Research On Joint Optimization Of Pricing And Seat Allocation For High-speed Railway

In recent years,the scale.of China's high-speed railway network has been gradually expanded,which promotes the ecomomice development of the regions along high-speed railways and changes the situation that railway passenger transport is short supply.However,compared with a regular-speed railway,an HSR requires more capital to construct the infrastructure and has higher operation costs.It is not conducive to the sustainable development of high speed railway to simply consider the social benefits of high-speed railway and ignore its revenue problem.Revenue management is an effective method to make rational use of the seat resources,meet the diversified demands of passengers and improve the competitiveness of high-speed railway market and passenger ticket revenue.This paper mainly studies the method of ticketing organization of high-speed railway,and focuses on the influence of multiple trains,multiple train stop plans,multiple fares,customer choice behaviour,differential pricing,integrated optimization of ticket prices and ticket allocation,dynamic control,etc,on the revenue management of high-speed raiway.Our work can provide the theoretical and methodological support for reasonable matching of seat resources and passenger demand and improving passenger ticket revenue.Specific research contents include:(1)As one origin-destination itinerary can be serviced by multiple passenger trains with alternative to each other,the method of passenger flow assignment being conducted first before ticket allocation can hardly ensure optimal ticket allocation plans of all passenger trains.For this problem,we put forward a method of ticket allocation under the conditions of multiple trains and multiple train stop plans.A nonlinear integer programming model is established with seat restriction as decision variables,which is solved using particle swarm algorithm.After verification of the model and algorithm by an example,the method proposed in this paper is compared with the method of passenger flow assignment being conducted first before ticket allocation.(2)The current ticketing organization of high-speed railway adopts a single fare during the entire sales horizon,which not only restricts the improvement of the ticket revenue,but also is lack of stimulating the passenger demand.In addition,the current ticketing organization ignores customer choice behaviours.For the above problems,we propose a multiple fare ticket allocation model for homogenous seats considering customer choice behaviours.An efficient heuristic approach is proposed to solve the proposed model.The Beijing-Shanghai HSR is taken as a case study.Finally,our method is compared with the current single fare ticket allocation method.(3)Multiple trains of high-speed railway for a same origin-destination itinerary are alternatives to each other.Passengers prefer to select trains with better start time and less travel time,which will result in that partial trains' tickets are nervous and other trains' tickets are redundant.Hence,this paper considers the influence of differential pricing strategy on customer choice behavior.In order to match seat capacity with passenger demand,we propose an integrated optimization model of differential pricing and ticket allocation for multiple trains and develop a hybrid heuristic algorithm to solve the model.(4)Based on stochastic passenger demand and customer choice behaviour under the condition of competition among multiple modes of transportation,study on the integrated optimization method of high-speed railway ticket pricing and allocation.Flexible pricing,which considers off season and peak season demand and customer choice behaviour,is adept in stimulating market demand and improving competitive advantage.Ticket allocation is an important method for reasonable utilization of ticket resources of long distance and short distance.This paper put forward a model which can integrated optimizing ticket price and ticket allocation,while designing a hybrid heuristic algorithm according to the characteristics of the model.After verification of the model and algorithm by an example,the method proposed in this paper was compared with the method with fixed ticket price and without considering customer choice behaviour.(5)Under the competitive environment of multiple modes of transportation,because passenger demand and competitors' strategies are dynamic changing,it is required to adopt a dynamic control method for the revenue management of high-speed railway.Based on the dynamic characterstics of the system,an integrated optimization model for dynamic pricing and ticket allocation is proposed,and two solution methods are designed for solution efficiency and solution quality.The validity of the two proposed algorithm and the application of the model are verified by numerical experiments.