2017
DOI: 10.13164/re.2017.1048
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Linear Array Pattern Synthesis Using An Improved Multiobjective Genetic Algorithm

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Cited by 3 publications
(6 citation statements)
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“…In the -th generation of evolution, one new population is combined by the offspring and the parent. One representative function for the normalized objective function values of the combined population can be calculated by fitting function or interpolation function [24]. The effective weight vector is corresponding to the dynamic reference points uniformly distributed on the representative function.…”
Section: Improved Multiobjective Genetic Algorithm With Dynamic Weighmentioning
confidence: 99%
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“…In the -th generation of evolution, one new population is combined by the offspring and the parent. One representative function for the normalized objective function values of the combined population can be calculated by fitting function or interpolation function [24]. The effective weight vector is corresponding to the dynamic reference points uniformly distributed on the representative function.…”
Section: Improved Multiobjective Genetic Algorithm With Dynamic Weighmentioning
confidence: 99%
“…The purpose of this paper is the same as that of [24], which is to improve the diversity of solutions of MOP. The three modifications in [24] are dynamic nondomination strategy, scope-constrained strategy, and front uniformly distributed strategy. These three modifications can improve the diversity of solutions and decrease the computational complexity.…”
Section: Improved Multiobjective Genetic Algorithm With Dynamic Weighmentioning
confidence: 99%
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