Research On Optimization Of Ticket Allocation And Dynamic Pricing For High-speed Railway

In recent years,the great-leap-forward development of high-speed railway alleviates the pressure of increasing passenger travel demand to some extent,and improves passengers’ travel efficiency and travel conditions.However,under the existing pattern of ticketing organization and management,the matching degree between passenger demand and seat capacity of high-speed railway is relatively low,and the utilization of train seat capacity is uneven,which leads to the waste of train seat capacity and affects the improvement of high-speed railway revenue.Aiming at the deficiencies of ticket allocation and ticket fare making in ticketing organization management,this paper introduces revenue management theory to research the related problems of ticket allocation and dynamic pricing under the given train timetable and train line plan,so as to improve the utilization of the train seat capacity and railway passenger revenue,to meet the travel demand of different passengers.This paper includes three research contents:research on high-speed railway ticket allocation based on the decision-making preferences of railway department,research on dynamic pricing of parallel trains for high-speed railway based on passenger segment,research on differential pricing of non-parallel trains for high-speed railway based on passenger time value.The research work and conclusions of each part are as follows:(1)The method of high-speed railway ticket allocation based on decision-making preference of railway department is studied.Firstly,the uncertainty of OD passenger demand and the attitude of railway department’s decision-making preference are taken into account,and the a optimistic value of random variables is introduced to quantitatively describe the attitude of railway department’s decision-making preference.Then,considering railway department’s decision-making preference,the stochastic chance-constrained programming model for ticket allocation of multiple trains running on the high-speed railway under the uncertain passenger demand is formulated with the aim of maximizing the revenue of the railway company.The model can be converted to linear integer programming model that is easy to solve through the relevant theories and methods of uncertainty programming,which is solved using optimization software Lingo 12.0.Finally,taking the Beijing-Shanghai high-speed railway trains as an example,the results show that under different confidence levels,this method is better than the existing ticket allocation method,and the attitude of railway department’s decision-making preference has an impact on the ticket allocation.(2)The method of dynamic pricing of parallel trains for high-speed railway based on passenger segment is studied.First,under the single fare system,the attendance rate of the two trains which have the different departure time and the same or similar traveling time,and run on the same OD of the same high-speed rail line is unbalanced.To solve the problem,the passengers are subdivided based on the sensitivity of time,the sensitivity of fare and the preference of departure time,meanwhile the sensitivity towards price is characterized by the distribution of reservation price.Then,the joint pricing model of dynamic programming for discrete time is developed with the objective of maximizing the total expected revenue of the two trains.Finally,the relationship between the marginal expected revenue and the pre-sale time,the optimal pricing and the pre-sale time,the optimal pricing and the remaining seats for two trains are discussed through a specific example,and the dynamic pricing decisions of two trains under different demands are studied through the passenger ticket purchase simulation.The model can provide a theoretical basis for the dynamic pricing of multiple trains on high-speed railway.(3)The method of differential pricing of non-parallel trains based on passenger time value is studied.First,aiming at the impact of passenger time value on passengers’travel choice,the differences of departure time,travel time and comfort-ability among the different trains running on the same OD are quantitatively studied.Second,the time value model based on passenger choice utility maximization is formulated by using the theory of consumer choice behavior to calculate the time value of passengers taking different trains.Then,considering the impact of passenger’s time value on ticket price,the differential pricing model of non-parallel trains running on the same OD is formulated.Finally,taking the high-speed trains from Beijing west to Xi’an north as an example,the results show that the differential pricing of each train running on the same OD can be obtained using this method.Also,the differential pricing can balance the occupancy rate of each train and improve the utilization rate of train capacity through the analysis of passenger flow sharing rate.