ABSTRACT As the reform of China Railway ticket pricing deepens, the implementation of differentiated and dynamic pricing for parallel trains has emerged as a key strategy for railway operators to enhance revenue. This study examines the joint optimisation problem of ticket pricing and seat allocation from the perspective of passenger decision‐making between two parallel trains, considering passenger demand shifts during the pre‐sale period. First, passengers are classified into two groups, and their ticket‐purchasing behaviour is analysed. Second, treating ticket price and seat allocation as decision variables, the pricing adjustment range is constrained using the PSM model. Additionally, a joint optimisation model is developed to ensure optimal utilisation of train seat capacity, with the objective of maximising total revenue across both parallel trains. A particle swarm optimisation algorithm is proposed to solve the model. Finally, the model and algorithm's validity are tested through case studies of trains G2457 and G2473 in China. The results show that the joint optimisation strategy increases revenue by 4.79% compared to the fixed ticket pricing scheme. Sensitivity analysis further investigates the impact of various parameters on the results. This study provides valuable insights for decision‐making in railway transportation, contributing to the sustainable development of the industry.
Yin et al. (Thu,) studied this question.
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