International Journal of Numerical Modelling: Electronic Networks, Devices and Fields
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II
IEEE Transactions on Evolutionary Computation
Design of a novel monopulse antenna system using the time-modulated antenna arrays
International Journal of RF and Microwave Computer-Aided Engineering
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
IEEE Transactions on Evolutionary Computation
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By using the time modulation technique in antenna arrays, the stringent requirements on excitation error tolerance can be relaxed. However, the sideband signals spaced at multiples of the modulation frequency need to be suppressed in some applications. Multiobjective optimization is an important tool in the design of arrays with conflicting goals, such as low sidelobe level, low sideband level, and narrow beamwidth in the time-modulated antenna arrays. In this paper, a novel multiobjective evolutionary algorithm based on objective decomposition (MOEA/D) with differential evolution operator and objective normalization technique is employed for the time-modulated array synthesis, which is typically a problem with disparately scaled conflicting objectives. The effectiveness of the method is demonstrated by comparing the performances obtained by MOEA/D with those of previously reported results obtained by a single-objective differential evolution algorithm and simulated annealing technique. Copyright © 2011 John Wiley & Sons, Ltd.