A hybrid assembly sequence planning approach based on discrete particle swarm optimization and evolutionary direction operation

2013 ◽  
Vol 68 (1-4) ◽  
pp. 617-630 ◽  
Author(s):  
Mingyu Li ◽  
Bo Wu ◽  
Youmin Hu ◽  
Chao Jin ◽  
Tielin Shi
2012 ◽  
Vol 13 (1) ◽  
pp. 732-738 ◽  
Author(s):  
Jameel A. A. Mukred ◽  
Zuwairie Ibrahim ◽  
Ismail Ibrahim ◽  
Asrul Adam ◽  
Khairunizam Wan ◽  
...  

2009 ◽  
Vol 16-19 ◽  
pp. 1228-1232 ◽  
Author(s):  
Hong Yu ◽  
Jia Peng Yu ◽  
Wen Lei Zhang

Assembly sequence planning (ASP) is the foundation of the assembly planning which plays a key role in the whole product life cycle. Although the ASP problem has been tackled via a variety of optimization techniques, the particle swarm optimization (PSO) algorithm is scarcely used. This paper presents a PSO algorithm to solve ASP problem. Unlike generic versions of particle swarm optimization, the algorithm redefines the particle's position and velocity, and operation of updating particle positions. In order to overcome the problem of premature convergence, a new study mechanism is adopted. The geometrical constraints, assembly stability and the changing times of assembly directions are used as the criteria for the fitness function. To validate the performance of the proposed algorithm, a 29-component product is tested by this algorithm. The experimental results indicate that the algorithm proposed in this paper is effective for the ASP.


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