Assembly Sequence Optimization Based on Improved PSO Algorithm

For the structural characteristics of products, the interference matrix is established according to the assembly direction, and the optimization of product sequence assembly planning is studied with the aim of maximizing the number and stability of parts assembled without interfering with the assembled parts and minimizing the number of changes in assembly direction. Aiming at the problem of low convergence speed and precision of basic PSO algorithm, a population initialization method based on Feigenbaum iteration is proposed, and a new inertia weight update function is designed to improve the basic PSO algorithm with reference to Sigmoid function. The performance of the proposed algorithm is verified by an assembly example. The results show that the improved PSO (IPSO) algorithm is effective and stable in solving assembly sequence optimization problems.