In order to meet the transfer and transportation requirements of passengers and to significantly mitigate the loss of passenger flow that exceeds the waiting tolerance threshold, the optimization method of feeder bus scheduling considering the arrival time and passenger flow loss of rail transit trains was studied. The distribution of passenger flow demand was characterized by the passenger transfer demand and the arrival times of rail transit within the study period. The transfer time was described by the alignment between the time passengers arrive at the station of the bus and the bus departure schedule, as well as the operational capacity of the buses. The constraints of bus departure intervals, passenger flow loss and transfer demands were considered, and the multi-objective optimization with the minimum passenger flow loss, bus number and passenger transfer waiting time was realized under the limited number of buses that can be scheduled. Due to the contradictions among the optimization objectives, the model was solved with Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-II). Finally, taking the actual bus routes as an example, the results show that the optimized model takes into account the bus operation cost and the passenger transfer time cost, and can obtain the scheduling that meets the passenger flow demand and represents different priorities. When the number of feeder buses is the same, the total transfer waiting time of the optimized method is reduced by 8.0% compared with the uniform headway. The average factor under the uneven is 59.3%, which is better than the average factor of 50.2% under the uniform. The calculation results validate the effectiveness and rationality of the model and algorithm, effectively enhancing the match between the time and capacity of buses and urban rail transit.