面向动用计划的车辆装备备件预测研究

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Title:

Vehicle maintenance spare-part prediction for equipment use plan

作者:

李凤月¹, 齐小刚¹, 班利明², 李建华², 索文凯²

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

Author(s):

LI Fengyue¹, QI Xiaogang¹, BAN Liming², LI Jianhua², SUO Wenkai²

1. School of Mathematics and Statistics, Xidian University, Xi’an 710000, China;
2. 32272 Group of PLA, Lanzhou 730000, China

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

Keywords:

vehicle equipment; spare parts prediction; using plan; consumption; regular inspection; inventory control; multi-population; fruit fly optimization algorithm

分类号:

TP273

DOI:

10.11992/tis.202012026

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。

Abstract:

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.