A comprehensive review of swarm optimization algorithms

Ab Wahab, MN, Nefti-Meziani, S and Atyabi, A 2015, 'A comprehensive review of swarm optimization algorithms' , PLoS ONE, 10 (5) , e0122827.

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Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained, and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE) and is closely followed by Particle Swarm Optimization (PSO), compared with other considered approaches.

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: PLoS ONE
Publisher: Public Library of Science
Refereed: Yes
Related URLs:
Funders: Regional Growth Fund
Depositing User: Christine Tate
Date Deposited: 12 Jun 2015 13:00
Last Modified: 15 Feb 2022 19:22
URI: https://usir.salford.ac.uk/id/eprint/35098

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