异构多种群双交换遗传算法综合矩形平面阵列

Synthesis of Plane Array Using Double-crossover Genetic Algorithm Based on Isomerous Multi-population

提出了一种异构多种群双交换遗传算法并应用该算法来综合矩形平面阵列。该算法通过多个异构子种群并行进化与对精英解的双交换遗传策略相结合的方法,摆脱了传统遗传算法收敛对初始群体的依赖性,克服了收敛陷入局部最优值的缺陷。为了说明该算法的有效性和实用性,运用异构多种群双交换遗传算法对矩形平面阵列的激励幅度和阵元位置进行了优化。

The double-crossover genetic algorithm based on isomerous multi-population is presented, and which is used to synthesis plane array. The convergence get rid of the dependence to initial population through combining parallel evolution of multiple heterogeneous populations and genetic strategy of double-crossover operator, and which overcomes the bug of getting in local optimal value. The algorithm is used to optimize the excitation amplitude and element position of plane array in order to show its validity and practicability.