Abstract
In this paper we are going to investigate the properties of Informative Differential Evolution with Self Adaptive Re-clustering technique (IDE_SR) algorithm on the problems of electromagnetic domain. Problems of electromagnetism domain generally exhibit multimodal characteristic as well as the high dimensionality and non-smooth attributes. IDE_SR is a modified Differential Evolution (DE) to overcome the problems of multimodality and complexity of the problem under consideration. In this paper we describe the salient features of IDE_SR and compare the result with other state-of-art algorithms.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Kennedy, J., Eberhart, R.C.: Particle Swarm Optimization. In: Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, pp. 1942–1948 (1995)
Passino, K.M.: Biomimicry of Bacterial Foraging for Distributed Optimization and Control. IEEE Control Systems Magazine 22, 52–67 (2002)
Dorigo, M., Stützle, T.: Ant Colony Optimization. MIT Press, Cambridge (2004)
Karaboga, D.: An Idea Based on Honey Bee Swarm for Numerical Optimization, technical REPORT-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department (2005)
Farmer, J.D., Packard, N., Perelson, A.: The Immune System, Adaptation and Machine Learning. Physica D 22, 187–204 (1986)
Holland, J.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)
Aihara, A., Takabe, T., Typoda, M.: Chaotic neural networks. Phys. Lett. A 144, 333–340 (1990)
Chen, X.S., Ong, Y.S., Lim, M.H., Tan, K.C.: A Multi-Facet Survey on Memetic Computation. IEEE Transactions on Evolutionary Computation 15(5), 591–607 (2011)
Storn, R., Price, K.V.: Differential Evolution-A simple and efficient Heuristic for Global Optimization over continuous Spaces. Journal of Global Optimization 11, 341–359 (1997)
Ilonen, J., Kamarainen, J.K., Lampinen, J.: Differential Evolution Training Algorithm for Feed-Forward Neural Networks. Neural Processing Letters 7, 93–105 (2003)
Storn, R.: Differential evolution design of an IIR-filter. In: Proceedings of IEEE Int. Conference on Evolutionary Computation, ICEC 1996, pp. 268–273. IEEE Press, New York (1996)
Boeringer, D.W., Werner, D.H.: Particle swarm optimization versus genetic algorithms for phased array synthesis. IEEE Transactions on Antennas and Propagation 52(3), 771–778 (2004)
Khodier, M.M., Eberhart, R.C.: Linear Array Geometry Synthesis with Minimum Sidelobe Level and Null Control Using Particle Swarm Optimization. IEEE Transactions on Antennas and Propagation 53(8), 2674–2679 (2005)
Mallahzadeh, A.R., Eshaghi, S., Alipour, A.: Design of an E-shaped MIMO antenna using IWO algorithm for wireless application at 5.8 GHz. Progress In Electromagnetics Research 90, 187–203 (2009)
Jain, R., Mani, G.S.: Dynamic thinning of antenna array using genetic algorithm. Progress In Electromagnetics Research B 32, 1–20 (2011)
Maity, D., Halder, U., Dasgupta, P.: An Informative Differential Evolution with Self Adaptive Re-clustering Technique. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds.) SEMCCO 2011, Part I. LNCS, vol. 7076, pp. 27–34. Springer, Heidelberg (2011)
Maity, D., Halder, U., Das, S., Vailakos, A.V.: An Informative Differential Evolution Algorithm With Self Adaptive Re-Clustering Technique for the Optimization of Phased Antenna Array. Progress In Electromagnetics Research B 40, 361–380 (2012)
Karimkashi, S., Kishk, A.A.: Invasive Weed Optimization and its Features in Electromagnetics. IEEE Transactions on Antennas and Propagation 58(4), 1269–1278 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Maity, D., Halder, U., Chaudhuri, S.S. (2012). Performance of Informative Differential Evolution Algorithm with Self Adaptive Re-clustering Technique on the Problems of Electromagnetism –The Linear Array Antenna Synthesis. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Nanda, P.K. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2012. Lecture Notes in Computer Science, vol 7677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35380-2_22
Download citation
DOI: https://doi.org/10.1007/978-3-642-35380-2_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35379-6
Online ISBN: 978-3-642-35380-2
eBook Packages: Computer ScienceComputer Science (R0)