Civil aircraft aviation spare parts inventory configuration method based on improved particle swarm

In order to solve the problem that the existing civil aircraft aviation spare parts inventory configuration method is prone to fall into the local optimal solution in large-scale configuration, it is proposed to establish a two-level civil aircraft aviation spare parts inventory model through the multi-echelon technique for recoverable item control theory. On this basis, the aviation spare parts configuration optimization is performed based on the improved particle swarm optimization (PSO) algorithm. The algorithm simplifies the optimization objective based on the aviation spare parts inventory model, and improves the particle swarm initial point strategy and speed update function to overcome the defect of falling into the local optimal solution. Taking civil aircraft aviation spare parts configuration plan as an example, the configuration amount of the improved PSO algorithm is reduced by 16.3% compared with the traditional marginal analysis method, which shows the effectiveness of the proposed improved PSO in civil aircraft aviation spare parts configuration. Improved PSO algorithm provides a theoretical reference for civil aircraft aviation spare parts configuration.