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A COMPARISON OF GENETIC ALGORITHMS, PARTICLE SWARM OPTIMIZATION AND THE DIFFERENTIAL EVOLUTION METHOD FOR THE DESIGN OF SCANNABLE CIRCULAR ANTENNA ARRAYS

By M. A. Panduro, C. A. Brizuela, L. I. Balderas, and D. A. Acosta

Full Article PDF (549 KB)

Abstract:
A comparison between different modern population based optimization methods applied to the design of scannable circular antenna arrays is presented in this paper. This design of scannable circular arrays considers the optimization of the amplitude and phase excitations across the antenna elements to operate with optimal performance in the whole azimuth plane (360ο). Simulation results for scannable circular arrays with the amplitude and phase excitation optimized by genetic algorithms, particle swarm optimization and the differential evolution method are provided. Furthermore, in order to set which design case could provide a better performance in terms of the side lobe level and the directivity, a comparative analysis of the performance of the optimized designs with the case of conventional progressive phase excitation is achieved. Simulation results show that differential evolution and particle swarm optimization have similar performances and both of them had better performance compared to genetic algorithms when all algorithms are allowed equal computation time.

Citation:
M. A. Panduro, C. A. Brizuela, L. I. Balderas, and D. A. Acosta, "A comparison of genetic algorithms, particle swarm optimization and the differential evolution method for the design of scannable circular antenna arrays," Progress In Electromagnetics Research B, Vol. 13, 171-186, 2009.
doi:10.2528/PIERB09011308
http://www.jpier.org/pierb/pier.php?paper=09011308

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