The study of train speed profiles plays a crucial role in optimizing the train operation process for urban rail train. To achieve better optimization results of train speed profiles, aiming at the three goals of train running punctuality, running energy consumption and passenger comfort, an approach based on an improved multi-objective differential evolution algorithm is proposed. Firstly, a multi-objective optimization model for urban rail transit trains is established based on the train operation process. Then, by adopting an elite mirror initialization strategy, ntroducing parameter adaptation and multi-mutation strategies, the performance of the multi-objective differential evolution (MODE) algorithm is improved, and by comparing with the IGD values obtained by the other 6 comparison algorithms on the ZDT series test functions, the superiority of the proposed algorithm is verified. Finally, combined with the real line data of Nanchang Metro Line 1, the simulation results show that the improved MODE algorithm has certain advantages in comprehensive performance compared with the comparison algorithm, and has strong practicability in train energy-saving optimization problems.