Research on Assembly Sequence Optimization Based on Improved Particle Swarm Optimization

To address the issue of combination explosion in complex product assembly sequences, an interference matrix is established to characterize the assembly geometric relationship among components. The assembly stability is quantified using connection matrices and support matrices. Subsequently, a fitness function incorporating feasibility and stability as evaluation metrics is constructed to achieve multi-objective optimization. To prevent the algorithm from converging prematurely to local peaks, the inertia weight of the procedure is reduced nonlinearly, and the concept of mutation is introduced to improve the local search functionality. The feasibility and efficacy of the proposed algorithm in addressing the assembly sequence optimization problem are validated through a case study involving the assembly sequence planning for a control cabin.