| 摘要: |
| 针对工程实践中研制阶段保障设备数量确定过于依赖工程经验、配置不合理的现象
，在装备维修保障过程分析的基础上，综合考虑保障系统的及时性、部署性和经济性要
求建立了以平均保障设备满足率为优化目标，以保障设备利用率、保障设备总费用和保障设
备规模为联合约束条件的保障设备配置优化模型；模型中给出了保障站点级和保障活动级保
障设备满足率的计算方法，其中，保障活动级保障设备满足率的计算考虑了保障活动与保障
设备之间4种不同关系（1∶1、1∶N、N∶1和N∶M）；最后，采用自适应遗传算法(AGA)
算法对模型进行求
解，得到保障站点内多类保障设备在多约束条件下整体配置优化的结果。通过某通信导航识
别
子系统的算例证明：该模型能有效提高保障设备的配置效率，为工业部门在研制阶段合理确
定保障设备配置数量提供方法。 |
| 关键词: 保障设备 研制阶段 满足率 利用率 优化模型 自适应遗传算法 |
| DOI：doi:10.3969/j.issn.1001-893x.2013.06.028 |
|
| 基金项目: |
|
| Joint optimization model for support equipment’s allocation under multi-constraint |
| WEN Jia |
| () |
| Abstract: |
| In project practice, the quantity of support equipment mostly determin
ed by experience can not exactly suit the need of maintenance support. Therefo
re, an optimization model for support equipment′s allocation quantity is estab
lished based on the analysis of maintenance support process. The footprint, cost
, the mean and variance of the utilization rate of support equipment are taken a
s the joint constraints of the model and the mean support equipment fill rate i
s used as the objective function of the model by considering the timeliness, foo
tprint and cost of support system. The calculating method for support equipment
fill rate of support site level and support activity level is presented, while
four types of relationship between support activities and support equipment (i.e
., 1∶1, 1∶N, N∶1, and N∶M) are considered in calculating support equ
ipment fill rate of support activity level. The adapted genetic algorithm (AGA)
is chosen t
o obtain the solution of the optimization model. The proposed model is demonstr
ated via a case of Communication Navigation Identification sub-system, and is p
roved to be effective to improve the allocation efficiency of support equipment. |
| Key words: support equipment design and development phase fill rate utilization rate optimized model adaptive genetic algorithm |
