Abstract:
An efficient variant of differential evolution (DE) algorithm, namely subpopulated differential evolution (subDE), is proposed for solving null synthesis problems of time-modulated circular antenna arrays by controlling time intervals and phases. The capabilities of subDE algorithm are examined by comparing its convergence curves and number of successful optimizations to those of the classical DE. Wilcoxon rank-sum test is also applied to ensure that the results are significant in terms of statistics. Furthermore, the antenna array parameters achieved by using subDE are compared to those of the classical DE in the literature. The results show that subDE can exhibit better performance than the classical DE for our antenna array synthesis examples. Additionally, the simulations are executed on an embedded microprocessor to investigate if subDE can also run on such a limited environment. The results demonstrate that the contemporary embedded systems hold promise for evolutionary algorithms.