航空学报 > 2025, Vol. 46 Issue (13): 531195-531195   doi: 10.7527/S1000-6893.2024.31195

基于可变作业流程的舰载机机务勤务保障作业调度

郭放1, 韩维1, 刘玉杰1,2, 刘洁3, 苏析超4(), 程亮亮4   

  1. 1.海军航空大学 航空基础学院,烟台 264001
    2.军事科学研究院 军队政治工作研究院,北京 100071
    3.中国人民解放军32009部队,北京 100091
    4.海军航空大学 航空作战勤务学院,烟台 264001
  • 收稿日期:2024-09-12 修回日期:2024-10-09 接受日期:2024-10-22 出版日期:2024-10-30 发布日期:2024-10-29
  • 通讯作者: 苏析超 E-mail:suxich@126.com
  • 基金资助:
    国家自然科学基金(12102077);中国科协青年人才托举工程

Scheduling for maintenance and service support of carrier-based aircraft based on variable operation process

Fang GUO1, Wei HAN1, Yujie LIU1,2, Jie LIU3, Xichao SU4(), Liangliang CHENG4   

  1. 1.School of Basic Science for Aviation,Naval Aviation University,Yantai 264001,China
    2.Military Political Work Research Institute,Military Science Academy,Beijing 100071,China
    3.Unit 32009 of the PLA,Beijing 100091,China
    4.Aeronautical Operations College,Naval Aviation University,Yantai 264001,China
  • Received:2024-09-12 Revised:2024-10-09 Accepted:2024-10-22 Online:2024-10-30 Published:2024-10-29
  • Contact: Xichao SU E-mail:suxich@126.com
  • Supported by:
    National Natural Science Foundation of China(12102077);Young Elite Scientists Sponsorship Program by CAST

摘要:

随着现代海战对航母作战能力要求的提高,舰载机机务勤务保障作业的效率直接影响航母作战效能的发挥,为优化保障作业流程,进一步提升作业效率,研究了基于可变作业流程的舰载机机务勤务保障作业调度优化问题,提出了相应的调度优化算法。首先,分析了甲板作业环境和机务勤务保障作业特点,构建了甲板作业环境中保障人员和设备的转移路径库;其次,以最小化保障完工时间为优化目标,构建了基于可变作业流程的舰载机机务勤务保障作业调度模型,模型中考虑了保障人员、保障设备和流程约束,以及武器的协同取送过程;进一步,将问题抽象为基于可变作业流程的资源受限多项目—资源转运集成调度问题,基于考虑资源、人员转移的串行调度生成机制,提出了一种改进粒子群优化算法(IPSO)对调度模型进行优化求解;最后,通过典型保障任务场景仿真和算法对比,验证了调度模型和算法的有效性,以及算法的高效性和鲁棒性。在相同条件下,相对于基于固定流程的保障作业调度方法,文中提出的基于可变作业流程的机务勤务保障作业调度方法能够有效缩短保障完工时间,在武器配送作业场景中保障作业平均完成时间至少可减少25.50%,在武器取送协同作业场景中保障作业平均完成时间至少可减少25.96%。

关键词: 舰载机, 可变作业流程, 机务勤务保障作业, 武器转运, 集成调度, 资源受限多项目调度, 粒子群优化算法

Abstract:

With the increasing demand for aircraft carrier combat capability in modern naval warfare, the efficiency of carrier aircraft maintenance and support operations directly affects the effectiveness of aircraft carrier combat. To optimize the support operation process and further improve operation efficiency, the scheduling optimization problem for maintenance and service support of carrier aircraft based on variable operation process was studied, and the corresponding scheduling optimization algorithm was proposed. Firstly, the characteristics of the flight deck environment and maintenance and support operations were analyzed, and a transfer path library for personnel and equipment in the deck environment was constructed. Secondly, with the optimization goal of minimizing the completion time of support operations, an scheduling model for maintenance and service support of carrier aircraft based on variable operation process is constructed. The model takes into account the constraints of support personnel, support equipment, and operation process, as well as the collaborative pickup and delivery process of weapons. Furthermore, the problem is conceptualized as an integrated scheduling problem of resource constrained multi-project scheduling and resource delivery scheduling based on variable process operation flow. Based on a serial scheduling generation scheme considering resource transfer and personnel transfer, an Improved Particle Swarm Optimization algorithm (IPSO) is proposed to optimize and solve the scheduling model. Finally, the effectiveness of the scheduling model and algorithm, as well as the efficiency and robustness of the algorithm, were verified through simulation of typical support task scenarios and algorithm comparisons. Under the same conditions, compared to the fixed process-based scheduling method, the proposed variable process-based scheduling method for maintenance and support operations can effectively shorten the completion time. In the scenario of flight deck operations with weapon delivery operations, the average completion time can be reduced by at least 25.50%; and in the scenario with weapon pick-up and delivery, the average completion time can be reduced by at least 25.96%.

Key words: carrier-based aircraft, variable process, maintenance and support operations, weapon transportation, integrated scheduling, resource-constrained multi-project scheduling problem, Particle Swarm Optimization (PSO) algorithm

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