基于IABC算法的舰载机着舰调度
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作者单位:

1. 海军航空大学 航空基础学院,山东 烟台 264001;2. 海军航空大学 航空作战勤务学院,山东 烟台 264001

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E-mail: guofang575856@163.com.

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V355.2

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武器装备预先研究项目.


Scheduling of landing for carrier-based aircraft based on improved artificial bee colony algorithm
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Affiliation:

1. School of Basic Science for Aviation,Naval Aviation University,Yantai 264001,China;2. Aeronautical Operations College,Naval Aviation University,Yantai 264001,China

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    摘要:

    舰载机有序、高效着舰是确保舰载机舰面保障计划如期进行的必要前提,为提高舰载机着舰效率并减轻传统人工着舰排序的负担,研究一种舰载机着舰调度算法.首先,以加权着舰完成时间和为优化目标,构建舰载机着舰调度的数学模型;其次,提出一种改进的人工蜂群算法用于模型求解,算法在基本人工蜂群算法的基础上引入遗传算法中的交叉算子、精英策略以及一系列自适应局部搜索策略,以增强算法的全局搜索性能,提高算法收敛速度;最后,通过着舰调度案例仿真和算法对比表明,改进的人工蜂群算法具备更强的优化性能和更好的鲁棒性,可以求解大规模舰载机着舰调度问题,具有工程实际应用价值.

    Abstract:

    The orderly and efficient landing of carrier-based aircrafts is a necessary prerequisite to ensure that the deck operation support plan is carried out as scheduled. In order to improve the landing efficiency of carrier-based aircrafts and reduce the burden of traditional manual landing scheduling, a landing scheduling algorithm for carrier-based aircrafts is studied. Firstly, the mathematical model of landing scheduling for a carrier-based aircraft is constructed with the weighted landing time sum as the optimization objective. Secondly, an improved artificial bee colony algorithm is proposed to solve the model. Based on the basic artificial bee colony algorithm, the crossover operation, the elite strategy and a series of adaptive local search strategies are introduced to enhance the global search performance of the algorithm and improve the convergence speed of the algorithm. Finally, the case study and algorithm comparison verify, the effectiveness of the proposed scheduling model, and show that the improved artificial bee colony algorithm has stronger optimization performance and better robustness, which can solve the large-scale carrier aircraft landing scheduling problem, having practical engineering application value.

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引用本文

刘玉杰,万兵,苏析超,等.基于IABC算法的舰载机着舰调度[J].控制与决策,2022,37(7):1810-1818

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  • 在线发布日期: 2022-05-25
  • 出版日期: 2022-07-20
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