A SEQUENCING APPROACH OF MODELS IN MIXED-MODEL ASSEMLY LINES

Zheng Yongqian, Wang Yunpeng, Hu Bo, Wang Yongsheng

Abstract


Sequence planning of different models for a mixed-model assembly line is crucial for its efficiency. This paper formalized this model sequencing problem based on minimizing the total cost of idle time and overtime. An adapted Particle Swarm Optimization (PSO) algorithm was proposed to optimize the problem. To avoid early convergence of the particles, an immunity mechanism was introduced into the algorithm. The particle was replaced in time to keep the diversity according to the particle affinity and consistency, and so to avoid being trapped into local optimum. Furthermore, the solutions yielded by these approaches were compared to the traditional PSO algorithm, and the results showed that this novel approach has a lot of advantages for solving the sequencing problems in mixed-model assembly lines.

http://dx.doi.org/10.5755/j01.mech.17.4.573


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Print ISSN: 1392-1207
Online ISSN: 2029-6983