面向动用计划的车辆装备备件预测研究  

Vehicle maintenance spare-part prediction for equipment use plan

作　　者：李凤月 齐小刚 班利明 李建华[2] 索文凯 LI Fengyue;QI Xiaogang;BAN Liming;LI Jianhua;SUO Wenkai(School of Mathematics and Statistics,Xidian University,Xi’an 710000,China;32272 Group of PLA,Lanzhou 730000,China)

机构地区：[1]西安电子科技大学数学与统计学院,陕西西安710000 [2]中国人民解放军32272部队,甘肃兰州730000

出　　处：《智能系统学报》2021年第6期1064-1072,共9页CAAI Transactions on Intelligent Systems

基　　金：国家自然科学基金项目(61877067);数据链技术重点实验室基金项目(CLDL-20182115)。

摘　　要：针对动用计划下的车辆装备备件的消耗特点,研究了车辆装备维修备件消耗量和库存控制两个预测优化问题。考虑动用计划期内车辆装备的预防性维修和修复性维修,实现定时定程维修和自然随机故障维修下装备维修备件的消耗量的预测。在此基础上,根据备件库存检查方式的特点,建立基于定期检查策略的联合补货库存控制模型,根据模型的结构特点确定决策变量界限,并利用多类种群位置更新方式改进了果蝇优化算法。仿真结果表明,改进的果蝇优化算法具有良好的求解效率,本文所提出的优化方法可为车辆维修保障资源优化提供决策依据。Aiming at the consumption characteristics of vehicle equipment spare parts under the use plan,two forecast optimization problems of spare-part consumption and inventory control are studied.First,the preventive and repairable maintenance of vehicle equipment is considered for the use plan period,and the consumption of equipment maintenance spare parts under the fixed schedule and random natural failure maintenance is predicted.Subsequently,based on the characteristics of the spare parts inventory inspection method,the joint replenishment inventory control model is established based on a regular inspection strategy.According to the structural characteristics of the model,the limits of decision variables are determined,and the multipopulation location upgrade method is used to improve the fruit fly optimization algorithm(FOA).The simulation results show that the improved FOA has good solving efficiency.The proposed optimization method can provide a decision-making basis for the optimization of vehicle maintenance support resources.

关 键 词：车辆装备 备件预测 动用计划 消耗量 定期检查 库存控制 多类种群 果蝇优化算法 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]