A comprehensive review of swarm optimization algorithms

Mohd Nadhir Wahab, Samia Nefti-Meziani, Adham Atyabi

    Research output: Contribution to journalArticlepeer-review

    403 Citations (Scopus)


    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.

    Original languageEnglish
    Article numbere0122827
    Pages (from-to)e0122827
    Number of pages36
    JournalPLoS One
    Issue number5
    Publication statusPublished - 18 May 2015


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