Model of Spare Parts Optimization Based on GA for Equipment

被引：0
|
作者：
Pan, Guangze [1 ]
Luo, Qin [1 ]
Li, Xiaobing [2 ]
Wang, Yuanhang [1 ]
Huang, Chuangmian [2 ]
机构：
[1] China Elect Prod Reliabil & Environm Testing Res, Guangzhou, Guangdong, Peoples R China
[2] Guangdong Prov Key Lab Elect Informat Prod Reliab, Guangzhou, Guangdong, Peoples R China
来源：
PROCEEDINGS OF THE 2018 3RD INTERNATIONAL CONFERENCE ON MODELLING, SIMULATION AND APPLIED MATHEMATICS (MSAM 2018) | 2018年 / 160卷
关键词：
equipment; genetic algorithm; spare parts optimization; FILL RATE;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Combined with the engineering requirements for the optimal allocation of the current ammunition equipment spare parts, a spare part optimization model based on genetic algorithm was established. With the combination of good readiness and cost of ammunition equipment, the use of genetic algorithm had the characteristics of fast convergence, strong global optimization, and simple programming. The model was solved and the spare parts of ammunition equipment were optimally configured. Finally, an example of ammunition equipment was analyzed. The results show that the genetic algorithm can effectively solve the optimization problem of ammunition equipment spare parts.
引用
收藏
页码：44 / 47
页数：4
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