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

Poveda-Pulla, Danilo F.; Dominguez-Paute, Jefferson Vicente; Chasi-Pesántez, Paúl A.; Ordoñez-Ordoñez, Jorge O.; Vintimilla-Tapia, Paul E.

doi:10.1109/argencon.2018.8646110

Cited by 8 publications

(1 citation statement)

References 51 publications

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“…The algorithm ends when the satisfying fitness level has been reached for the population, or the maximum has been achieved [6]. GA in designing microstrip antennas can provide optimal results on antenna impedance and faster convergence time [7].…”

Section: Introductionmentioning

confidence: 99%

A Microstrip Antenna Design Using an Heuristic Algorithm

Wiryawan

Wahyuningtyas

Persada

et al. 2020

IJITEE

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Microstrip antennas have several advantages. Some of them are that they have a compact shape and small dimensions. Moreover, they are also easy to be fabricated and easily connected as well as integrated with other electronic devices. Currently, designing antennas conventionally is limited by time, energy, and experience as well as expertise. As an alternative, a way to design antennas with revolutionary methods is developed using algorithms and computing. Algorithm design techniques can overcome limitations and automatically find practical solutions that usually take a long time to discover. The particle swarm optimization algorithm and a genetic algorithm can find solutions from microstrip antennas. Objective functions play an essential role in heuristic algorithms. With a proper objective function, simulation results are obtained on the particle swarm optimization algorithm with a return loss value of -47.837, VSWR of 1.0083, and impedance of 46.805 Ω. In contrast, the genetic algorithm obtains return loss of -16.157 dB, impedance of 50.233 Ω, and VSWR of 1.3687.

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Section: Introductionmentioning

confidence: 99%