Abstract
A modified differential evolution (MDE) algorithm based on a novel mutation strategy and adaptive adjustment strategy of parameter crossover rate (CR) is proposed to improve the population diversity and to avoid frapping in local optima. Also the simplified quadratic interpolation is employed to accelerate the convergence rate. Benchmark functions have been provided to verify the MDE algorithm. Compared with other improved evolutionary algorithms, experiment results reveal that the MDE has a promising performance in the convergence rate and the exploration ability. Finally, the proposed algorithm is proved to realize accelerating the optimization of time-modulated arrays (TMA).
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