Cooperative Optimization of Seat Control and Ticket Price for High-Speed Rail Passenger Transport

With the rapid construction of the high-speed railway in China, the operational efficiency and revenue performance are getting more and more attention from operators. In this paper, the idea of revenue management is adopted to adjust the passenger flow of parallel trains through differential pricing considering the preference of passengers for different parallel trains. Based on utility theory, the Multinomial Logit model is used to describe passengers’ choice behavior among parallel trains, and a cooperative optimization model for ticket price and seat control of high-speed rail network with multi-train and multi-stop stations is established. At the same time, the optimization strategy of differential pricing and seat control of parallel trains is obtained. The validity of the model is proved by numerical experiments based on the train of Beijing-Shanghai high-speed railway. The optimization polices of this model in this paper can provide optimization strategy for the revenue management of high-speed parallel trains and enrich the synchronous optimization theory of capacity control and pricing in revenue management.