DocumentCode :
2944019
Title :
Mixed-Model Assembly Line Balancing Using the Hybrid Genetic Algorithm
Author :
Bai Ying ; Zhao Hongshun ; Zhu Liao
Author_Institution :
Dept. of Electr. Eng., Changzhou Inst. of Machatronic Technol., Changzhou, China
Volume :
3
fYear :
2009
fDate :
11-12 April 2009
Firstpage :
242
Lastpage :
245
Abstract :
In view of the existing problem of mixed-model assembly line balancing, a mathematical model is proposed based on two factors, which are integrated including the workstation number and the assembly line efficiency. Then a new hybrid genetic algorithm is developed for finding optimal solution of the problems. To prevent the premature convergence problem and enhance the globe-optimization capability, GA (genetic algorithms) is combined with SA (simulated annealing algorithms). The results of the simulation indicated that the hybrid algorithm has better efficiency an optimization performance.
Keywords :
assembling; genetic algorithms; simulated annealing; hybrid genetic algorithm; mathematical model; mixed-model assembly line balancing; optimization performance; simulated annealing algorithm; workstation number; Assembly; Automation; Electric variables measurement; Genetic algorithms; Mathematical model; Mechanical engineering; Mechanical variables measurement; Mechatronics; Simulated annealing; Workstations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-0-7695-3583-8
Type :
conf
DOI :
10.1109/ICMTMA.2009.591
Filename :
5203192
Link To Document :
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