改进人工免疫算法的多机协同空战目标分配方法
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摘要
针对多机协同空战目标分配问题,在我方综合优势函数建模的基础上,提出了一种改进人工免疫算法。首先采用随机生成法和人工构造法创建2个初始种群,保证了初始种群的多样性;然后采用2种不同的选择、交叉、变异操作进行进化;接着采用设计的新移民算子进行种群间信息交换,进一步增加种群多样性,提高搜索效率。最后设计实验将改进人工免疫算法与3种类型的人工免疫算法进行了对比。仿真结果表明:改进人工免疫算法能够有效改善早熟收敛问题,提高搜索效率,获得最优分配方案,适用于多机协同空战目标分配问题,满足实际作战需求。
Aiming at the target allocation of multi-aircraft cooperative air combat, an improved artificial immune algorithm is proposed based on the modeling for comprehensive superiority function. Firstly, the random generation method and artificial construction method are used to create two initial populations, which ensure the diversity of the initial populations; following is to evolve the populations by adopting two different selection, crossover and mutation operations; then, the designed new immigration operator is used to exchange information among the populations, which further increases the diversity of the populations and improves the search efficiency. Finally, the comparison of the improved artificial immune algorithm with the traditional artificial immune algorithm had been made. Simulation results show that the improved artificial immune algorithm can effectively improve the premature convergence problem, and the search efficiency, the optimal allocation scheme is obtained, which is suitable for target allocation problem of multi-aircraft cooperative air combat and meet the actual operational requirements.
Aiming at the target allocation of multi-aircraft cooperative air combat, an improved artificial immune algorithm is proposed based on the modeling for comprehensive superiority function. Firstly, the random generation method and artificial construction method are used to create two initial populations, which ensure the diversity of the initial populations; following is to evolve the populations by adopting two different selection, crossover and mutation operations; then, the designed new immigration operator is used to exchange information among the populations, which further increases the diversity of the populations and improves the search efficiency. Finally, the comparison of the improved artificial immune algorithm with the traditional artificial immune algorithm had been made. Simulation results show that the improved artificial immune algorithm can effectively improve the premature convergence problem, and the search efficiency, the optimal allocation scheme is obtained, which is suitable for target allocation problem of multi-aircraft cooperative air combat and meet the actual operational requirements.
引文
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[14] 翟仲曦,钱锋,杜文莉.基于定向突变的自适应并行免疫算法[J].华东理工大学学报(自然科学版),2010,36(1):88-92ZHAN Zhongxi,QIAN Feng,DU Wenli.Adaptive Parallel Immune Algorithm with Orthomutation[J].Journal of East China University of Science and Technology (Natural Science Edition),2010,36(1):88-92(in Chinese)
[15] 余振华,张其善.最优路径问题的自适应伪并行免疫算法[J].计算机工程与应用,2009,45(26):88-92YU Zhenhua,ZHANG Qishan.Adaptive Pseudo-Parallel Immune Algorithm on Optimal Path Planning Problem[J].Computer Engineering and Applications,2009,45(26):88-92 (in Chinese)
[2] 王庆贺,万刚,柴峥,等.基于改进遗传算法的多机协同多目标分配方法[J].计算机应用研究,2018,35(9):2597-2601WANG Qinghe,WAN Gang,CHAI Zheng,et al.Multiple Targets Assignment of Multiple UAVs′ Cooperation Based on Improved Genetic Algorithm[J].Application Research of Computers,2018,35(9):2597-2601 (in Chinese)
[3] 张邦楚,彭琛,余新荣,等.基于蚁群优化的多弹协同目标分配算法[J].弹箭与制导学报,2012,32(7):69-73ZHANG Bangchu,PENG Chen,YU Xinrong,et al.Cooperative Target Assignment Algorithm of Multiple Missiles Based on Ant Colony Optimization[J].Journal of Projectiles,Rockets,Missiles and Guidance,2012,32(7):69-73 (in Chinese)
[4] 王永泉,罗建军.基于多群体改进萤火虫算法的UCAV协同多目标分配[J].西北工业大学学报,2014,32(3):451-456WANG Yongquan,LUO Jianjun.Target Assignment in Cooperative Attacking of UCAVs Based on Multi-Intelligence Improved Glowworm Swarm Optimization Algorithm[J].Journal of Northwestern Polytechnical University,2014,32(3):451-456 (in Chinese)
[5] 黄国强,张兵.基于混合优化算法的多飞行器协同目标分配方法[J].指挥信息系统与技术,2015,6(6):76-82HUANG Guoqiang,ZHANG Bing.Target Assignment Method for Multi-Aircraft Cooperation Based on Hybrid Optimization Algorithm[J].Command Information System and Technology,2015,6(6):76-82 (in Chinese)
[6] FORTEST S,HOFMEYR S A.Immunology As Information Prcessing,Design Principles for the Immune System and Other Distributed Autonomous Systems[M].USA,Oxford University Press,2000:865-869
[7] CHRISTIAN Wallenta,JUNGWON Kim,PETER J Bentley,et al.Detecting Interest Cache Poisoning in Sensor Networks Using an Artificial Immune Algorithm[J].Applied Intelligence,2010,32(1):1-26
[8] MCCOY D F,DEVARAJIAN V.Artificial Immune Systems and Aerial Image Segmentation[C]//IEEE International Conference on Systems,Man,and Cybemetics,1997:867-872
[9] 徐克虎,黄大山,王天召.改进的人工免疫算法求解武器-目标分配问题[J].系统工程与电子技术,2013,35(10):2121-2127XU Kehu,HUANG Dashan,WANG Tianzhao.Improved Artificial Immuneal Gorithm for Solving Weapon-Target Assignment Problems[J].Systems Engineering and Electronics,2013,35(10):2121-2127 (in Chinese)
[10] 阮旻智,李庆民,刘天华.编队防空火力分配建模及其优化方法研究[J].兵工学报,2010,31(11):1525-1526RUAN Minzhi,LI Qingmin,LIU Tianhua.Modeling and Optimization on Fleet Antiaircraft Firepower Allocation[J].Acta Armamentarii,2010,31(11):1525-1526 (in Chinese)
[11] 刘洪引,李体方,王立安.基于改进人工免疫算法的火力分配[J].火力与指挥控制,2014,39(10):171-174LIU Hongyin,LI Tifang,WANG Lian.Improved Artificial Immune Algorithm Based on Weapon-Target Assignment[J].Fire Control & Command Control,2014,39(10):171-174 (in Chinese)
[12] 卢有麟,陈金松,祁进.基于改进熵权和集对分析的水库多目标防洪调度决策方法研究[J].水电能源科学,2015,33(11):43-46LU Youlin,CHEN Jinsong,QI Jin.Multi-Objective Decision Making Method for Reservoir Flood Operation Based on Improved Entropy Weight and Set Pair Analysis[J].Water Resources and Power,2015,33(11):43-46 (in Chinese)
[13] 戚玉涛,焦李成,刘芳.基于并行人工免疫算法的大规模TSP问题求解[J].电子学报,2008,36(8):1552-1558QI Yutao,JIAO Licheng,LIU Fang.Parallel Artificial Immune Algorithm for Large-Scale TSP[J].Acta Electronica Sinica,2008,36(8):1552-1558 (in Chinese)
[14] 翟仲曦,钱锋,杜文莉.基于定向突变的自适应并行免疫算法[J].华东理工大学学报(自然科学版),2010,36(1):88-92ZHAN Zhongxi,QIAN Feng,DU Wenli.Adaptive Parallel Immune Algorithm with Orthomutation[J].Journal of East China University of Science and Technology (Natural Science Edition),2010,36(1):88-92(in Chinese)
[15] 余振华,张其善.最优路径问题的自适应伪并行免疫算法[J].计算机工程与应用,2009,45(26):88-92YU Zhenhua,ZHANG Qishan.Adaptive Pseudo-Parallel Immune Algorithm on Optimal Path Planning Problem[J].Computer Engineering and Applications,2009,45(26):88-92 (in Chinese)