Abstract
Differential pricing of trains with different departure times caters to the taste heterogeneity of the time-dependent (departure time) demand and then improves the ticket revenue of railway enterprises. This paper studies optimal differential pricing for intercity high-speed railway services. The distribution features of the passenger demand regarding departure times are analyzed, and the time-dependent demand is formulated; a passenger assignment method considering departure periods and capacity constraints is constructed to evaluate the prices by simulating the ticket-booking process. Based on these, an optimization model is constructed with the aim of maximizing the ticket revenue and the decision variables for pricing train legs. A modified direct search simulated annealing algorithm is designed to solve the optimization model, and three random generation methods of new solutions are developed to search the solution space efficiently. Experimental analysis containing dozens of trains is performed on Wuhan-Shenzhen high-speed railway in China, and price solutions with different elastic demand coefficients ( ϕ ) are compared. The following results are found: (i) the optimization algorithm converges stably and efficiently and (ii) differentiation is shown in the price solutions, and the optimized ticket revenue is influenced greatly by ϕ , increasing by 7%–21%.
Highlights
Intercity high-speed railways serve passengers that are located in densely populated metropolitan areas or city clusters. ey feature high departure frequencies and high speeds, not less than 250 km/h
Algorithm with each elastic coefficient. e ticket revenue of the optimized solution is denoted as Z∗. e test obtains 30 optimized solutions for each elastic coefficient, and the biggest ticket revenue of these solutions is selected, called the best Z∗. e average ticket revenue of these solutions is calculated, called the average Z∗. e achieved proportion of the best Z∗ after 200 cooling iterations is denoted as AP. e statistical results of Z∗ for each elastic coefficient are shown in Table 4, where the last column is the increase in the proportion of the best Z∗ compared with Z0. e relative
To analyze passenger choice behaviors between trains, a time-dependent demand formulation is determined based on the historical ticket reservation data, and a passenger assignment method considering departure periods and capacity constraints is constructed by simulating the ticket-booking process
Summary
Intercity high-speed railways serve passengers that are located in densely populated metropolitan areas or city clusters. ey feature high departure frequencies and high speeds, not less than 250 km/h. Since 2016, the ticket prices of part high-speed trains have been floated within certain limits on several lines (Beijing-Shanghai high-speed railway and Hangzhou-Shenzhen railway) because pricing power has been devolved to the railway transport enterprise in China. Train prices of most high-speed lines in China are still unitary for the same train leg and fixed which have seriously affected the market competitiveness of intercity high-speed railways. According to the passenger characteristics in the railway transportation market, optimal pricing methods for intercity high-speed railways are studied in this paper, which are of great significance for improving railway operation and management mechanisms and increasing the economic revenue of railway transportation enterprises. Determining the optimal pricing of intercity high-speed railways is a revenue management problem, and revenue management methods have been studied for decades and widely applied in the railway industry in Europe and Japan [1, 2].
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