Critical engineering challenges in aviation ammunition operation and support for large warships are recognized, including high operational complexity, limited onboard space resources, stringent timeliness requirements, and diverse mission scenario transitions.In order to address these challenges and realize accurate and efficient multi-scenario aviation ammunition transshipment scheduling, the optimal design of aviation ammunition transshipment schemes for large warships was investigated. Three mission scenarios (combat, routine training, special window-period training) were classified. A bi-level nonlinear integer programming scheduling model was constructed, with ammunition transporters as the basic optimization unit, and mission completion time, number of deployed transporters, and load balancing degree as optimization objectives. An improved hierarchical-coded Stellar Oscillation Optimizer (SOO) was adopted, and random key strategy and simulated annealing mechanism were introduced to enhance algorithm performance.The results show that the proposed model can effectively generate scenario-adaptive aviation ammunition transshipment schemes. Compared with traditional intelligent algorithms, the improved SOO algorithm presents significant advantages in solution quality, convergence and stability.It is concluded that the proposed method can provide timely and effective decision-making basis for aviation ammunition transshipment, scheduling and support operations of large warships under various scenarios.