Optimization designs in patch antennas using nature-inspired metaheuristic algorithms: A review

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Abstract

In this article we present a general review of nature-inspired metaheuristic algorithms with implementations in patch antenna designs. The primary focus is on Genetic Algorithm (GA), Differential Evolution (DE), Particle Swarm Optimization (PSO), Bacterial Foraging Optimization (BFO). New algorithms recently been introduced also are analyzed, such as: Firefly algorithm (FA), Cuckoo Search (CS), Bat algorithm (BA), Social Spider Optimization (SSO) and Spider Monkey Optimization (SMO). Of each algorithm, a summary of significant examples and a flowchart for a quick and easy interpretation are presented. Finally, the common characteristics of algorithms are compared, concluding in a hierarchical classification according to the efficiency of each one to solve the patch antenna problems.

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Poveda-Pulla, D. F., Vicente Dominguez-Paute, J., Guerrero-Vasquez, L. F., Andres Chasi-Pesantez, P., Ordonez-Ordonez, J. O., & Esteban Vintimilla-Tapia, P. (2019). Optimization designs in patch antennas using nature-inspired metaheuristic algorithms: A review. In 2018 IEEE Biennial Congress of Argentina, ARGENCON 2018. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ARGENCON.2018.8646110

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