基于云遗传算法的防空导弹目标分配问题

Target Assignment Problem of Air-defense Missile Based on Cloud Genetic Algorithm

针对传统遗传算法在防空导弹目标优化分配中存在的缺陷,提出了一种更为有效的云遗传算法。通过该算法对防空导弹目标分配模型进行仿真求解,得出防空导弹射击目标的最优目标分配方案。通过算例分析,云遗传算法相比传统遗传算法收敛速度快,搜索效率高出一倍左右,对产生局部最优解情况进行了合理有效的控制,可操作性、优越性更强。

Aimming at the defects of traditional genetic algorithm in target optimizing distribution,a more efficient cloud genetic algorithm is proposed. Using this algorithm,the target distribution model for air-defense missile shooting target is simulated and solved. At last,the optimal allocation scheme of air-defense missile is obtained. Compared with the traditional genetic algorithm,the numerical analysis shows that convergence speed of the cloud genetic algorithm is faster. At the same time,search efficiency increases more than double approximately. Meanwhile local optima phenomena can be controlled effectively and reasonablely. The results shows the operability and superiority of this algorithm are better.