Abstract: The models and methods of spare parts inventory strategies that allow for complete sharing or unidirectional transshipment may not necessarily be applicable to all spare parts support systems. The inventory optimization problem of single echelon support systems is studied to further optimize the spare parts inventory strategy and operating cost of airlines, allowing mutual transshipment among multiple bases with incomplete sharing of repairable spare parts. The inventory of the system and bases is analyzed respectively according to Poisson distribution and Markov process theory. On this basis, an optimization model is established for the inventory of spare parts considering incomplete transshipment with the comprehensive support rate and the support rate of each base as constraints, and the objective being the minimum of total system cost. Then, the iterative algorithm and particle swarm optimization algorithm are constructed for solving the optimization problem. The results of AnyLogic simulation and sensitivity analysis of key parameters show that: the maximum relative error of each base support rate is 0.06, and the maximum relative error of the total system cost is 0.31% by comparing the optimization method and simulation calculation under the optimal configuration strategy in different situations. These results meet or very close to the target support rate requirements. Sensitivity analysis and error analysis show that the proposed model and algorithm are feasible and effective.