Abstract: To study the multi-objective rush order insertion rescheduling problem under hybrid flow shop with multiple stages and multiple machines, the constraints, such as job lots, sequence-dependent set-up times, and round-trip transportation times, were simultaneously considered. A static optimal scheduling model of initial orders was first established to minimize the maximum order completion time and minimize the total transportation time. The non-dominated sorting genetic algorithm (NSGA)-II algorithm was applied to solve a two-objective optimal problem. Then, for the rush order insertion disturbance factor, the objective to minimize the total machine deviation between the initial scheduling and rescheduling plans was added as a stability index to establish an optimal rush order rescheduling model. The NSGA-III algorithm based on the event-driven rescheduling strategy and order rearrangement strategy was applied to solve a three-objective optimal problem. Finally, a realistic ship pipe parts manufacturing enterprise is regarded as a study case. Two sets of experiments are carried out to explain the motivation of the selected method. The performances of the NSGA-II and NSGA-III algorithms are evaluated by three metrics, including the mean ideal distance, spread of non-dominated solution, and percentage of domination. The results show that the NSGA-II algorithm is more suitable for solving two-objective optimal problem, whereas NSGA-III algorithm performs better in solving three-objective optimal problems. Then, the proposed model and method were applied to 10 rush order insertion cases of the enterprise. All the three objectives were improved according to the compared results obtained by the actual and optimal scheduling. The optimal rate is close to one third, which verifies the feasibility of the proposed model and the effectiveness of the proposed method. The proposed model and method may assist other enterprises that apply make-to-order production mode to reduce the impact of rush order insertion and realize a win-win mechanism between enterprises and customers.