A hybrid particle swarm optimization algorithm for solving engineering problem

To overcome the disadvantages of premature convergence and easy trapping into local optimum solutions, this paper proposes an improved particle swarm optimization algorithm (named NDWPSO algorithm) based on multiple hybrid strategies. Firstly, the elite opposition-based learning method is utilized t...

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Veröffentlicht in:	Scientific reports Jg. 14; H. 1; S. 8357 - 30
Hauptverfasser:	Qiao, Jinwei, Wang, Guangyuan, Yang, Zhi, Luo, Xiaochuan, Chen, Jun, Li, Kan, Liu, Pengbo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 10.04.2024 Nature Publishing Group Nature Portfolio
Schlagworte:	639/166/988 639/705/1042 Algorithms Convergence Convergence analysis Elite opposition-based learning Humanities and Social Sciences Iterative mapping multidisciplinary Optimization algorithms Particle swarm optimization Science Science (multidisciplinary) Iterative mapping Elite opposition-based learning Particle swarm optimization Convergence analysis
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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