In order to reduce the passenger delay in the transfer journey, the optimization model is set up to minimize the total delay between the transfer passengers and the subsequent flight passengers when considering the delay of the subsequent flight passengers in the transit process. The stud genetic algorithm is applied to solve the model under the constraint of flight operation. An example is given to verify the passenger flow data of Beijing Capital International Airport, and the optimization results of the minimum connecting time for different passengers are compared. The results show that compared with classical genetic algorithm and strengthen elitist genetic algorithm, stud genetic algorithm has a faster convergence rate. With the minimum connecting time of 120 minutes, the passenger delay during the optimized transfer journey was reduced by 29.9%. When the passenger connection time is shorter, the passenger delay will be less, and the optimization effect of the model is relatively stable, with the optimization percentage between 25% and 30%.