CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Migration Effects on BBO Evolution in Optimizing Fifteen Element Yagi-Uda Antenna Design

by Gagan Sachdeva, Dilpal Singh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 18
Year of Publication: 2013
Authors: Gagan Sachdeva, Dilpal Singh
10.5120/11676-7346

Gagan Sachdeva, Dilpal Singh . Migration Effects on BBO Evolution in Optimizing Fifteen Element Yagi-Uda Antenna Design. International Journal of Computer Applications. 68, 18 ( April 2013), 1-5. DOI=10.5120/11676-7346

@article{ 10.5120/11676-7346,
author = { Gagan Sachdeva, Dilpal Singh },
title = { Migration Effects on BBO Evolution in Optimizing Fifteen Element Yagi-Uda Antenna Design },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 18 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number18/11676-7346/ },
doi = { 10.5120/11676-7346 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:28:10.706972+05:30
%A Gagan Sachdeva
%A Dilpal Singh
%T Migration Effects on BBO Evolution in Optimizing Fifteen Element Yagi-Uda Antenna Design
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 18
%P 1-5
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Biogeography Based Optimization (BBO) is a recently introduced optimization technique based on science of biogeography, i. e. , study of distribution of biological species over space and time. In BBO, potential solutions of a problem are grouped in integer vectors known as habitats. Feature, i. e. , Suitability Index Variable (SIV), sharing among various habitats is made to occur with migration operator where as exploration of new SIVs is done with mutation operator. Different migration variants are proposed to increase the diversity in the population, with objective of improved performance of BBO algorithm. Yagi-Uda antenna is a widely used antenna design due to various useful properties of high gain, low cost and ease of construction. Designing a Yagi-Uda antenna involves determination of element lengths and spacings between them to get desired radiation characteristics. In this paper, various migration variants of BBO algorithm, reported till date, are investigated to optimize the lengths and spacings for Yagi-Uda antenna elements for maximum gain. The results obtained with these migration variants are compared and the best results are presented in the ending sections of the paper.

References
  1. E. E. Altshuler and D. S. Linden. Wire-antenna Designs using Genetic Algorithms. Antennas and Propagation Magazine, IEEE, 39(2):33–43, 1997.
  2. A. N. Amaral, U. C. Resende, and E. N. Gonc¸alves. Yagi-uda antenna optimization by elipsoid algorithm. pages 503– 506, 2011.
  3. A. Wallace. The Geographical Distribution of Animals. Boston, MA: Adamant Media Corporation, Two:232–237, 2005.
  4. S. Baskar, A. Alphones, P N Suganthan, and J J Liang. Design of Yagi-Uda Antennas using Comprehensive Learning Particle Swarm Optimisation. IEEE, 152(5):340–346, 2005.
  5. JH Bojsen, H. Schjaer-Jacobsen, E. Nilsson, and J. Bach Andersen. Maximum Gain of Yagi–Uda Arrays. Electronics Letters, 7(18):531–532, 1971.
  6. G. J. Burke and A. J. Poggio. Numerical Electromagnetics Code (NEC) method of moments. NOSC Tech. DocLawrence Livermore National Laboratory, Livermore, Calif, USA, 116:1–131, 1981.
  7. C. Chen and D. Cheng. Optimum Element Lengths for Yagi-Uda Arrays. IEEE Transactions on Antennas and Propagation,, 23(1):8–15, 1975.
  8. D. Cheng and C. Chen. Optimum Element Spacings for Yagi-Uda Arrays. IEEE Transactions on Antennas and Propagation,, 21(5):615–623, 1973.
  9. D. K. Cheng. Optimization Techniques for Antenna Arrays. Proceedings of the IEEE, 59(12):1664–1674, 1971.
  10. D. K. Cheng. Gain Optimization for Yagi-Uda Arrays. Antennas and Propagation Magazine, IEEE, 33(3):42–46, 1991.
  11. D. Correia, A. J. M. Soares, and M. A. B. Terada. Optimization of gain, impedance and bandwidth in Yagi-Uda Antennas using Genetic Algorithm. IEEE, 1:41–44, 1999.
  12. C. Darwin. The Orign of Species. New York : gramercy, Two:398–403, 1995.
  13. D. Du, D. Simon, and M. Ergezer. Biogeography-based Optimization Combined with Evolutionary Strategy and Immigration Refusal. IEEE, 1:997–1002, 2009.
  14. H. Ehrenspeck and H. Poehler. A New Method for Obtaining Maximum Gain from Yagi Antennas. IRE Transactions on Antennas and Propagation,, 7(4):379–386, 1959.
  15. R. M. Fishenden and E. R. Wiblin. Design of Yagi Aerials. Proceedings of the IEE-Part III: Radio and Communication Engineering, 96(39):5, 1949.
  16. E. A. Jones andW. T. Joines. Design of Yagi-Uda Antennas using Genetic Algorithms. IEEE Transactions on Antennas and Propagation,, 45(9):1386–1392, 1997.
  17. Y. Kuwahara. Multiobjective Optimization Design of Yagi- Uda Antenna. IEEE Transactions on Antennas and Propagation,, 53(6):1984–1992, 2005.
  18. J. Y. Li. Optimizing Design of Antenna using Differential Evolution. IEEE, 1:1–4, 2007.
  19. J. Y. Li. A bi-swarm optimizing strategy and its application of antenna design. Journal of Electromagnetic Waves and Applications, 23(14-15):1877–1886, 2009.
  20. Y. Li, F. Yang, J. OuYang, and H. Zhou. Yagi-uda antenna optimization based on invasive weed optimization method. Electromagnetics, 31(8):571–577, 2011.
  21. H. Ma and D. Simon. Blended Biogeography-based Optimization for Constrained Optimization. Engineering Applications of Artificial Intelligence, 24(3):517–525, 2011.
  22. R. H. MacArthur and E. O. Wilson. The Theory of Island Biogeography. Princeton Univ Pr, 1967.
  23. T. McTavish and D. Restrepo. Evolving Solutions: The Genetic Algorithm and Evolution Strategies for Finding Optimal Parameters. Applications of Computational Intelligence in Biology, 1:55–78, 2008.
  24. S. S. Pattnaik, M. R. Lohokare, and S. Devi. Enhanced Biogeography-Based Optimization using Modified Clear Duplicate Operator. IEEE, 1:715–720, 2010.
  25. M. Rattan, M. S. Patterh, and B. S. Sohi. Optimization of Yagi-Uda Antenna using Simulated Annealing. Journal of Electromagnetic Waves and Applications, 22, 2(3):291– 299, 2008.
  26. D. G. Reid. The Gain of an Idealized Yagi Array. Journal of the Institution of Electrical Engineers-Part IIIA: Radiolocation,, 93(3):564–566, 1946.
  27. L. C. Shen. Directivity and Bandwidth of Single-band and Double-band Yagi Arrays. IEEE Transactions on Antennas and Propagation,, 20(6):778–780, 1972.
  28. D. Simon. Biogeography-based Optimization. IEEE Transactions on Evolutionary Computation,, 12(6):702–713, 2008.
  29. U. Singh, H. Kumar, and T. S. Kamal. Design of Yagi-Uda Antenna Using Biogeography Based Optimization. IEEE Transactions on Antennas and Propagation,, 58(10):3375– 3379, 2010.
  30. U. Singh, M. Rattan, N. Singh, and M. S. Patterh. Design of a Yagi-Uda Antenna by Simulated Annealing for Gain, Impedance and FBR. IEEE, 1:974–979, 2007.
  31. Shintaro Uda and Yasuto Mushiake. Yagi-Uda Antenna. Maruzen Company, Ltd, 1954.
  32. N. V. Venkatarayalu and T. Ray. Single and Multi-Objective Design of Yagi-Uda Antennas using Computational Intelligence. IEEE, 2:1237–1242, 2003.
  33. N. V. Venkatarayalu and T. Ray. Optimum Design of Yagi- Uda Antennas Using Computational Intelligence. IEEE Transactions on Antennas and Propagation,, 52(7):1811– 1818, 2004.
  34. H. J. Wang, K. F. Man, C. H. Chan, and K. M. Luk. Optimization of Yagi array by Hierarchical Genetic Algorithms. IEEE, 1:91–94, 2003.
  35. H. Yagi. Beam Transmission of Ultra Short Waves. Proceedings of the Institute of Radio Engineers, 16(6):715– 740, 1928. 5
Index Terms

Computer Science
Information Sciences

Keywords

Yagi-Uda Antenna Biogeography Based Optimization Antenna Gain Genetic Algorithm

Powered by PhDFocusTM