Benchmark antenna designs via wind driven optimization with dynamic control parameters

Abstract

An approach to accelerating the convergence of the wind driven optimization (WDO) is proposed based on a novel Taguchi-based dynamic control parameter (CP) identification method. To find the best CP combinations with different numbers of fitness evaluations, the Taguchi method is used, and the fitted dynamic CP functions are determined to represent the variation of each CP. Furthermore, an extra velocity update strategy is proposed, which integrates information from both the personal best and the global best to enhance the exploitation of WDO. The proposed algorithm is validated by nine benchmarks involving four functions and five antenna designs. Additionally, its optimization performance is compared with that of state-of-the-art meta-heuristic algorithms. The results demonstrate the effectiveness of this method in improving the convergence speed of WDO.