MOEA/D-GO for Fragmented Antenna Design

In this paper, a hybrid multiobjective evolutionary algorithm, MOEA/D-GO (Multiobjective Evolutionary Algorithm Based on Decomposition combined with Enhanced Genetic Operators), is proposed for fragment-type antenna design. It combines the ability and e-ciency of MOEA/D to deal with multiobjective optimization problems with the speciflc character of two-dimensional chromosome coding of genetic algorithm. And enhanced genetic operators are also introduced to generate new individuals. Numerical results of a set of six multiobjective 0/1 knapsack problems show that MOEA/D- GO with weighted sum decomposition approach outperforms original MOEA/D and MOEA/D-PR (MOEA/D combined with Path- Relinking operator). Then it's applied to optimize a CPW-fed monopole antenna to achieve band-notch characteristic. Both numerical and test results show that MOEA/D-GO is promising for solving multiobjective optimization problems about fragmented antenna.

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