基于改进引力搜索的武器目标分配方法

Weapon Target Assignment Method Based on Modified Gravitation Search Algorithm

针对目前武器目标分配(WTA)问题所用引力搜索算法(GSA)存在着早熟收敛的问题,提出了基于改进GSA的武器目标分配方法。该方法首先将粒子群算法(PSO)的记忆信息和群体共享信息能力引入到GSA算法之中,再将混沌搜索(CS)的思想嵌入到改进的GSA算法之中,提出了CP-GSA算法;然后利用提出的CPGSA算法直接求解WTA最小化问题,进行武器目标分配。仿真实验表明:所提出的方法能够有效解决WTA问题,提高分配性能,在4个地面防空作战单元抗击8个来袭目标的情况下,迭代41次即可得到最优解,适应度值为1.18,与枚举法所得的最优适应度值相等。

Aimed at the problem of premature convergence in the weapon target assignment(WTA)when using gravitation search algorithm(GSA),a modified GSA was proposed in this paper.Firstly,the abilities to memorize information and share information of particle swarm optimization(PSO)algorithm were introduced into the process of GSA.Then,the operation of chaos search(CS)was also inserted into the improved GSA algorithm,and the modified GSA,named CP-GSA algorithm was proposed.At last,the CP-GSA algorithm was applied directly to solve the WTA minimization problem.The simulation results demonstrated that the proposed method could solve the WTA problem effectively.Specially,to attack eight targets using four air defense units,the proposed method could find the best solution by only 41 iterative operations,and the finest value was 1.18,which was equivalent to that obtained by enumeration method.