A Comprehensive Study On Multi-Stage Ticket Price Of High-Speed Railway Considering Passenger Purchasing Behavior

With the advancement of high-speed railway construction in recent years,increasing in operation of the rail line,passenger travel demand has been further meet,travel choice also enriched.Volatility,however,because of the complexity of the traffic demand and the present fixed ticket allocation and price strategy is difficult to satisfy the increasing traffic demand,has become the important obstacles to raise the capacity of railway operation.In this paper,from the perspective of passengers’ actual purchase behavior,the ticket pre-sale period is divided into multiple stages.In the multi-train high-speed rail network,the actual purchase behavior of passengers is simulated,the combined optimization method of ticket amount and ticket price on each OD is studied,and a multistage stochastic nonlinear programming model is established.Through the distribution of the stages model to solve the ticket and the ticket price adjustment scheme and is verified by an example.The specific work of this paper is as follows:Firstly,starting from the choice behavior of passengers,according to the development status of high-speed railway in China,the competition between high-speed railway and other modes of transportation is analyzed,the existing methods of ticket allocation and fare adjustment are summarized,the problems existing in ticket allocation and fare formulation at the present stage are pointed out,and the theoretical content of multi-stage ticket amount and fare adjustment in the pre-sale period is summarized.Then,with a period of time,in this paper,based on high-speed rail passenger flow rule,high-speed each OD random demand is obtained by simulation method,finally established the passenger ticket behavior simulation process,the passengers from the practical perspective,the dynamic of passenger flow distribution of the secondary.On the premise of passenger travel choice,according to the random of the density of passenger flow and ticket price,the railroad department profit maximization as the goal,construct multistage fare ticket allocation and optimization model.According to model characteristics,select the particle swarm algorithm to solve,and improved algorithm selection process,the solution of the model is more suitable.And put forward suitable for multi-phase flow dynamic adjustment algorithm,target date for the rest of the passenger flow for dynamic adjustment.By means of case analysis,finally,a comprehensive optimization model is set up,get under random traffic demand fare ticket allocation and adjustment plan.The scheme without passenger flow adjustment is set as the control group,and the feasibility and rationality of the model and algorithm are verified by comparative analysis of the two schemes,which provides some suggestions for railway departments to formulate ticket allocation and fare adjustment schemes.