LAUSR

In the paper, PSO algorithm is used to solve the assembly sequence planning problem. According to the analysis and extraction of fixture assembly information, a complete and correct fixture assembly model is established in which PSO algorithm is introduced, including assembly direction matrix, interference matrix, sequence-relation matrix, etc. Taking shorten the assembly time as the optimization goal, the feasible assembly sequences for specific fixture are obtained using PSO algorithm and the optimal assembly sequence is found. The influence of main factors on PSO algorithm is analyzed. With the increase of population, the chance to find the optimal solution increases. When $$\upomega $$ω and $$\hbox {c}_{1}$$c1 increase and $$\hbox {c}_{2}$$c2 decreases, it is good for global searches of the PSO algorithm. When $$\upomega $$ω and $$\hbox {c}_{1}$$c1 decrease, and $$\hbox {c}_{2}$$c2 increases, it is good for local searches of the PSO algorithm. In practical applications, the factors should be adjusted according to specific problems.