Research On Theory And Method Of Passenger Demand Oriented Ticket Allocation For High-speed Railway

In recent years,the large-scale construction and operation of high-speed railway has significantly improved the travel condition of passengers and to some extent alleviated short supply of railway passenger transport capacity.However,the utilization of seat capacity for high-speed train still faces severe challenge that the utilization of capacity is uneven.And with the reform and development of the market-oriented operation of high-speed railway,the passenger demand oriented operation management mechanism will become the trend of the future development for the railway company.In this background,aiming at the problems of existing ticket allocation methods,this paper introduces the passenger demand oriented revenue management theory to research the theory and method of passenger demand oriented high-speed railway ticket allocation with the high-speed railway ticket allocation as the research object,so as to improve the utilization of train seat capacity and better meet the passenger’s travel demand.This paper includes three aspects:high-speed railway ticket allocation considering passenger travel time,high-speed railway ticket allocation considering passengers,dynamic ticket booking demand and high-speed railway ticket allocation considering dynamic pricing.The proposed models and algorithms enrich the theory of dynamic pricing and ticket allocation for high-speed railway.The research work and conclusions of each part can be summarized as follows:(1)The method of high-speed railway ticket allocation considering travel time is studied.First,aiming at the influences of substitutability,difference and passenger choice behavior on ticket allocation,the comfort of the train is quantified by the fatigue recovery time of passengers.Then,on the basis of considering the differences of the running time,comfort and stop plan of the trains,the stochastic nonlinear integer programming model for ticket allocation of multiple high-speed trains is formulated by taking into account the travel time,with the aim of maximizing the system revenue of the railway company and the passengers.The simulated annealing algorithm is designed to solve the model.Finally,a case study is carried out with the Beijing-Shanghai high-speed trains as an example.The results show that the method can improve the system revenue of the railway company and passengers,reduce the passenger travel time and travel cost and the travel demand of long-haul passengers is better satisfied.(2)The method of high-speed railway ticket allocation considering dynamic ticket booking demand is studied.First,aiming at the differences of the passengers’ ticket booking behavior and the passengers’ticket booking process for different OD during the pre-sale period,on the premise that the passengers’ ticket booking process of different OD are quantified by compound non-homogeneous Poisson process,the stochastic nonlinear integer programming model for ticket allocation of multiple high-speed trains is formulated by taking into account the dynamic characteristic of passengers’ticket booking demand for different OD,with the aim of maximizing the system revenue of the railway company and the passengers.Then,the model is transformed into the deterministic linear integer programming model by demand simulation,which is solved by Lingo 12.0.Finally,the simulation of ticket booking process is carried out with the Beijing-Shanghai high-speed trains as an example.The results show that the method can improve the system revenue of the railway company and passengers.And on the premise that the trains seat capacity is fully utilized,the characteristic of passenger booking demand for different booking stage is better satisfied.(3)The method of high-speed railway ticket allocation considering dynamic pricing is studied.First,the elements of dynamic pricing for high-speed railway and passenger segment market are analyzed.Then,based on the analysis of passenger’s sensitivity towards ticket price in different booking periods,two kinds of robust optimization models of ticket allocation considering dynamic pricing under the conditions of determined demand with random error terms and the uncertainty of demand function coefficient are developed aiming to maximize the revenue,on the basis of revenue management theory and the characteristics of high-speed railway dynamic pricing and ticket allocation.The two kinds of robust optimization model are solved with the robust optimization methods.Finally,the feasibility and effectiveness of the methods are verified by concrete examples.The results show that the methods can adjust the passenger flow demand of different booking periods through dynamic price adjustment according to the demand characteristics of different booking periods,so as to improve the revenue.They are also better able to adapt to the demand fluctuation,so as to avoid the much work of ticket allocation adjustment when the ticket allocation scheme doesn’t meet the actual demand owing to the fluctuation of the actual demand;In addition,they can ensure that more tickets can be sold at a higher price.