Modern Defense Technology ›› 2021, Vol. 49 ›› Issue (5): 88-94.DOI: 10.3969/j.issn.1009-086x.2021.05.012

• INTEGRATED LOGISTICS SUPPORT TECHNOLOGY • Previous Articles     Next Articles

Equipment Maintenance Scheduling Optimization Model Based on Cost Analysis

SONG Wei-xing1,4, WU Jing-jing2, DONG Zhi-peng1, ZHANG Jun3, ZHOU Kai4   

  1. 1. Army Engineering University of PLA,Shijiazhuang Campus,Hebei Shijiazhuang 050003,China;
    2. Western Theater Army Department of logistics,Gansu Lanzhou 730000,China;
    3. Western Theater ARSTAF,Ganshu Lanzhou 730000,China;
    4. PLA,No.32272 Troop,Ganshu Lanzhou 730000,China
  • Received:2021-04-07 Revised:2021-05-20 Online:2021-10-20 Published:2021-11-01

基于成本分析的装备维修调度优化模型

宋卫星1,4, 武婧婧2, 董志鹏1, 张君3, 周凯4   

  1. 1.陆军工程大学石家庄校区,河北 石家庄 050003;
    2.西部战区陆军保障部,甘肃 兰州 730000;
    3.西部战区陆军参谋部,甘肃 兰州 730000;
    4.中国人民解放军32272部队,甘肃 兰州 730000
  • 作者简介:宋卫星(1982-),男,河北遵化人。工程师,博士,主要从事装备维修保障优化建模及算法研究。通信地址:050003 河北省石家庄市新华区和平路97号 E-mail:88159073@qq.com

Abstract: Aiming at the problems of large equipment maintenance support tasks,limited support resources,extensive maintenance scheduling organization,and low support benefits.An equipment maintenance cost model,accurately calculates the equipment maintenance cost is established by using the activity-based costing method to analyze the relationships between equipment maintenance resource input and benefits,and also a multi-objective equipment maintenance optimization model is established,which is with the goal of the largest number of repaired equipment and the lowest average maintenance cost.Aiming at the characteristics of multiple model parameters and complex calculations,an improved hybrid nested particle swarm algorithm is designed based on a comprehensive use of particle swarm algorithm and genetic algorithm.A maintenance organization is taken as an example to carry out simulation calculations to verify the model and algorithm.The model and algorithm provide a certain theoretical basis for equipment maintenance decision-making.

Key words: maintenance scheduling optimization, particle swarm optimization, genetic algorithm, activity-based costing

摘要: 针对装备维修保障任务量大、保障资源有限,维修调度组织粗放、保障效益低等问题。利用作业成本法分析装备维修资源投入与效益关系,建立装备维修成本模型,精准核算装备维修成本,以维修装备数量最多和平均单装维修成本最低为目标,建立了多目标装备维修优化模型。针对模型参数多、运算复杂的特点,融合粒子群算法和遗传算法,设计了改进的混合嵌套式粒子群算法,并以某维修机构为例,进行实例仿真计算,对模型和算法进行验证,效果良好,为装备维修调度决策提供了一定的理论依据。

关键词: 维修调度优化, 粒子群算法, 遗传算法, 作业成本法

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