Genetic Learning Particle Swarm Optimization

Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanis...

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Veröffentlicht in:	IEEE transactions on cybernetics Jg. 46; H. 10; S. 2277 - 2290
Hauptverfasser:	Gong, Yue-Jiao, Li, Jing-Jing, Zhou, Yicong, Li, Yun, Chung, Henry Shu-Hung, Shi, Yu-Hui, Zhang, Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.10.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithm design and analysis Algorithms Animals Artificial Intelligence Bees Computer Simulation Convergence Efficiency Evolution & development Exemplar construction genetic algorithm (GA) Genetic algorithms Genetics Genetics, Behavioral hybrid method learning scheme Models, Genetic Optimization techniques particle swarm optimization (PSO) Sociology Statistics
ISSN:	2168-2267, 2168-2275, 2168-2275
Online-Zugang:	Volltext
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