划模型,并采用CPLEX快速求解,得到列车最佳编组方案和售票控制策略.实验结果表明:需求不饱和时,相比固定编组,灵活编组下的售票时间窗控制策略获利更高;旅客到达率和转移购买概率越高,列车最佳编组越趋向于大编组.

关 键 词:铁路运输  收益管理  偏好序选择行为  灵活编组  停售时间控制  
修稿时间:2021-09-06

Optimization of Ticketing Time Window for High-Speed Railway Trains of Flexible Formation
YAN Zhen-ying,HAN Bao-ming,LI Xiao-juan,CAO Jin-xin.Optimization of Ticketing Time Window for High-Speed Railway Trains of Flexible Formation[J].Journal of Northeastern University(Natural Science),2022,43(10):1513-1520.
Authors:YAN Zhen-ying  HAN Bao-ming  LI Xiao-juan  CAO Jin-xin
Institution:1. Transportation Institute, Inner Mongolia University, Hohhot 010020, China; 2. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China; 3. Inner Mongolia Academy of Science and Technology, Hohhot 010070, China.
Abstract:The flexible train formation brings limited flexible capacity for high-speed railway trains. The optimization of ticketing control of flexible capacity matches supply and demand more efficiently than that of fixed capacity. Based on the service network formed by multiple trains and multiple stops on the high-speed rail lines, tickets were set to multiple class fares according to revenue management. The preference order simulated the passengers’ choice behavior, and the ticketing time window controlled the pre-sale process. The joint optimization model of the formation scheme and the ticket closing time was established to maximize the total profit. Ticket sorting was designed according to ticketing needs, the model was transformed into a linear programming model, and it was solved quickly by CPLEX to obtain the optimal train formation and ticketing control strategy. The experimental results show that under the unsaturated demand market, the control strategy of the ticketing time window under flexible formation is more profitable than that under the fixed formation. The higher passengers’ arrival rate and transfer purchasing probability, the more units the train contains in the best formation.
Keywords:railway transportation  revenue management  preference order choice behavior  flexible train formation  ticket closing control  
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