Research on Optimized Design of Antenna Based on Improved Whale Optimization Algorithm

In order to improve the efficiency of antenna design, various intelligent optimization algorithms are used for settling the complex nonlinear problems involved. The whale optimization algorithm (WOA) is one of the relatively novel and well-performing swarm intelligence optimization algorithms. In this article, an improved whale optimization algorithm (IWOA) is proposed in view of the shortcomings of WOA. First, the nonlinear control parameter, adaptive weight and Cauchy disturbance are introduced to improve algorithm performance. Then a CEC benchmark function set is selected to test the feasibility and effectiveness of IWOA. The results show that IWOA has obvious advantages in terms of convergence speed, convergence accuracy and stability. Finally, the algorithm is used for the optimization of structural parameters of two ultra-wideband (UWB) antennas. The automated design of antenna is realized by MATLAB and HFSS joint simulation.