Boosted arithmetic optimization algorithm with elite opposition-based pattern search mechanism and its promise to design microstrip patch antenna for WLAN and WiMAX

This paper investigates the performance of a novel artificial intelligence optimization technique in terms of designing a small size antenna that can be used for WLAN and WiMAX applications. In this regard, a boosted version of the arithmetic optimization algorithm is constructed as a novel artificial intelligence optimization technique with the aid of pattern search and elite opposition-based learning mechanisms. The proposed boosted arithmetic optimization algorithm is demonstrated for its superior explorative and exploitative behavior using classical fixed-dimensional, multimodal, and unimodal benchmark functions. The performance of the boosted arithmetic optimization algorithm is then presented for a real-world engineering optimization problem. For the latter challenge, a small size antenna that can be used for WLAN and WiMAX applications is designed. The obtained simulation results show that a compact small-sized patch antenna operating at WLAN and WiMAX frequencies can successfully be designed with the proposed boosted arithmetic optimization algorithm. Comparative evaluation against the state-of-the-art shows that efficiency is increased significantly since a bandwidth increase of up to 21% is achieved even with a more than 39% reduction in size.

Automated summary

This paper investigates the performance of a novel artificial intelligence optimization technique, the boosted arithmetic optimization algorithm, in designing small size antennas for WLAN and WiMAX applications. The algorithm demonstrates superior explorative and exploitative behavior and is applied to a real-world engineering optimization problem, resulting in the successful design of a compact small-sized patch antenna operating at WLAN and WiMAX frequencies. Comparative evaluation shows significant efficiency improvements with a bandwidth increase of up to 21% and a size reduction of over 39%.