Optimization on mixed-flow assembly u-line balancing problem

被引：0
作者：
Ting Wang
Ran Fan
Yanjie Peng
Xin Wang
机构：
[1] Guizhou University,School of Management
[2] China Railway Tunnel Survey and Design Institute,undefined
来源：
Cluster Computing | 2019年 / 22卷
关键词：
U-shaped assembly line balancing; Learning effects; Multi-constraints; Mixed flow; Genetic algorithm;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
U-shaped assembly line which has a better balance and a more compact space compared with traditional linear line derived from lean production. Aiming at balancing type-2 and -3 problem, learning effect and various constraints which cannot be ignored being added, an idea of combining learning effect with multiple constraints in actual production is put forward in this paper. Besides, the mixed nonlinear integer programming model is established for u-shaped assembly line to conduct a synthesis optimization for multiple optimized objects, and the improved genetic algorithm is being used for optimized solution. Finally, this model is applied to X company, and the weighted average load balance of each station and the assembly line rhythm as well as time fluctuation of the workstation are improved which verify the optimization of this model and the fitness of the improved genetic algorithm.
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页码：8249 / 8257
页数：8
相关论文
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