Fan Shu
Logistics Engineering College, Shanghai Maritime University, 201306, Shanghai, China
Zi-Qi Xu
Logistics Engineering College, Shanghai Maritime University, 201306, Shanghai, China
Chao Mi
Container Supply Chain Technology Engineering Research Center, Shanghai Maritime University, 201306, Shanghai, China
Xiao-Ming Yang
Logistics Engineering College, Shanghai Maritime University, 201306, Shanghai, China
ABSTRACT
This study, pertinent to the problem that the traditional process optimization of assembly line optimizes only for single target but neglects other important elements, builds the mathematical model for the multi-objective, including maximizing the capacity, balancing the load and minimizing the cost, process optimization of the assembly line of the passenger car engine. Based on the features of the passenger car engine assembly, such as complex steps, too many stations, expensive tools and great market demands, this paper adopts the GASA algorithm combining the genetic algorithm and the simulated annealing algorithm for solution. Experiments show that such model and algorithm can solve the process optimization problems of the passenger car engine assembly line effectively.
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How to cite this article
Fan Shu, Zi-Qi Xu, Chao Mi and Xiao-Ming Yang, 2013. Research on Engine Assembly Line Balancing Based on an Improved Genetic
Algorithm. Journal of Applied Sciences, 13: 2429-2435.
DOI: 10.3923/jas.2013.2429.2435
URL: https://scialert.net/abstract/?doi=jas.2013.2429.2435
DOI: 10.3923/jas.2013.2429.2435
URL: https://scialert.net/abstract/?doi=jas.2013.2429.2435
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