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Reseach Article

Multibeam Antennas Array Pattern Synthesis using Hybrid Particle Swarm Optimizer with Breeding and Subpopulations Algorithm

by Hichem Chaker, S. M. Meriah, F. T. Bendimerad
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 52 - Number 6
Year of Publication: 2012
Authors: Hichem Chaker, S. M. Meriah, F. T. Bendimerad
10.5120/8207-1615

Hichem Chaker, S. M. Meriah, F. T. Bendimerad . Multibeam Antennas Array Pattern Synthesis using Hybrid Particle Swarm Optimizer with Breeding and Subpopulations Algorithm. International Journal of Computer Applications. 52, 6 ( August 2012), 27-31. DOI=10.5120/8207-1615

@article{ 10.5120/8207-1615,
author = { Hichem Chaker, S. M. Meriah, F. T. Bendimerad },
title = { Multibeam Antennas Array Pattern Synthesis using Hybrid Particle Swarm Optimizer with Breeding and Subpopulations Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 52 },
number = { 6 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 27-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume52/number6/8207-1615/ },
doi = { 10.5120/8207-1615 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:51:35.069336+05:30
%A Hichem Chaker
%A S. M. Meriah
%A F. T. Bendimerad
%T Multibeam Antennas Array Pattern Synthesis using Hybrid Particle Swarm Optimizer with Breeding and Subpopulations Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 52
%N 6
%P 27-31
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper a new effective optimization algorithm called hybrid particle swarm optimizer with breeding and subpopulation is presented. This algorithm is essentially, as PSO and GA, a population-based heuristic search technique, now in use for the optimization of electromagnetic structures, modeled on the concepts of natural selection and evolution (GA) but also based on cultural and social rules derived from the analysis of the swarm intelligence and from the interaction among particles (PSO). The optimized design of multibeam antennas arrays is reported with numerical results.

References
  1. Torn, A. and Zilinskas, A. 1989. Global Optimization, lecture notes in computer science. New York springer-verlag, vol. 350.
  2. Lovbjerg, M. , Rasmussen, T. K. , and T. Krink. 2001. Hybrid Particle Swarm Optimizer with Breeding and Subpopulations, In Proceedings of the Genetic and Evolutionary Computation Conference, San Francisco.
  3. Akdagli, A and Guney, K. 2003. Shaped-beam Synthesis of Equally and Unequally Spaced Linear Antenna Arrays Using A Modified Tabu Search Algorithm, Microwave and Optical Technology Letters, Vol. 36, No. 1.
  4. Spears, W. M. 1994. Simple subpopulation schemes, proceeding of the evolutionary programming conference, pp. 296-30.
  5. Kennedy, J. and Eberhart, R. C. 1995. Particle swarm optimization, IEEE proceeding of international conference on neural networks, vol. 4, pp. 1942-1948.
  6. Y. Shi, R. C. Eberhart, A modified particle swarm optimiser, IEEE international conference on evolutionary computation, Alaska, May 1998.
  7. Shi, Y. and Eberhart, R. C. 1998. Parameter selection in particle swarm optimization, lecture notes in computer science. Evolutionary programming VII, 591-600. Springer.
  8. Kennedy, J. 1999. Small words and mega-minds: Effects of neighbourhood topology on particle swarm performance, proceedings of the congress of evolutionary computation, vol. 3, pp. 1931-1938. IEEE.
  9. Ghayoula, R. , Traii, M. , and Gharsallah, A. 2006. Application of the Neural Network to the Synthesis of Multibeam Antennas Arrays, Transaction on engineering, computing and technology. Vol. 14. August
Index Terms

Computer Science
Information Sciences

Keywords

Hybrid Particle Swarm Optimizer Synthesis Multibeam Linear Antenna Arrays