Research On Short-term Passenger Flow Volume Forecasting And Ticket Assignment Optimization For Beijing-Shanghai High-Speed Railway

Since the Beijing-Shanghai High-Speed Railway (HSR) opened, the passenger flow has been growing year by year, due to its characteristics as speedy, comfortable and on time performance. Moreover, the situation has been changed from the overall low passenger load factor at the beginning to today’s hard purchasing for the tickets in many legs. To deal with the increasing capacity pressure to HSR operation, a delicacy management is required. For example how to reasonably use the capacity of HSR for improving overall load factors and its revenue.Based on the airline industry’s Revenue Management system and existing research achievements, this paper made the following research works:(1) Considering the problems in current HSR tickets allocation management, it is proposed by reference to airline industry which had a successful application of RM (Revenue Management) system. Then combine its own characteristics of HSR to make applicability analysis on RM system.(2) An improved BP neural network was proposed for short-term passengers flow volume forecasting, which will provide data support for the ticket allocation strategy. Moreover, this paper analysis the passenger flow distribution and factors which influencing the fluctuation. The results of case experiment show that the presented approach improves the accuracy of forecasting significantly.(3) We further build tickets’allocation model for HSR in the booking period based on the nest strategy and non-nest strategy. Then, according to different model structure characteristics and number of variables, different corresponding algorithms were put forward. Lastly, we compared the allocation effectiveness at different date types and models based on two strategies.The models and corresponding solutions for above problems, on the one hand, can improve the operation effectiveness of Beijing-Shanghai HSR, then raise its overall benefits and protect the interests of the long-distance passengers, and optimizing the capacity utilization. On the other hand, it will be an important part of HSR revenue management system. Therefore, this research of short-term passage flow volume forecasting and ticket allocation for HSR has important theory value and practical significance.