Abstract: Objectives Aiming at the characteristics of high coupling of tasks and fuzzy support time in ammunition support operation of carrier aircraft, this paper proposes a two-stage optimization method to realize the balance of task allocation and the robustness of operation scheduling. Methods In the first stage, Unity is used to build the aircraft carrier deck environment, and the hybrid A* algorithm is used to plan the collision-free shortest path, with the goal of minimizing the maximum total task path distance of ammunition buffer areas; In the second stage, the ammunition transportation scheduling problem is formalized to a flexible job shop scheduling problem with fuzzy processing time, and an adaptive genetic algorithm integrated with teaching-learning-based optimization is designed for solving it. Results Experimental results show that the fuzzy completion time of the proposed method is reduced by 1.9%-3.1% compared with that of the baseline algorithm in the ammunition transportation scheduling problem in four ammunition buffer areas, and the proposed algorithm converges stably; In the benchmark tests of the fuzzy flexible job shop scheduling problem, the proposed algorithm obtains the optimal solutions in all instances, verifying its effectiveness and generalization.Conclusions The fuzzy scheduling of ammunition transportation can provide valuable insights for solving the scheduling of carrier-based aircraft support operations in uncertain environments, and the proposed algorithm can be applied to various scheduling problems that can be modeled to general fuzzy flexible job shop scheduling problems.