一种用于线性阵列综合的改进遗传算法

为了提高阵列综合收敛速度,实现目标函数局部最优,分析了现有的遗传算法存在的不足,提出了一种应用于线性阵列综合的改进遗传算法。该算法根据现有算法对实数编码搜索能力不强,容易陷于局部最优解的缺陷,提出了能够增强个体寻优范围的搜索方案,以跳出局部最优解,是解决问题的有效途径。仿真结果表明,改进后的算法能够使目标函数迅速跳出局部最优解,收敛速度至少增加了2¹0倍。

A modified genetic algorithm used for synthesis of linear arrays

In order to improve the convergence speed and the target array synthesis function of local optimum,the deficiencies of the existing genetic algorithm are analyzed,and a modified genetic algorithm for synthesis of linear arrays is proposed in this paper because the existing genetic algorithm is easy to occur the local convergence when it conducts the synthesis of linear arrays. A search scheme to enhance the scope of individual search program so as to jump out of the local optimal solution is proposed in consideration of the problems that the existing algorithms are not strong in realcoded search capability and is easy to trap in the local optima solution. It′s an effective way to solve the problem. Simulation results show that the modified algorithm can make the object function jump out of local optimum solution rapidly,and the convergence speed is substantially increased by at least 2~10 times,comparing with the origin method.