Improved self-adaptive genetic algorithm with quantum scheme for electromagnetic optimisation

In this study, an accurate and efficient quantum genetic algorithm (QGA) combined with an improved self-adaptive (SA) scheme is proposed to solve electromagnetic optimisation problems. QGA is employed as the main optimisation frame because of its wider search range and higher efficiency than the con...

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Veröffentlicht in:	IET microwaves, antennas & propagation antennas & propagation, 2014-09, Vol.8 (12), p.965-972
Hauptverfasser:	Wei, Xiao-Kun, Shao, Wei, Zhang, Cheng, Li, Jia-Lin, Wang, Bing-Zhong
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms crossover operation crossover probability Crossovers electromagnetic optimisation problem electromagnetic wave propagation finite difference time‐domain analysis finite difference time‐domain method finite element analysis flnite element method frequency selective surfaces Genetic algorithms HFSS improved SA scheme Iterative methods Mathematical analysis Mathematical models mutation rate Optimization probability QGA quantum genetic algorithm Searching self‐adaptive genetic algorithm
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