改进多目标鲸鱼优化算法的武器目标分配研究  

WEAPON TARGET ALLOCATION BASED ON MULTI-OBJECTIVE WHALE OPTIMIZATION ALGORITHM

作　　者：邱少明 刘良成 杜秀丽[1] 吕亚娜 王建伟 Qiu Shaoming;Liu Liangcheng;Du Xiuli;Lu Yana;Wang Jianwei(Key Laboratory of Communication and Network,Dalian University,Dalian 116622,Liaoning,China)

机构地区：[1]大连大学通信与网络重点实验室,辽宁大连116622

出　　处：《计算机应用与软件》2023年第12期248-254,276,共8页Computer Applications and Software

基　　金：中央军委装备发展部领域基金项目(6140002010101,6140001030111)。

摘　　要：针对武器目标分配问题中存在求解精度低的问题,提出一种改进多目标鲸鱼优化算法(CMMWOA)的武器目标分配方法。通过分别计算鲸鱼个体的非支配等级和拥挤度大小,对鲸鱼种群进行排序,并在父代和子代个体中筛选出优秀个体组成下一代鲸鱼个体,同时加入交叉和变异机制,增加鲸鱼种群间多样性。仿真结果表明,CMMWOA在5个多目标测试函数中,具有更好的寻优能力,在武器目标分配模型中,CMMWOA与其他算法那相比,在相同的条件下得到的目标分配的打击效果也是最大,验证了CMMWOA的有效性。Aimed at the problem of low accuracy in weapon target allocation,a weapon target allocation method based on improved multi-objective whale optimization algorithm(CMMWOA)is proposed.By calculating the non-dominant rank and crowding degree of whale individuals respectively,the whale population was sorted,and excellent individuals were screened out from the parent and offspring individuals to form the next generation of whale individuals.Meanwhile,crossover and mutation mechanisms were added to increase the diversity among whale populations.The simulation results show that CMMWOA has better optimization capability among 5 multi-target test functions,and in the weapon target assignment model,CMMWOA has the largest impact effect of target assignment under the same conditions compared with other algorithms,which indicates the effectiveness of CMMWOA.

关 键 词：多目标鲸鱼优化算法 武器目标分配 非支配关系 拥挤度大小 精英选择 交叉 变异 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]