| With the rapid development of the four major transportations of road,railway,aviation,and water,the competition among them has become increasingly fierce.At the same time,the global energy crisis and climate change make the environmental protection,energy saving and efficient transportation mode of railway transportation become more and more important.By the end of the 2017,the mileage of high-speed railways has reached 25,000 kilometers and the passenger traffic has reached 1.2 billion,four vertical and four horizontal high-speed rail network is basically completed.Therefore,it is urgent to expand the market share of railway transportation in order to enhance its competitiveness.Therefore,combining the applications of revenue management in the field of aviation and some forgine railway corporations with the current situation in our country,this paper analyzes the problems existing in the current high-speed railway passenger transportation in our country,clarifies the necessity and feasibility of introducing revenue management into the high-speed rail passenger transport.The dissertation mainly focuses on the revenue management of high-speed railway passenger transportation.From the perspective of passenger demand,this paper studies the existing problems in demand forecasting of high-speed rail passenger transport and puts forward the idea of"unconstrained”demand.High-speed railway passenger seat optimization model is built based on O&D ticket allocation strategy from the perspective of profit optimization.Through literature search,model construction and data analysis,the paper researches on the unconstrained high-speed railway passenger revenue management method from the following four aspects:(1)Through reading literature,this paper analyzes the background and significance of revenue management of high-speed railway based on unconstrained demand,introduces the research status at home and abroad,elaborates the theory of revenue management,in the respect of demand forecasting,differential pricing and inventory control.By analyzing the existing problems of the high-speed railways passenger transport,the feasibility of introducing revenue management into high-speed railway passenger transport is analyzed by comparing the similarities between aviation transport and high-speed rail passenger transport.(2)Based on the existing literature,the paper studies the revenue management of high-speed railway passenger transportation in our country.According to the demand forecast of high-speed railway passenger revenue management,there is "missing" in the history reservation data,which can not fully reflect the real demand of passengers.The paper constructs the unconstrained model of passenger demand for high-speed railways and takes the EM expectation maximization algorithm to solve the unconstrained demand.At last,a numerical example is used to prove the validity of the modle。(3)On the basis of the unconstrained demand research,according to the reason that the passenger demand is affected by many factors and the different routes of different trips involve more sections,the gray nerve network prediction method,combined with the advantages of gray prediction and neural network prediction,maps the transformed response function to the neural network structure,defines the weights between different layers,and determines the excitation function between different neurons.Thus demand forecasting for different OD is carried out.(4)According to the results of the demand forecast in Chapter 4 and the stock control allocation model in revenue management,a ticket allocation method based on O&D stock control is proposed.An precise pre-division model and a fuzzy pre-division model are established.Particle Swarm Optimization algorithm is used to solve.Finally,the results of a numerical example show that the ticket distribution based on O&D nesting can enhance the revenue of the railway department and bring certain economic benefits to the railway department while meeting the travel demand of passengers. |
PDF Full Text Request