Evolutionary computation of multi-band antenna using multi-objective evolutionary algorithm based on decomposition

Authors:
Dawei Ding;Hongjin Wang;Gang Wang
Affiliations:
Department of Telecommunication Engineering, UJS, Zhenjiang, China;Department of Telecommunication Engineering, UJS, Zhenjiang, China;Department of Electronic Engineering and Information Science, USTC, Hefei, China
Venue:
ICICA'11 Proceedings of the Second international conference on Information Computing and Applications
Year:
2011

Citing 4
Cited 0

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Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II

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A fast and elitist multiobjective genetic algorithm: NSGA-II

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MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition

IEEE Transactions on Evolutionary Computation

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Abstract

Design of multi-band antenna involves multiple characteristics such as return loss in multiple operation bands. To apply MOEA/D (multi-objective evolutionary algorithm based on decomposition) to antenna structure optimization, it was introduced into this field for the first time. MOEA/D framework was demonstrated at first. Then it was in conjunction with electromagnetic solver, HFSS (high frequency structure simulator) to optimize and design tri-band bow-tie antenna to serve as an example. The evolutionary results showed that MOEA/D worked efficiently and generated multiple candidate structures at one single iteration, and that MOEA/D had lower computational overhead than NSGA-II (non-dominated sorting genetic algorithm II) for this problem. Therefore, MOEA/D shows great potential for antenna structure optimization and design.