| As an important way of passenger transport in China,high-speed railway occupies a large share in the middle and long distance intercity passenger transport market.With the large-scale construction and operation development of high-speed railway network,the situation of short supply of railway transportation is gradually becoming a thing of the past.However,the full use of seat capacity at present is still a challenge,especially when tickets demand is quite big.The unreasonable ticket allocation is more likely to cause uneven distribution of seats,not only can reduce the efficiency of train carrying capacity,will also seriously affect the passenger ticket to experience,resulting in the loss of passenger flow and operating income loss.In this context,the paper proposes a collaborative optimization model of ticket allocation through dynamic ticket price to adjust passenger flow demand,so as to balance ticket demand distribution among different trains,and ultimately improve the overall passenger load factor and operation efficiency of high-speed railway.First of all,based on relevant literature,the paper summarizes the research status,main principles and methods of high-speed railway ticket allocation and revenue management theory,and focuses on the factors affecting passengers’ ticket purchasing behavior.Secondly,combined with SP/RP survey method and uniform experimental design strategy,the paper conducted a lot of research through online questionnaire to analyze different passengers’ ticket choice preferences.Meanwhile,combined with the latent class theory,the paper divides different travelers into four groups according to the survey results,which can improve the computational processing accuracy in the follow-up research.Thirdly,based on the choice preference data of interviewed passengers,the paper calibrates the data through Multinomial Logit Model,and calculates the choice utility parameters of various passengers for train ticket price,departure time,journey length and comfort level.According to the utility function of ticket selection,the paper establishes the arrival and transfer model of ticket demand for different types of passengers.Finally,based on passengers’ ticket purchasing behavior during the high-speed railway train presale,the paper constructs a collaborative optimization model of ticket allocation under dynamic ticket price,which is constrained by the upper and lower price limits and train seat capacity.This paper takes two trains running on Beijing-Shanghai High-Speed Railway as an example,and uses genetic algorithm to calculate and solve the optimization model.The results show that the collaborative optimization model of ticket allocation under dynamic ticket price can effectively adjust the distribution of passenger flow on different trains.Moreover,it is also beneficial to increase the income of high-speed railway organization. |
