In this paper, a hierarchical-based multi strategy improved whale optimization algorithm (MIWOA) is proposed to address inefficiencies in traditional antenna optimization processes. Chaotic mapping is employed to enhance the spatial distribution characteristics of the initial population in the Whale Optimization Algorithm (WOA). Global and local leaders are introduced to balance the algorithm’s global search and local exploration capabilities. Additionally, a differential mutation strategy is adopted to accelerate the convergence rate of WOA. The effectiveness of MIWOA is demonstrated using the CEC2019 functions and compared with five other algorithms. Furthermore, MIWOA is applied to optimizing a triple notch UWB antenna, addressing challenges such as extended optimization time, strong frequency selectivity, and mutual coupling between notch structures. Experimental results demonstrate that the performance of the algorithm has been significantly improved through the introduction of the enhanced strategy. The triple-notch UWB antenna optimized based on the MIWOA algorithm exhibits excellent performance and achieves more efficient suppression of the WiMAX (3.3~3.6 GHz), HIPERLAN (5.47~5.725 GHz), and ITU (8.025~8.40 GHz) bands.