Model of Spare Parts Optimization Based on GA for Equipment
Guangze Pan, Qin Luo, Xiaobing Li, Yuanhang Wang, Chuangmian Huang
Available Online July 2018.
- https://doi.org/10.2991/msam-18.2018.10How to use a DOI?
- equipment; genetic algorithm; spare parts optimization
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Guangze Pan AU - Qin Luo AU - Xiaobing Li AU - Yuanhang Wang AU - Chuangmian Huang PY - 2018/07 DA - 2018/07 TI - Model of Spare Parts Optimization Based on GA for Equipment BT - Proceedings of the 2018 3rd International Conference on Modelling, Simulation and Applied Mathematics (MSAM 2018) PB - Atlantis Press SP - 44 EP - 47 SN - 1951-6851 UR - https://doi.org/10.2991/msam-18.2018.10 DO - https://doi.org/10.2991/msam-18.2018.10 ID - Pan2018/07 ER -