基于收益管理的高速铁路票价与坐席分配联合优化  

Joint Optimization Method of High-speed Rail Ticket Price and Seat Allocation Based on Revenue Management

作　　者：秦进[1] 郝丽娜 毛成辉[1] 徐彦 曾艺佳 胡心磊 QIN Jin;HAO Lina;MAO Chenghui;XU Yan;ZENG Yijia;HU Xinlei(School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China;China State Railway Group Co., Ltd., Beijing 100844, China)

机构地区：[1]中南大学交通运输工程学院,湖南长沙410075 [2]中国国家铁路集团有限公司,北京100844

出　　处：《铁道学报》2020年第12期10-17,共8页Journal of the China Railway Society

基　　金：中国铁路总公司科技研究开发计划(N2018X009);中南大学研究生自主探索创新项目(2018zzts505,2018zzts027)。

摘　　要：高速铁路满足现代旅客出行需求,在其运量持续上升的同时,仍存在部分动车组列车客座率随时间波动较大而导致运力不足或运力浪费的现象。针对目前高速铁路票价机制单一,不能有效发挥引导客流合理分布和增加企业票价收益等问题,引入收益管理的思想和方法,提出考虑弹性需求的高速铁路列车动态定价和票额分配的联合优化方法,以各售票时段的票额限制和动态票价为决策变量,同时考虑各列车的票价上下限、列车运输能力等约束,以客票总收益最大化为目标构建优化模型,并基于蜂群算法设计高效求解算法。最后,以京沪高速铁路列车票价制定为例进行计算分析,结果表明:在不增加运力的情况下,所提出优化方法使高速铁路客票期望收益最高提升4.28%。China’s high-speed railway has been highly recognized by the market and passengers,but there are still some lines with large fluctuations over time in the seat rate,resulting in inadequate capacity or capacity waste.In view of the current fixed high-speed railway fare,which cannot guide the reasonable distribution of passenger flow or increase fare revenue,the related theory of revenue management was introduced,and the joint optimization method of high-speed railway dynamic pricing and seat allocation considering passenger elasticity demand was proposed.The optimization model was constructed with the goal of maximizing the total expected revenue,taking the seat allocation limit and dynamic fare of each ticketing period as the decision variables,while considering the constraints of the upper and lower limits of the price and the train transportation capacity.A solution method based on bee colony algorithm was designed.Finally,the calculation and analysis were carried out in the case of the ticket pricing of Beijing-Shanghai high-speed railway.The results show that without increasing the capacity,the proposed optimization method could increase the expected revenue by up to 4.28%.

关 键 词：铁路运输 高速铁路 票价 联合优化模型 人工蜂群算法 收益管理 

分 类 号：U293.2[交通运输工程—交通运输规划与管理]