Comprehensive optimization of dynamic pricing and passenger flow assignment for differentiated high-speed train products

Abstract

In the context of high-speed railway marketization, devising a scientific dynamic fare strategy to achieve an efficient match between train supply and passenger demand is a pressing issue. Dynamic pricing and passenger flow assignment were placed into the same framework to achieve collaborative optimization. On the demand side, the space-time service network for the train timetable was constructed. A bidirectional breadth-first reasonable route search algorithm and passenger travel choice cost formula were proposed. The passenger choice behavior parameters were derived from revealed preference (RP) and stated preference (SP) surveys. On the supply side, differentiated train products were classified by the station level and the station number and were connected to the fare adjustment strategy. To solve the comprehensive optimization problem of dynamic pricing and passenger flow assignment, a differential pricing biobjective comprehensive optimization model was developed, and a multidimensional passenger flow assignment strategy was employed. Based on real data, the Beijing–Shanghai high-speed railway was used as a case study, and the station level, OD (Origin-Destination) level, train classification, fare adjustment strategy, enterprise revenue, train indices and OD fare were analyzed. The case study verified the effectiveness of the fare adjustment strategy based on differentiated train products and provided a novel approach for the marketization of high-speed railways.