Revenue Model for the Inter-City Railway System Based on the Stop Stations and Graded Ticket Fares

Abstract

With respect to the maximum revenue for the inter-city railway passenger transportation channel system with different grades of parallel trains, this paper has studied the matching relations between the system revenue and the passenger flow demand under confirmed demand conditions, analyzed the behavior selection process of passengers for trains with different speed grades within the channel, confirmed the passenger train flow transformation equation based on Logit sharing rate model as well as the collaborative optimization of stop stations and graded ticket fares, established the maximum revenue model of the system, and designed the hybrid particle swarm harmony search algorithm to solve the model. Besides, the new solution comparative law for the algorithm has also been formulated, which can improve the occurring probability of excellent solutions. Finally, verification has been made by taking Zhengzhou-Xi’an Railway Passenger Transportation Channel as an example, which has showed the effectiveness of the model and the algorithm, and the research results have showed that the redistribution of passenger flow realized through the stop stations and graded ticket fare policy can better improve the maximum revenue of the system.