Synergetic Optimization Of Ticket Price And Ticket Amount Of High-speed Railway Based On Revenue Management

With the market-oriented reform and development of railway transport enterprises,the relatively single and fixed ticket allocation mode and fare form can not meet the rapid development of China’s railway passenger transport demand.On the one hand,the passenger demand matching degree of the ticket allocation scheme before the pre-sale period is not high,resulting in the coexistence of tension and deficiency in the utilization of train seat capacity,resulting in the waste of train seat capacity;on the other hand,the static ticket price and the fixed pre-allocated ticket amount in the pre-sale period do not consider the distribution law of the passenger purchase in the pre-sale period,which is not conducive to mobilizing the vitality of the passenger market,but also hinders the further excavation of the potential revenue.Starting from the limitations of the existing high-speed railway ticket allocation and ticket price forms,this paper introduces the theory of revenue management to study the related problems of ticket allocation and dynamic pricing,in this paper,we construct and validate the pre-sale and pre-sale models,and the co-optimization models of pre-sale and pre-sale prices:(1)Using the theory of revenue management for reference,this paper expounds the current floating ticket price mechanism and the ticket allocation process and strategy in China’s highspeed railway,and combines the problems existing in the current ticket allocation and floating ticket price system,make clear the research optimization goal of this paper.(2)Before the pre-sale period,in view of the stochastic and time-varying demand of passenger flow,a random variable and a fuzzy degree value are introduced to quantitatively characterize the fuzzy degree in the pre-sale of tickets,a ticket allocation model based on stochastic chance constraints is constructed,and the model is solved according to the econstraint method and some theorems and propositions of uncertain programming theory.(3)To analyze the behavior of passenger purchasing tickets during the pre-sale period,and to simulate the process of passenger purchasing tickets in each section by using nonhomogeneous Poisson process.On the basis of the pre-allocation scheme,a bi-decision variable stochastic Nonlinear programming model for the co-optimization of ticket price and ticket amount during the pre-sale period of a single train is established according to the simulation results,particle swarm optimization algorithm is designed to solve the model.(4)Analyze the feasibility of revenue management of Beijing-shanghai high-speed railway from the angle of location factor and passenger revenue.Based on the passenger flow data of G19 trains running on Beijing-shanghai railway line,a case study is made on the model of presale tickets,and the sensitivity of the model is analyzed by adjusting the fuzzy value of pre-sale tickets The collaborative optimization model of ticket price and ticket amount during the presale period of G19 trains is analyzed by using the pre-sale data of G19 trains,the sensitivity analysis of the model was carried out by taking the price elasticity of demand and its decreasing law as the influencing factors.In this paper,the pre-allocation model and the co-optimization model of ticket price and ticket amount are established.Before the pre-sale period,the railway transportation enterprises may,according to the passenger demand of each section,in the pre-sale period,the average utilization ratio of the passenger seat of the train does not decline significantly,and the revenue of the train ticket is increased slightly.