Vol. 32

Latest Volume
All Volumes
All Issues

Fire Fly and Artificial Bees Colony Algorithm for Synthesis of Scanned and Broadside Linear Array Antenna

By Banani Basu and Gautam Mahanti
Progress In Electromagnetics Research B, Vol. 32, 169-190, 2011


This paper describes the application of two recently developed metaheuristic algorithms known as fire fly algorithm (FFA) and artificial bees colony (ABC) optimization for the design of linear array of isotropic sources. We present two examples: one for broad side arrays and the other for steerable linear arrays. Three instances are presented under each category consisting of different numbers of array elements and array pattern directions. The main objective of the work is to compute the radiation pattern with minimum side lobe level (SLL) for specified half power beam width (HPBW) and first null beam width (FNBW). HPBW and FNBW of a uniformly excited antenna array with similar size and main beam directions are chosen as the beam width constraints in each case. Algorithms are applied to determine the non-uniform excitation applied to each element. The effectiveness of the proposed algorithms for optimization of antenna problems is examined by all six sets of antenna configurations. Simulation results obtained in each case using both the algorithms are compared in a statistically significant way. Obtained results using fire fly algorithm shows better performances than that of artificial bees colony optimization technique provided that the same number of function evaluations has been considered for both the algorithms.


Banani Basu and Gautam Mahanti, "Fire Fly and Artificial Bees Colony Algorithm for Synthesis of Scanned and Broadside Linear Array Antenna," Progress In Electromagnetics Research B, Vol. 32, 169-190, 2011.


    1. Stutzman, W. L. and G. A. Thiele, Antenna Theory and Design, 2nd Ed., Wiley, Chichester, New York, Brisbane, Singapore, Toronto, 1998.

    2. Panduro, M. A., D. H. Covarrubias, C. A. Brizuela, and F. R. Marante, "A multi-objective approach in the linear antenna array design," AEU --- International Journal of Electronics and Communications, Vol. 59, No. 4, 205-212, 2005.

    3. EPFL, "Smart antenna systems for mobile communications," Technical Report EPFL CH-1015, Ecole Polytechnique Fédérale de Laussane, 2003.

    4. Liberti, J. C. and T. S. Rappaport, Smart Antennas for Wireless Communications: IS-95 and Third Generation CDMA Applications, Prentice Hall, New Jersey, 1999.

    5. Panduro, M., D. H. Covarrubias, and C. Brizuela, "Design of electronically steerable linear arrays with evolutionary algorithms," Applied Soft Computing, Vol. 8, 46-54, 2008.

    6. Eiben, A. E. and J. E. Smith, Introduction to Evolutionary Computing, Springer, 2003.

    7. Xie, P., K.-S. Chen, and Z.-S. He, "Synthesis of sparse cylindrical arrays using simulated annealing algorithm," Progress In Electromagnetics Research Letters, Vol. 9, 147-156, 2009.

    8. Kirkpatrik, S., C. Gelatt, and M. Vecchi, "Optimization by simulated annealing," Science, Vol. 220, 671-680, 1983.

    9. Haupt, R. L., "Adaptive nulling with weight constraints," Progress In Electromagnetics Research B, Vol. 26, 23-38, 2010.

    10. Hosseini, S. A. and Z. Atlasbaf, "Optimization of side lobe level and fixing quasi-nulls in both of the sum and difference patterns by using continuous ant colony optimization (ACO) method," Progress In Electromagnetics Research, Vol. 79, 321-337, 2008.

    11. Kennedy, J. and R. Eberhart, "Particle swarm optimization," Proc. IEEE Int. Conf. Neural Networks, 1942-1948, 1995.

    12. Pathak, N. N., B. Basu, and G. K. Mahanti, "Combination of inverse fast fourier transform and modified particle swarm optimization for synthesis of thinned mutually coupled linear array of parallel half-wave length dipole antennas," Progress In Electromagnetics Research M, Vol. 16, 105-115, 2011.

    13. Kim, S.-Y. and N.-H. Myung, "An optimal antenna pattern synthesis for active phased array SAR based on particle swarm optimization and adaptive weighting factor," Progress In Electromagnetics Research C, Vol. 10, 129-142, 2009.

    14. Mallahzadeh, A. R., H. Oraizi, and Z. Davoodi-Rad, "Application of the invasive weed optimization technique for antenna configurations," Progress In Electromagnetics Research, Vol. 79, 137-150, 2008.

    15. Sheng, N., C. Liao, W. Lin, L. Chang, Q. Zhang, and H. Zhou, "A hybrid optimized algorithm based on EGO and Taguchi's method for solving expensive evaluation problems of antenna design," Progress In Electromagnetics Research C, Vol. 17, 181-192, 2010.

    16. Dib, N. I., S. K. Goudos, and H. Muhsen, "Application of Taguchi's optimization method and self-adaptive differential evolution to the synthesis of linear antenna arrays," Progress In Electromagnetics Research, Vol. 102, 159-180, 2010.

    17. Chowdhury, A., A. Ghosh, R. Giri, and S. Das, "Optimization of antenna configuration with a fitness-adaptive differential evolution algorithm," Progress In Electromagnetics Research B, Vol. 26, 291-319, 2010.

    18. Pal, S., S. Das, and A. Basak, "Design of time-modulated linear arrays with a multi-objective optimization approach," Progress In Electromagnetics Research B, Vol. 23, 83-107, 2010.

    19. Pal, S., B. Qu, S. Das, and P. N. Suganthan, "Linear antenna array synthesis with constrained multi-objective differential evolution," Progress In Electromagnetics Research B, Vol. 21, 87-111, 2010.

    20. Lukasik, S. and S. Zak, Firefly algorithm for continuous constrained optimization tasks, Lecture Notes in Computer Science, Vol. 5796, Springer Link, 2009.

    21. Yang, X.-S., "Firefly algorithm, stochastic test functions and design optimization," International Journal of Bio-Inspired Computation, Vol. 2, No. 2, 2010.

    22. Karaboga, D. and B. Basturk, "Artificial Bee Colony (ABC) optimization algorithm for solving constrained optimization problems," LNCS: Advances in Soft Computing: Foundations of Fuzzy Logic and Soft Computing, Vol. 4529, 789-798, Springer-Verlag, 2007.

    23. Karaboga, D. and B. Basturk, "A powerful and efficient algorithm for numerical function optimization: Artificial Bee Colony (ABC) algorithm," Journal of Global Optimization, Vol. 39, No. 3, 459-471, Springer, 2007.

    24. Baykasoglu, A., L. Ozbakir, and P. Tapkan, "Artificial bee colony algorithm and its application to generalized assignment problem," Swarm Intelligence Focus on Ant and Particle Swarm Optimization, 113-144, I-Tech. Education and Publishing, Vienna, Austria, 2007.

    25. Elliott, R. S., Antenna Theory and Design, Wiley Interscience, New York, 2003.

    26. Gibbons, J. D., Nonparametric Statistical Inference, 2nd Ed., M. Dekker, 1985.

    27. Roy, G. G., S. Das, P. Chakraborty, and P. N. Suganthan, "Design of non-uniform circular antenna arrays using a modified invasive weed optimization algorithm," IEEE Transactions on Antennas and Propagation, Vol. 59, No. 1, 110-118, Jan. 2011.

    28. Panduro, M. A., C. A. Brizuela, L. I. Balderas, and D. A. Acosta, "A comparison of genetic algorithms, particle swarm optimization and the differential evolution method for the design of scanable circular antenna arrays," Progress In Electromagnetics Research B, Vol. 13, 171-186, 2009.