高铁列车动态定价与预售时段划分综合优化方法  

Joint Optimization of Dynamic Pricing and Pre-sale Period Division for High-speed Trains

作　　者：许景 邓连波[1] 刘华儒 胡心磊 XU Jing;DENG Lianbo;LIU Huaru;HU Xinlei(School of Traffic and Transportation Engineering,Central South University,Changsha 410075,China)

机构地区：[1]中南大学,交通运输工程学院,长沙410075

出　　处：《交通运输系统工程与信息》2024年第5期259-267,共9页Journal of Transportation Systems Engineering and Information Technology

基　　金：湖南省自然科学基金(2023JJ30703,2023JJ40784)。

摘　　要：立足高铁收益亟需提高和灵活化市场票价体制实施的背景,本文考虑需求在预售期内各天的波动性和差异性,以及预售时段划分方案对铁路收益的影响,研究高铁列车动态定价与预售时段划分的综合优化问题。为预售期内每天构建独立的弹性需求函数,考虑列车能力约束、需求约束及票价递增约束等条件,建立高铁列车动态定价与预售时段划分综合优化大规模非线性模型。根据模型特点,设计双层遗传—模拟退火算法求解,将优化问题分为外层预售时段划分、内层动态定价与票额分配的双层优化问题,内外两层分别采用遗传算法和模拟退火算法求解。最后,采用一个数值算例验证优化模型和求解算法的有效性,并探讨不同预售时段数量下的划分结果。结果表明,随预售时段数量的增加,预售期的划分主要集中在后半段;预售时段数量为5时,优化后,该数值算例的收益提高了约1.21%。Based on the need to enhance high-speed rail revenue and implement a flexible market ticket pricing system,this paper focuses on the joint optimization of dynamic pricing and pre-sale period division considering the demand fluctuations and differences on each day during the booking horizon,as well as the impact of the pre-sale period division on railway revenue.Separate elastic demand functions are constructed for each day.A large-scale nonlinear model is developed to optimize the dynamic pricing and pre-sale period division for high-speed trains in consideration of the train capacity constraints,demand constraints,and price-related constraints.To solve the optimization problem,a bi-level genetic-simulated annealing algorithm is designed according to the model's properties.The optimization problem is divided into an outer-level pre-sale period division problem and an inner-level dynamic pricing and seat allocation problem,which are solved by genetic algorithm and simulated annealing algorithm,respectively.At last,a numerical instance is provided to evaluate the effectiveness of the optimization model and solution algorithm,and the results for different numbers of pre-sale period are discussed.The results indicate that as the number of period increases,the division of the booking horizon primarily concentrates on the latter half.For a case with five periods,the optimized revenue increased by approximately 1.21%.

关 键 词：铁路运输 动态定价 双层遗传—模拟退火算法 高铁列车 时段划分 席位分配 

分 类 号：U293.1[交通运输工程—交通运输规划与管理]