Application of Genetic Algorithm for Binary Optimization of Microstrip Antennas: A Review

Jeevani W. Jayasinghe; Jeevani W. Jayasinghe

doi:10.3934/electreng.2021016

AIMS Electronics and Electrical Engineering

2021, Volume 5, Issue 4: 315-333. doi: 10.3934/electreng.2021016

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Review

Application of Genetic Algorithm for Binary Optimization of Microstrip Antennas: A Review

Jeevani W. Jayasinghe ^,

Department of Electronics, Wayamba University of Sri Lanka, Kuliyapitiya, Sri Lanka

Received: 23 September 2021 Accepted: 24 November 2021 Published: 02 December 2021

Researchers have proposed applying optimization techniques to improve performance of microstrip antennas (MSAs) in terms of bandwidth, radiation characteristics, polarization, directivity and size. The drawbacks of the conventional MSAs can be overcome by optimizing the antenna parameters while keeping a compact configuration. Applying a global optimizer is a better technique than using a local optimizer or a trial and error method for performance enhancement. This paper discusses genetic algorithm (GA) optimization of microstrip antennas presented by the antenna research community. The GA optimization procedure, antenna parameters optimized by using GA and the optimization objectives are presented by reviewing the literature. Further, evolution of GA in the field of MSAs and its significance are explored. Application of GA optimization to design broadband, multiband, high-directivity and miniature antennas is demonstrated with the support of several case studies giving an insight for further developments in the field.
- cost function,
- design optimization,
- genetic algorithms,
- microstrip antennas
Citation: Jeevani W. Jayasinghe. Application of Genetic Algorithm for Binary Optimization of Microstrip Antennas: A Review[J]. AIMS Electronics and Electrical Engineering, 2021, 5(4): 315-333. doi: 10.3934/electreng.2021016

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Abstract

Researchers have proposed applying optimization techniques to improve performance of microstrip antennas (MSAs) in terms of bandwidth, radiation characteristics, polarization, directivity and size. The drawbacks of the conventional MSAs can be overcome by optimizing the antenna parameters while keeping a compact configuration. Applying a global optimizer is a better technique than using a local optimizer or a trial and error method for performance enhancement. This paper discusses genetic algorithm (GA) optimization of microstrip antennas presented by the antenna research community. The GA optimization procedure, antenna parameters optimized by using GA and the optimization objectives are presented by reviewing the literature. Further, evolution of GA in the field of MSAs and its significance are explored. Application of GA optimization to design broadband, multiband, high-directivity and miniature antennas is demonstrated with the support of several case studies giving an insight for further developments in the field.

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