航空学报 > 2025, Vol. 46 Issue (2): 227327-227327   doi: 10.7527/S1000-6893.2022.27327

固体力学与飞行器总体设计

考虑多资源约束的多任务条件下装备选择性维修决策

马维宁, 胡起伟(), 贾希胜   

  1. 陆军工程大学 石家庄校区,石家庄 050003
  • 收稿日期:2022-04-26 修回日期:2022-05-26 接受日期:2022-06-21 出版日期:2022-06-28 发布日期:2022-06-24
  • 通讯作者: 胡起伟 E-mail:hu_qiwei@126.com
  • 基金资助:
    全军军事类研究生资助重点课题(JY2020B085)

Selective maintenance decision for equipment under multi-mission setting considering multiple resource constraints

Weining MA, Qiwei HU(), Xisheng JIA   

  1. Shijiazhuang Campus,Army Engineering University of PLA,Shijiazhuang 050003,China
  • Received:2022-04-26 Revised:2022-05-26 Accepted:2022-06-21 Online:2022-06-28 Published:2022-06-24
  • Contact: Qiwei HU E-mail:hu_qiwei@126.com
  • Supported by:
    Postgraduate Funing Project of PLA(JY2020B085)

摘要:

战场环境下任务间隔时间有限,如何在较短时间内恢复装备战斗力、提高任务可靠度是装备维修决策的重要问题。以装备连续执行多个任务为背景,综合考虑任务可靠度要求、可用度要求、维修人员技能水平等因素,以多任务间隔时间之和最小化为优化目标,建立装备选择性维修决策模型,采用遗传算法进行优化求解。结合算例,分析了任务可靠度要求、可用度要求、维修人员技能水平等因素对优化结果的影响。研究结果表明,所建模型和求解算法有效,能够为战场环境下装备维修决策问题提供理论指导和技术支持。

关键词: 选择性维修, 不完全维修, 多任务, 遗传算法, 可靠度

Abstract:

In the battlefield environment, the mission interval is limited. The quick restoration of equipment combat power and improvement of mission reliability is an important issue in equipment maintenance decision-making. Taking equipment continuously performing multiple missions as the background, and comprehensively considering factors such as mission reliability requirement, availability requirement and the skill levels of maintenance personnel, we establish an equipment selective maintenance decision-making model with the optimization goal of minimizing the sum of the multi-mission interval time, and use the genetic algorithm to obtain the solution. Combined with a numerical example, the influences of factors such as mission reliability requirement, availability requirement and the skill levels of maintenance personnel on the optimization results are analyzed. The results show that the established model and the solution algorithm are effective, which can provide theoretical guidance and technical support for equipment maintenance decision-making in the battlefield environment.

Key words: selective maintenance, imperfect maintenance, multi-mission, genetic algorithm, reliability

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