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基于改进灰狼优化算法的舰载机着舰调度

刘玉杰 韩维 苏析超 郭放

刘玉杰,韩维,苏析超,等. 基于改进灰狼优化算法的舰载机着舰调度[J]. 北京航空航天大学学报,2024,50(3):803-813 doi: 10.13700/j.bh.1001-5965.2022.0280
引用本文: 刘玉杰,韩维,苏析超,等. 基于改进灰狼优化算法的舰载机着舰调度[J]. 北京航空航天大学学报,2024,50(3):803-813 doi: 10.13700/j.bh.1001-5965.2022.0280
LIU Y J,HAN W,SU X C,et al. Carrier aircraft landing scheduling problem based on improved gray wolf optimization[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(3):803-813 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0280
Citation: LIU Y J,HAN W,SU X C,et al. Carrier aircraft landing scheduling problem based on improved gray wolf optimization[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(3):803-813 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0280

基于改进灰狼优化算法的舰载机着舰调度

doi: 10.13700/j.bh.1001-5965.2022.0280
基金项目: 国家自然科学基金(62001499)
详细信息
    作者简介:

    刘玉杰 男,博士,高级工程师。主要研究方向:航空飞行、航空保障、航空心理、空域管理及航空人才选拔培养等

    韩维 男,博士,教授,博士研究生导师。主要研究方向:舰载机甲板航空保障、飞行力学

    苏析超 男,博士,副教授。主要研究方向:舰载机甲板航空保障、智能优化算法

    郭放 男,博士。主要研究方向:舰载机甲板航空保障

    通讯作者:

    E-mail:hanwei70cn@tom.com

  • 中图分类号: TP273

Carrier aircraft landing scheduling problem based on improved gray wolf optimization

Funds: National Natural Science Foundation of China (62001499)
More Information
  • 摘要:

    针对第一类着舰模式下的舰载机着舰调度问题进行了研究,建立着舰调度模型,以最小化加权着舰延误时间和、着舰完成时间为优化目标,考虑舰载机战损程度、剩余燃油量的影响。为减轻人工调度的负担,提出一种改进灰狼优化(IGWO)算法对调度模型进行优化求解,在灰狼优化(GWO)算法的基础上,改进算法选择历史最优解灰狼个体为$\alpha $狼,引入混沌算子,设置算法参数更新控制变量,以应对GWO算法后期收敛速度慢、可能陷入局部最优解的缺点。通过不同规模着舰调度案例仿真和算法对比,验证了IGWO算法的有效性,所提算法在30、60、90机规模着舰调度案例中的优化效果均优于对比算法,证明其具备一定工程应用价值。

     

  • 图 1  舰载机着舰阶段划分

    Figure 1.  Stages of carrier aircraft landing

    图 2  第1类着舰模式下舰载机等待航线

    Figure 2.  Awaiting route of carrier aircraft under class one landing mode

    图 3  第1类着舰模式下舰载机进近着舰航线

    Figure 3.  Approach and landing route of carrier aircraft under class one landing mode

    图 4  福特级航母着舰时甲板状态

    Figure 4.  Deck layout of a Ford carrier when aircraft landing

    图 5  GWO算法改进前后$\omega $的位置更新

    Figure 5.  Position updating of $\omega $ before and after GWO algorithm improvement

    图 6  参数$ e $控制下参数$ a $的更新过程

    Figure 6.  Updating process of $ a $ under control of parameter $ e $

    图 7  IGWO算法流程

    Figure 7.  Flow of IGWO algorithm

    图 8  IGWO算法编码结构

    Figure 8.  Algorithm coding structure of IGWO

    图 9  算法最优解收敛曲线对比

    Figure 9.  Comparison of optimal solution of algorithms convergence curves

    图 10  舰载机着舰调度甘特图

    Figure 10.  Gantt chart of carrier aircraft landing scheduling

    表  1  案例中使用的舰载机参数

    Table  1.   Parameters of carrier aircraft used in cases

    i I O/L W w E/s
    1 1 1 200 90 0.304 6 0
    2 1 1 500 100 0.060 7 0
    3 1 1 600 90 0.256 1 0
    4 2 1 000 100 0.121 4 80
    5 2 1 500 90 0.268 2 80
    6 2 1 400 100 0.072 9 80
    下载: 导出CSV

    表  2  参数值组合

    Table  2.   Parameter values combinations

    参数值水平 Ps e rb Nf
    1 30 0.8 0.2 200
    2 50 1.0 0.4 500
    3 80 2.0 0.6 800
    下载: 导出CSV

    表  3  正交实验及其参数对应的$ A_{{\mathrm{RV}}}$

    Table  3.   Orthogonal experiments and its corresponding ${ A_{{\mathrm{RV}}}}$

    实验次数 Ps e rb Nf ARV
    1 30 0.8 0.2 200 0.3717
    2 30 1.0 0.4 500 0.2993
    3 30 2.0 0.6 800 0.4032
    4 50 0.8 0.4 800 0.3401
    5 50 1.0 0.6 200 0.3343
    6 50 2.0 0.2 500 0.3144
    7 80 0.8 0.6 500 0.3120
    8 80 1.0 0.2 800 0.3665
    9 80 2.0 0.4 200 0.4798
    下载: 导出CSV

    表  4  正交实验参数水平$\overline A_{{\mathrm{RV}}}$

    Table  4.   $\overline A_{{\mathrm{RV}}}$ of orthogonal experiments parameter level

    参数值水平 Ps对应值 e对应值 rb对应值 Nf对应值
    1 0.3581 0.3413 0.3509 0.3953
    2 0.3296 0.3333 0.3731 0.3086
    3 0.3861 0.3991 0.3498 0.3699
    下载: 导出CSV

    表  5  仿真实验结果

    Table  5.   Simulation experiment results min

    规模 最优值
    IGWO FPDGWO[29] GWO[9] VWMPIO[30] TLBO[31] DLGA[32]
    30 64.2 64.7 64.3 64.6 64.7 64.6
    60 286.5 294.9 295.2 311.1 309.8 306.3
    90 496.5 513 505.6 536.3 510.9 551.2
    规模 平均值
    IGWO FPDGWO[29] GWO[9] VWMPIO[30] TLBO[31] DLGA[32]
    30 64.7 66.1 65.4 66.4 65.9 65.3
    60 297 305.2 309.7 326.8 321.1 316.2
    90 512 553.1 543.7 572.5 552.2 567.1
    规模 最劣值
    IGWO FPDGWO[29] GWO[9] VWMPIO[30] TLBO[31] DLGA[32]
    30 65.7 67.5 66.5 67.9 67.3 66.1
    60 303 313.2 343.3 343.6 330.8 322.5
    90 545.1 584.8 596.1 588.5 573.9 581.1
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-04-25
  • 录用日期:  2022-05-15
  • 网络出版日期:  2022-06-09
  • 整期出版日期:  2024-03-27

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