Train operation adjustment of the urban rail transit based on dwell time model

Train operation adjustment (TOA) plays an important role in ensuring transportation order and enhancing transportation efficiency, the purpose of TOA is to make the error between actual schedule and planned schedule as small as possible, According to the influence of passenger flow on train delay, this paper builds a novel multi-objective train adjustment model by incorporating the dwelling time model of trains in each station. In order to resolve the proposed TOA problem, we introduce the mutation gene and the hybrid gene to improve the PSO algorithm. Finally, simulation results verify the validity of the introduced model and the better performance of the improved algorithm with respect to the normal PSO algorithm.