Modified Multiobjective Evolutionary Algorithm Based on Decomposition for Antenna Design

For antenna design with multiobjective evolutionary algorithm based on decomposition (MOEA/D), population diversity and evolution speed of MOEA/D are two major concerns. Population diversity can be improved by selecting father- individuals along different search directions from external populations sorted by nondominated sorting strategy at small expense of evolution speed. Optimization results of given test instances and a tri-band bow-tie antenna indicate that the modified MOEA/D could generate a large set of alternative solutions in a more efficient way if compared to original MOEA/D. The modified MOEA/D is further demonstrated by designing a quad-band double-sided bow-tie antenna. Both numerical and test results show that modified MOEA/D is a promising multiobjective evolutionary algorithm for antenna design.

[1]  R. J. Acosta,et al.  A method for producing a shaped contour radiation pattern using a single shaped reflector and a single feed , 1988 .

[2]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[3]  Gang Wang,et al.  Tri‐band bow‐tie antenna with overlapped arms , 2010 .

[4]  Hisao Ishibuchi,et al.  Evolutionary many-objective optimization by NSGA-II and MOEA/D with large populations , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[5]  R. A. Pearson,et al.  A strategy for multiple contoured beam shaped reflector design , 1991 .

[6]  Hisao Ishibuchi,et al.  A multi-objective genetic local search algorithm and its application to flowshop scheduling , 1998, IEEE Trans. Syst. Man Cybern. Part C.

[7]  Qingfu Zhang,et al.  MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.

[8]  Qingfu Zhang,et al.  Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II , 2009, IEEE Transactions on Evolutionary Computation.

[9]  Y. Rahmat-Samii Array feeds for reflector surface distortion compensation: concepts and implementation , 1990, IEEE Antennas and Propagation Magazine.

[10]  Gang Wang,et al.  Evolutionary Computation of Multi-Band Antenna Using Multi-Objective Evolutionary Algorithm Based on Decomposition , 2011, ICICA.

[11]  Y. Rahmat-Samii A generalized reflector/array surface compensation algorithm for gain and sidelobe control , 1987, 1987 Antennas and Propagation Society International Symposium.

[12]  Kalyanmoy Deb,et al.  Self-Adaptive Genetic Algorithms with Simulated Binary Crossover , 2001, Evolutionary Computation.

[13]  Jasbir S. Arora,et al.  Survey of multi-objective optimization methods for engineering , 2004 .

[14]  R. Storn,et al.  Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .

[15]  E. K. Walton,et al.  Automobile conformal antenna design using non-dominated sorting genetic algorithm (NSGA) , 2006 .

[16]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[17]  L. I. Bialyi Optimal synthesis of linear antenna arrays , 1979 .

[18]  A. C. Lisboa,et al.  A Multi-Objective Evolutionary Algorithm Based on Decomposition for Optimal Design of Yagi-Uda Antennas , 2012, IEEE Transactions on Magnetics.

[19]  Wen-Chung Liu Design of a multiband CPW-fed monopole antenna using a particle swarm optimization approach , 2005, IEEE Transactions on Antennas and Propagation.

[20]  R.L. Rogers,et al.  Design and analysis of planar monopole antennas using a genetic algorithm approach , 2004, IEEE Transactions on Antennas and Propagation.

[21]  Marco Laumanns,et al.  Scalable multi-objective optimization test problems , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).