Differential Pricing Optimization of High-speed Railways Based on Discrete Price

Different from most existing studies focusing on continuous pricing, this paper proposes a differentiated pricing optimization model for high-speed railways based on discrete prices. Firstly, a set of discrete discount rates is set, and railway passengers are classified according to their price sensitivity. Considering that the departure and arrival times in the different periods bring additional opportunity costs to passengers, a generalized cost function for each group of passengers is obtained, which is summarized as the overall passenger elastic demand function. We develop a linear integer programming model with multi trains and multi sections with an objective of revenue maximization. Finally, a PSO algorithm is used to solve the model. The numerical results show that the optimization model proposed in this paper can significantly improve the overall revenue. Moreover, the case using the continuous optimal price in most pricing theories can be regarded as a special case of the discrete pricing optimization problem. The discrete pricing fits the practice better, which should be attracted more attention