A comprehensive review of swarm optimization algorithms

Ab Wahab, MN; Nefti-Meziani, S; Atyabi, A

Abstract

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.

Citation

Ab Wahab, M., Nefti-Meziani, S., & Atyabi, A. (2015). A comprehensive review of swarm optimization algorithms. PLoS ONE, 10(5), e0122827. https://doi.org/10.1371/journal.pone.0122827

• Journal Article Type: Article
• Acceptance Date: Feb 15, 2015
• Publication Date: May 18, 2015
• Deposit Date: Jun 12, 2015
• Publicly Available Date: Apr 5, 2016
• Journal: PLoS ONE
• Electronic ISSN: 1932-6203
• Publisher: Public Library of Science
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 5
• Pages: e0122827
• DOI: https://doi.org/10.1371/journal.pone.0122827
• Publisher URL: http://dx.doi.org/10.1371/journal.pone.0122827
• Related Public URLs: http://www.plosone.org/
• Additional Information: Projects : Gamma Programme