This paper investigates the use of clonal selection principles based on our immune system for optimization applications in electromagnetics. This concept is based on our immune system's ability to respond to an antigen and produce a pool of anti-body secreting cells. In addition to the common implementations of this algorithm where the affinity maturation and cloning principles of clonal selection principles are used, we utilize memory and the cross-over concepts that are common to other bio-inspired methods. The performance of the algorithm is investigated for well known mathematical test functions and its potential is demonstrated in the context of the design of a radar absorbing material and a planar phased array antenna with specific radiation and null characteristics.
2. Kennedy, J. and R. C. Eberhart, "Particle swarm optimization," Proc. IEEE Conf. Neural Networks IV, 1995.
3. Dorigo, M., V. Maniezzo, and A. Colorni, "The ant system: Optimization by a colony of cooperating agents," IEEE Trans. Systems, Man, and Cybernetics, Vol. 26, No. 1, 1-13, Part B, 1996.
4. Mori, K., M. Tsukiyama, and T. Fukuda, "Immune algorithm with searching diversity and its application to resource allocation problem," TIEE Japan, Vol. 113-C, No. 10, 872-878, 1993.
5. Haupt, R., "An introduction to genetic algorithms for electro-magnetics," IEEE Antennas and Propagation Magazine, Vol. 37, No. 2, 7-15, Apr. 1995.
6. Robinson, J. and Y. Rahmat-Samii, "Particle swarm optimization in electromagnetics," IEEE Trans. Antennas and Prop., Vol. 52, No. 2, 397-407, 2004.
7. Karaboga, N., K. Guney, and A. Akdagli, "Null steering of linear antenna arrays with use of modified touring ant colony optimization algorithm," Int. Journal of RF and Microwave Computer-Aided Engineering, Vol. 12, No. 4, 375-383, 2002.
8. Kilic, O., "Comparison of nature based optimization methods for multi-beam satellite antennas," Proc. Applied Computational Electromagnetics Conf., 2008.
9. Kilic, O., "FPGA accelerated phased array design using the ant colony optimization," Applied Comp. Electromag. Soc. Journal, 7, Feb. 2010.
10. De Castro, L. N. and F. J. Von Zuben, "Learning and optimization using the clonal selection principle," IEEE Trans. Evolutionary Computation, Vol. 6, 239-251, 2002.
11. Chun, J., H. Jung, and S. Hahn, "A study on comparison of optimization performances between immune algorithm and other heuristic algorithms ," IEEE Trans. on Magnetics, Vol. 34, No. 5, 2972-2975, 1998.
12. Campelo, F., F. G. Guimaraes, H. Igarashi, and J. A. Ramirez, "A clonal selection algorithm for optimization in electromagnetics," IEEE Trans. Magnetics, Vol. 41, 1736-1739, 2005.
13. Akdagli, A., K. Guney, and B. Babayigit, "Clonal selection algorithm for design of reconfigurable antenna array with discrete phase shifters," Journal of Electromagnetic Waves and Applications, Vol. 21, No. 2, 215-227, 2007.
14. Babayigit, B., A. Akdagli, and K. Guney, "A clonal selection algorithm for null synthesizing of antenna arrays by amplitude control ," Journal of Electromagnetic Waves and Applications, Vol. 20, No. 8, 1007-1020, 2006.
15. Ada, G. L. and G. Nossal, "The clonal selection theory," Scientific American, Vol. 257, 50-57, 1987.
16. Michielssen, E., J.-M. Sajer, S. Ranjithan, and R. Mittra, "Design of lightweight, broad-band microwave absorbers using genetic algorithms," IEEE Trans. on Microwave Theory and Tech., Vol. 41, No. 6/7, 1024-1031, 1993.
17. Chambers, B. and A. Tennant, "Optimised design of Jaumann radar absorbing materials using a genetic algorithm," IEE Proceedings Radar, Sonar and Navigation, Vol. 143, No. 1, 23-30, 1996.
18., "The cellular concept," The Bell System Technical Journal, Vol. 58, No. 1, 15-41, Jan. 1979.
19. Kilic, O. and A. I. Zaghloul, "Antenna aperture size reduction using sub-beam concept in multiple-spot-beam cellular satellite systems," Radio Science, Vol. 44, RS3001, May 2009.