固体力学与飞行器总体设计

航空母舰舰载机弹药保障作业调度优化算法

  • 张少辉 ,
  • 刘舜 ,
  • 李亚飞 ,
  • 金钊 ,
  • 靳远远 ,
  • 王少参 ,
  • 赵建波 ,
  • 徐明亮
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  • 1.郑州大学 计算机与人工智能学院,郑州 450001
    2.周口师范学院 网络工程学院,周口 466001
    3.智能集群系统教育部工程研究中心,郑州 450001
    4.国家超级计算郑州中心,郑州 450001
    5.中国船舶集团有限公司第七一三研究所,郑州 450015
    6.江苏科技大学 经济管理学院,镇江 212100

收稿日期: 2023-01-09

  修回日期: 2023-03-07

  录用日期: 2023-03-17

  网络出版日期: 2023-03-17

基金资助

国家自然科学基金重点项目(62036010);国家自然科学基金优秀青年基金(61822701);国家自然科学基金面上项目(62172457);中国博士后科学基金(2018M630836);河南省自然科学基金优秀青年基金(202300410378);河南省科技攻关项目(212102210098);河南省高等学校青年骨干教师培养计划(2020GGJS215);河南省高等学校重点科研项目(22A520051)

Optimization algorithm for ammunition support operation scheduling of carrier-borne aircraft

  • Shaohui ZHANG ,
  • Shun LIU ,
  • Yafei LI ,
  • Zhao JIN ,
  • Yuanyuan JIN ,
  • Shaocan WANG ,
  • Jianbo ZHAO ,
  • Mingliang XU
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  • 1.School of Computer Science and Artificial Intelligence,Zhengzhou University,Zhengzhou  450001,China
    2.School of Network Engineering,Zhoukou Normal University,Zhoukou  466001,China
    3.Intelligent Cluster System Engineering Research Center of the Ministry of Education,Zhengzhou  450001,China
    4.National Supercomputing Center in Zhengzhou,Zhengzhou  450001,China
    5.The 713 Research Institute,China Shipbuilding Industry Corporation,Zhengzhou  450015,China
    6.School of Economics and Management,Jiangsu University of Science and Technology,Zhenjiang  212100,China

Received date: 2023-01-09

  Revised date: 2023-03-07

  Accepted date: 2023-03-17

  Online published: 2023-03-17

Supported by

National Natural Science Foundation of China(62036010);National Science Fund for Excellent Young Scholars(61822701);National Natural Science Foundation of China(62172457);China Postdoctoral Science Foundation(2018M630836);Excellent Youth Fund of Henan Natural Science Foundation(202300410378);Science and Technology Project of Henan Province(212102210098);Training Program for Young Backbone Teachers of Henan Higher Education Institutions(2020GGJS215);Key Research Project of Henan Higher Education Institutions(22A520051)

摘要

针对航空母舰舰载机弹药保障作业高动态、多阶段特性,将柔性流水车间调度方法和群体智能优化理论相结合,提出一种面向舰载机弹药保障作业的调度优化算法。提出将复杂的弹药保障作业调度问题抽象规约为一类考虑工件交货期的柔性流水车间调度问题,引入启发式规则,构建兼顾高效性和可靠性实战要求的弹药保障作业调度数学模型ATSCA。结合弹药保障作业问题特征,设计提出一种基于双层整数编码的贪婪局部搜索遗传算法(GLSGA-DC),改进操作算子和局部搜索算法设计,以最小化弹药保障完成时间为目标对保障模型进行求解。多组仿真结果表明,相比于同类算法,GLSGA-DC算法在Benchmark基准算例和实际弹药转运实例实验中均取得优秀的效果,在求解均值(AVG)、相对偏差(RD)等指标方面均明显占优,验证了ATSCA模型和求解算法在实际弹药保障任务中的有效性和鲁棒性。

本文引用格式

张少辉 , 刘舜 , 李亚飞 , 金钊 , 靳远远 , 王少参 , 赵建波 , 徐明亮 . 航空母舰舰载机弹药保障作业调度优化算法[J]. 航空学报, 2023 , 44(20) : 228485 -228485 . DOI: 10.7527/S1000-6893.2023.28485

Abstract

Considering the highly dynamic and multi-stage characteristics of carrier-based aircraft ammunition support operations, we establish an optimization model based on the theory of swarm intelligence optimization and the method of flexible flow-shop scheduling. Firstly, the ammunition transfer support operation problem is reduced to a flexible flow-shop scheduling problem considering the delivery time of work-pieces, and heuristic rules are introduced to construct the model of Ammunition Transport Support for Carrier-Borne Aircraft (ATSCA), which takes into account the requirements of efficiency and robustness. Secondly, combined with the practice of ammunition dispatching operation, a Greedy Local Search Genetic Algorithm with Dual-Level Coding (GLSGA-DC) is designed to solve the ATSCA model with the goal of minimizing the maximum ammunition transfer time. The simulation results show that the GLSGA-DC algorithm has obtained the optimal values in the Mean Value (AVG), Relative Deviation (RD) and other indicators in benchmark tests and multiple groups of experiments in real ammunition transfer operations, demonstrating the effectiveness and robustness of the ATSCA model and algorithm in real ammunition support operations for carrier-borne aircraft.

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