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Evolutionary Intelligence
Erschienen in: Evolutionary Intelligence 2/2019

21.02.2019 | Review Article

A survey on particle swarm optimization with emphasis on engineering and network applications

verfasst von: Mohammed Elbes, Shadi Alzubi, Tarek Kanan, Ala Al-Fuqaha, Bilal Hawashin

Erschienen in: Evolutionary Intelligence | Ausgabe 2/2019

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Abstract

Swarm intelligence is a kind of artificial intelligence that is based on the collective behavior of the decentralized and self-organized systems. This work focuses on reviewing a heuristic global optimization method called particle swarm optimization (PSO). This includes the mathematical representation of PSO in contentious and binary spaces, the evolution and modifications of PSO over the last two decades. We also present a comprehensive taxonomy of heuristic-based optimization algorithms such as genetic algorithms, tabu search, simulated annealing, cross entropy and illustrate the advantages and disadvantages of these algorithms. Furthermore, we present the application of PSO on graphics processing unit and show various applications of PSO in networks.
Vorheriger Artikel Incremental supervised learning: algorithms and applications in pattern recognition
Nächster Artikel A new evolutionary neural networks based on intrusion detection systems using locust swarm optimization

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Metadaten
Titel
A survey on particle swarm optimization with emphasis on engineering and network applications
verfasst von
Mohammed Elbes
Shadi Alzubi
Tarek Kanan
Ala Al-Fuqaha
Bilal Hawashin
Publikationsdatum
21.02.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Evolutionary Intelligence / Ausgabe 2/2019
Print ISSN: 1864-5909
Elektronische ISSN: 1864-5917
DOI
https://doi.org/10.1007/s12065-019-00210-z

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