Ticket Allocation Optimization of Fuxing Train Based on Overcrowding Control: An Empirical Study from China

Abstract

At the peak of passenger flow, some passengers extend travel sections, which will be likely to lead to overcrowding of high-speed railway (HSR) trains. Therefore, the problem of train overcrowding control needs to be considered in ticket allocation. Firstly, by simulating the passenger demand function and utility function, an optimization model of ticket allocation for multiple trains and multiple stops with the goal of maximizing revenue is constructed. Secondly, the concepts of the travel extension coefficient and risk coefficient are introduced, the number of passengers is estimated under the risk coefficient as the probability, and the total number of passengers on the train arriving at any station is obtained. Thus, preventing the number of passengers on the train from exceeding the train capacity is introduced to the ticket allocation optimization model of multiple trains and multiple stops as a constraint. Finally, this model is solved by the particle swarm optimization algorithm (PSO). The research results show that the idea of controlling passenger numbers so as not to exceed train capacity based on ticket allocation proposed in this paper has strong practical feasibility. By reasonably and accurately allocating the tickets to the departure terminal section and long-distance terminal sections, it can ensure that, even if there are some passengers extending their travel section, the train will not be overcrowded under a certain probability, improving the train safety and passenger travel experiences.