A New Jumping Genes Paradigm for an E-Shaped Folded Patch Feed Antenna Design

Yeung, S. H.; Man, K. F.

doi:https://doi.org/10.1155/2007/10672

International Journal of Microwave Science and Technology

On this page

Abstract References Copyright Related Articles

Research Article | Open Access

Volume 2007 | Article ID 010672 | https://doi.org/10.1155/2007/10672

A New Jumping Genes Paradigm for an E-Shaped Folded Patch Feed Antenna Design

S. H. Yeung¹and K. F. Man¹

Academic Editor: K. Yazdandoost

Received14 Jun 2007

Accepted03 Aug 2007

Published20 Sept 2007

Abstract

A novel evolutionary computing algorithm, namely, jumping genes evolutionary algorithm (JGEA) is used for the optimization of antenna designs. This scheme incorporates with a multiobjective strategy that enables the gene mobility within the same chromosome, or even to a different chromosome. This type of horizontal gene movement causes the genes to find the suitable locations to achieve the necessary building blocks in such a way that the quality of nondominated solutions and/or the Pareto-optimal solutions can be enhanced. This new scheme is robust and provides outputs in speed and accuracy. It also generates a range of widespread extreme solutions. The design of an E-shaped patch antenna was adopted for the purpose of design demonstration. An antenna structure with 91% impedance bandwidth for a frequency range of 3.6–9.6 GHz was selected amongst the nondominated solutions set for the hardware fabrication. Its measured performances both for impedance bandwidth and frequency range were in good agreement with the simulated solution. The cross-polarized field was found to be small in comparison, and the copolarized field can sustain the broadside radiation pattern over the frequency band. This methodology of optimization can be of an alternative approach for antenna design.

References

K. C. Gupta and M. Abouzahra, Analysis and Design of Planar Microwave Components, IEEE Computer Society Press, New York, NY, USA, 1994.
T. Bäck, U. Hammel, and H.-P. Schwefel, “Evolutionary computation: comments on the history and current state,” IEEE Transcatins on Evolutionary Computation, vol. 1, no. 1, pp. 3–17, 1997.
View at: Publisher Site | Google Scholar
K. F. Man, K.-S. Tang, and S. Kwong, Genetic Algorithms: Concepts and Designs, Springer, Berlin, Germany, 1999.
C. A. Coello Coello, D. A. van Veldhuizen, and G. B. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems, Kluwer Academic Publishers, Boston, Mass, USA, 2002.
K. Deb, A. Pratap, S. Agrawal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Transcations on Evolutionary Computation, vol. 6, no. 2, pp. 182–197, 2002.
View at: Publisher Site | Google Scholar
C. M. Fonseca and P. J. Fleming, “Multiobjective optimization and multiple constraint handling with evolutionary algorithms—I: a unified formulation,” IEEE Transactions on Systems, Man and Cybernetics, Part A, vol. 28, no. 1, pp. 26–37, 1998.
View at: Publisher Site | Google Scholar
M. Erickson, A. Mayer, and J. Horn, “The niched pareto genetic algorithm 2 applied to the design of groundwater remediation systems,” in Proceedings of the 1st International Conference on Evolutionary Multi-Criterion Optimization (EMO '01), vol. 1993, pp. 681–695, Springer, Zurich, Switzerland, March 2001.
View at: Google Scholar
C. Andrew, F. Peter, P. Hartmut, and F. Carlos, Genetic algorithm toolbox user's guide, version 1.2.
F. J. Villegas, T. Cwik, Y. Rahmay-Samii, and M. Manteghi, “A parallel electromagnetic genetic algorithm optimization (EGO) application for patch antenna design,” IEEE Transcations on Antennas and Propagation, vol. 52, no. 9, pp. 2424–2435, 2004.
View at: Publisher Site | Google Scholar
N. Fedoroff and D. Boststein, Eds., The Dynamic Genome: Barbara McClintock's Ideas in the Century of Genetics, Cold Spring Harbor Laboratory Press, New York, NY, USA, 1992.
A. B. Simoes and E. Costa, “Enhancing transposition performance,” in Proceedings of the Congress on Evolutionary Computation (CEC '99), vol. 2, pp. 1434–1441, Washington, DC, USA, July 1999.
View at: Publisher Site | Google Scholar
A. V. Spirov and A. B. Kazansky, “Jumping genes-mutators can rise efficacy of evolutionary search,” in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '02), pp. 561–568, New York, NY, USA, July 2002.
View at: Google Scholar
R. B. Kasat and S. K. Gupta, “Multi-objective optimization of an industrial fluidized-bed catalytic cracking unit (FCCU) using genetic algorithm with the jumping genes operator,” Computers & Chemical Engineering, vol. 27, no. 12, pp. 1785–1800, 2003.
View at: Publisher Site | Google Scholar
S. H. Sun, K. F. Man, B.-Z. Wang, and T. P. Wong, “An optimized wideband quarter-wave patch antenna design,” IEEE Antennas and Wireless Propagation Letters, vol. 4, no. 1, pp. 486–488, 2005.
View at: Publisher Site | Google Scholar
T. M. Chan, K. F. Man, K. S. Tang, and S. Kwong, “A jumping gene paradigm for evolutionary multiobjective optimization,” to appear in IEEE Transcations on Evolutionary Computation.
View at: Google Scholar
T. M. Chan, K. F. Man, K. S. Tang, and S. Kwong, “A jumping gene algorithm for multiobjective resource management in wideband CDMA systems,” The Computer Journal, vol. 48, no. 6, pp. 749–768, 2005.
View at: Publisher Site | Google Scholar
T. M. Chan, K. F. Man, K. S. Tang, and S. Kwong, “Optimization of wireless local area network in IC factory using a jumping-gene paradigm,” in Proceedings of the 3rd International IEEE Conference on Industrial Informatics (INDIN '05), pp. 773–778, Perth, Western Australia, August 2005.
View at: Publisher Site | Google Scholar
S. H. Yeung, W. T. Luk, H. K. Ng, K. F. Man, and C. H. Chan, “A jumping genes paradigm for the design of wide-band patch antenna with double shorting wall,” Microwave and Optical Technology Letters, vol. 49, no. 3, pp. 706–709, 2007.
View at: Publisher Site | Google Scholar
C. Y. Chiu and C. H. Chan, “A wideband antenna with a folded patch feed,” in Proceedings of the IEEE International Workshop on Antenna Technology: Small Antennas and Novel Metamaterials (IWAT '05), pp. 45–48, Singapore, March 2005.
View at: Publisher Site | Google Scholar
L. H. Caporale, Jumping Genes, in Darwin in the Genome: Molecular Strategies in Biological Evolution, McGraw-Hill, New York, NY, USA, 2003.
F. Yang, X.-X. Zhang, X. Ye, and Y. Rahmat-Samii, “Wide-band E-shaped patch antennas for wireless communications,” IEEE Transcations on Antennas and Propagation, vol. 49, no. 7, pp. 1094–1100, 2001.
View at: Publisher Site | Google Scholar
B.-L. Ooi, S. Qin, and M.-S. Leong, “Novel design of broadband stacked patch antenna,” IEEE Transcations on Antennas and Propagation, vol. 50, no. 10, pp. 1391–1395, 2002.
View at: Publisher Site | Google Scholar
IE3D is a trademark of Zeland Software.
J. Kennedy and R. C. Eberhart, Swarm Intelligence, Morgan Kaufmann, San Francisco, Calif, USA, 2001.
X. Li, “A non-dominated sorting particle swarm optimizer for multiobjective optimization,” in Proceedings of the Genetic and Evolutionary Computation (GECCO '03), vol. 2723 of Lecture Notes in Computer Science, pp. 37–48, Chicago, Ill, USA, July 2003.
View at: Google Scholar
T. O. Ting, M. V. C. Rao, and C. K. Loo, “A novel approach for unit commitment problem via an effective hybrid particle swarm optimization,” IEEE Transactions on Power Systems, vol. 21, no. 1, pp. 411–418, 2006.
View at: Publisher Site | Google Scholar
S. Genovesi, R. Mittra, A. Monorchio, and G. Manara, “Particle swarm optimization for the design of frequency selective surfaces,” IEEE Antennas and Wireless Propagation Letters, vol. 5, no. 1, pp. 277–279, 2006.
View at: Publisher Site | Google Scholar
B. Zhao, C. X. Guo, and Y. J. Cao, “A multiagent-based particle swarm optimization approach for optimal reactive power dispatch,” IEEE Transactions on Power Systems, vol. 20, no. 2, pp. 1070–1078, 2005.
View at: Publisher Site | Google Scholar
N. Jin and Y. Rahmat-Samii, “Advances in particle swarm optimization for antenna designs: real-number, binary, single-objective and multiobjective implementations,” IEEE Transactions on Antennas and Propagation, vol. 55, no. 3, pp. 556–567, 2007.
View at: Publisher Site | Google Scholar
A. I. Selvakumar and K. Thanushkodi, “A new particle swarm optimization solution to nonconvex economic dispatch problems,” IEEE Transactions on Power Systems, vol. 22, no. 1, pp. 42–51, 2007.
View at: Publisher Site | Google Scholar
Z. Bayraktar, P. L. Werner, and D. H. Werner, “The design of miniature three-element stochastic Yagi-Uda arrays using particle swarm optimization,” IEEE Antennas and Wireless Propagation Letters, vol. 5, no. 1, pp. 22–26, 2006.
View at: Publisher Site | Google Scholar
Y. Ma, C. Jiang, Z. Hou, and C. Wang, “The formulation of the optimal strategies for the electricity producers based on the particle swarm optimization algorithm,” IEEE Transactions on Power Systems, vol. 21, no. 4, pp. 1663–1671, 2006.
View at: Publisher Site | Google Scholar
S. L. Ho, S. Yang, G. Ni, and H. C. Wong, “A particle swarm optimization method with enhanced global search ability for design optimizations of electromagnetic devices,” IEEE Transactions on Magnetics, vol. 42, no. 4, pp. 1107–1110, 2006.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2007 S. H. Yeung and K. F. Man. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation Order printed copies

Views

180

Downloads

394

Citations