IEEE Transactions on Magnetics · 2012 · 64 citations · 10 references
ArchitectureMathematicsAntennasDesign OptimizationOptimizationAntenna DesignEvolutionary OptimizationGenetic AlgorithmsMulti-objective Design OptimizationMulti-objective OptimizationMultiobjective OptimizationDifferential EvolutionDirectivityFront-to-back RatioGaussian MutationMulti-objective Evolutionary AlgorithmsMulti-objective Evolutionary ComputationMultiobjective Evolutionary AlgorithmsPareto Front Approximation
This paper presents a multi-objective evolutionary algorithm based on decomposition (MOEA/D) to design broadband optimal Yagi-Uda antennas. A multi-objective problem is formulated to achieve maximum directivity, minimum voltage standing wave ratio and maximum front-to-back ratio. The algorithm was applied to the design of optimal 3 to 10 elements Yagi-Uda antennas, whose optimal Pareto fronts are provided in a single picture. The multi-objective problem is decomposed by Chebyshev decomposition, and it is solved by differential evolution (DE) and Gaussian mutation operators in order to provide a better approximation of the Pareto front. The results show that the implemented MOEA/D is efficient for designing Yagi-Uda antennas.
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