[1]李凤月,齐小刚,班利明,等.面向动用计划的车辆装备备件预测研究[J].智能系统学报,2021,16(6):1064-1072.[doi:10.11992/tis.202012026]
 LI Fengyue,QI Xiaogang,BAN Liming,et al.Vehicle maintenance spare-part prediction for equipment use plan[J].CAAI Transactions on Intelligent Systems,2021,16(6):1064-1072.[doi:10.11992/tis.202012026]
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面向动用计划的车辆装备备件预测研究(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第16卷
期数:
2021年6期
页码:
1064-1072
栏目:
学术论文—智能系统
出版日期:
2021-11-05

文章信息/Info

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 equipmentspare parts predictionusing planconsumptionregular inspectioninventory controlmulti-populationfruit 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.

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备注/Memo

备注/Memo:
收稿日期:2020-12-16。
基金项目: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)
作者简介:李凤月,硕士研究生,主要研究方向为系统建模、资源优化;齐小刚,教授,博士生导师,主要研究方向为复杂系统建模与仿真。参加了国家自然科学基金项目、省自然科学基金项目、中国–加拿大国际合作项目、ISN国家重点实验室专项基金项目等多项。发表学术论文100余篇;班利明,工程师,主要研究方向为装备维修保障优化
通讯作者:齐小刚.E-mail:xgqi@xidian.edu.cn
更新日期/Last Update: 2021-12-25