Differential Pricing Optimization Method For High-Speed Railway Based On Cumulative Prospect Theory

China’s high-speed railway(HSR)currently mainly adopts fixed fares.It follows the principle of flat tariffs and decreases with increasing distance.The fares for the same class of seats aboard different trains are the same.Fixed fares cannot be adjusted scientifically and flexibly to reflect market situations,which not only reduces passenger satisfaction,but also limits the profitability.Differential pricing refers to the careful implementation of product price fluctuation rights based on demand conditions,market composition and other factors,and make the establishment of different prices for products and services that are mutually replaceable.This pricing strategy has been a major success in markets such as hospitality,fresh produce and energy.High-speed railway products also exhibit high substitutability,quality differences,and fluctuating demand.Therefore,drawing on successful experience,analyzing the elastic demand and exploring scientific and reasonable differential pricing methods for HSR have become key issues to be solved urgently.This thesis takes the maximization of ticket revenue as the starting point to study the differential pricing of HSR.Firstly,sort out the successful experience of differential pricing and the HSR fare mechanism at home and abroad,summarize the connotation,necessity and applicability of HSR differential pricing.Secondly,expound the influence of trip characteristics on passengers’ choice behavior,use the latent class(LC)model to classify passengers into business type and leisure type.Thirdly,introduce the cumulative prospect theory(CPT)to describe the bounded rationality of passengers,construct the elastic demand function based on CPT and prove its rationality through an example.Finally,on the basis of elastic demand,establish an integrated optimization model of differential pricing and seat allocation,which aiming at maximizing ticket revenue and considering the constraints of train capacity,pricing fluctuation range,noninverted pricing and minimum seat number.Use a non-stationary multi-stage assignment penalty function to address the noninverted pricing constraints.Solve the model based on an improved gray wolf optimizer.Finally,certain HSR trains operating on the Beijing-Shanghai line are given as examples.Without investing more transportation resources,the total revenue of passenger tickets increased by 4.67%compared to the fixed rate.The passenger flow is more balanced among different trains.In the case of abundant resources,differential pricing can give full meaning to the medium and long-haul transportation advantages of HSR.The differential pricing optimization method of HSR proposed in this thesis enriches the HSR fare system and provides theoretical support for the market-oriented operation of HSR in my country.This thesis has a total of 37 figures,20 tables,and 85 references.