Automated Design of Microstrip Patch Antenna Using Ant Colony Optimization

Tung, Lam Vu; Manh, Linh Ho; Beccaria, Michele; Pirinoli, Paola

doi:10.1109/iceaa.2019.8879031

Cited by 11 publications

(4 citation statements)

References 1 publication

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“…Various optimization algorithms are commonly employed in the electromagnetic field to design antennas [ 6 ]. The most widely used algorithms are Genetic Algorithms (GA) [ 7 ], Particle Swarm Optimization (PSO) [ 8 ], Ant Colony Optimization (ACO) [ 9 ], Differential Evolution (DE) [ 10 ], and Grey Wolf Optimization (GWO) [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Design and performances improvement of an UWB antenna with DGS structure using a grey wolf optimization algorithm

Bouchachi,

Reddaf,

Boudjerda

et al. 2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

Design and performances improvement of an UWB antenna with DGS structure using a grey wolf optimization algorithm

Bouchachi,

Reddaf,

Boudjerda

et al. 2024

Heliyon

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“…Among these methods, conventional GA (combined with assignment simulation software) is stable and highly efficient. A version of the ant colony optimization (ACO) algorithm had been implemented to automatically design a microstrip patch antenna that operates at 3.5 GHz with a bandwidth of 50-170 MHz [22]. In [23], GA was used to develop a high-absorption, wideband metamaterial absorber.…”

Section: Introductionmentioning

confidence: 99%

Frequency-Selective Surface Stopband Designed with a Genetic Algorithm for Gain Enhancement of a Broadband Monopole Antenna

Nguyen

Seo

2022

J Electromagn Eng Sci

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This paper presents an unusual, high-performance, cost-efficient, wideband frequency-selective surface (FSS) designed with a genetic algorithm (GA) and its effect on the performance of a broadband M-shaped monopole antenna. Each FSS unit cell with the dimensions of 0.2λ0 × 0.2λ0 × 0.01λ0 acts as a stopband filter for a wide bandwidth of 5.5 GHz (105%, 2.6–8.1 GHz). The FSS properties and advantages to antennas were tested via numerical simulations and measurements, respectively. Using the 6×6 array of the designed FSS unit cell as a reflector, the antenna impedance bandwidth improved from 96.1% (3.1–8.1 GHz) to 98.07% (3.3–8.4 GHz), with a center frequency of 5.2 GHz. In addition, the antenna gain improved at the maximum of 7.8 dBi, which was sustained from 9 dBi to 10.1 dBi for the entire bandwidth.

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“…Notwithstanding, the applicability of numerical algorithms to the generation of unconventional geometries is often demonstrated based on relatively simple, single-objective problems [28,29]. Furthermore, the optimization of generic models is normally undertaken using population-based routines (e.g., particle swarm optimization, genetic algorithms, or ant colony methods), which require thousands of evaluations to obtain the final solution [31,35,38,40]. To put that into perspective, in [41], the particle swarm algorithm required a total of 248 EM simulations to solve a set of 12 problems represented using only one input parameter.…”

Section: Introductionmentioning

confidence: 99%

EM-Driven Multi-Objective Optimization of a Generic Monopole Antenna by Means of a Nested Trust-Region Algorithm

et al. 2021

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Antenna structures for modern applications are characterized by complex and unintuitive topologies that are difficult to develop when conventional, experience-driven techniques are of use. In this work, a method for the automatic generation of antenna geometries in a multi-objective setup has been proposed. The approach involves optimization of a generic spline-based radiator with an adjustable number of parameters using a nested, trust region-based algorithm. The latter iteratively increases the dimensionality of the radiator in order to gradually improve its performance. The method has been used to generate a set of nine antenna designs, representing a trade-off between minimization of reflection within 3.1 GHz to 10.6 GHz and a reduction of size. The properties of the optimized designs vary along the Pareto set from −10 dB to −20 dB and from 230 mm2 to 757 mm2 for the first and second objectives, respectively. The presented design approach has been validated against a genuine, population-based optimization routine. Furthermore, the smallest Pareto-optimal design has been compared to the antennas from the literature.

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Automated Design of Microstrip Patch Antenna Using Ant Colony Optimization

Cited by 11 publications

References 1 publication

Design and performances improvement of an UWB antenna with DGS structure using a grey wolf optimization algorithm

Design and performances improvement of an UWB antenna with DGS structure using a grey wolf optimization algorithm

Frequency-Selective Surface Stopband Designed with a Genetic Algorithm for Gain Enhancement of a Broadband Monopole Antenna

EM-Driven Multi-Objective Optimization of a Generic Monopole Antenna by Means of a Nested Trust-Region Algorithm

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