IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0122827.html
   My bibliography  Save this article

A Comprehensive Review of Swarm Optimization Algorithms

Author

Listed:
  • Mohd Nadhir Ab Wahab
  • Samia Nefti-Meziani
  • Adham Atyabi

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.

Suggested Citation

  • Mohd Nadhir Ab Wahab & Samia Nefti-Meziani & Adham Atyabi, 2015. "A Comprehensive Review of Swarm Optimization Algorithms," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-36, May.
    • Handle: RePEc:plo:pone00:0122827
    DOI: 10.1371/journal.pone.0122827
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0122827
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0122827&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0122827?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Minfang Huang & Qiong Guo & Jing Liu & Xiaoxu Huang, 2018. "Mixed Model Assembly Line Scheduling Approach to Order Picking Problem in Online Supermarkets," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    2. Anupama Kaushik & Shivi Verma & Harsh Jot Singh & Gitika Chhabra, 2017. "Software cost optimization integrating fuzzy system and COA-Cuckoo optimization algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1461-1471, November.
    3. Kharkeshi, Behrad Alizadeh & Shafaghat, Rouzbeh & Jahanian, Omid & Alamian, Rezvan & Rezanejad, Kourosh, 2022. "Experimental study of an oscillating water column converter to optimize nonlinear PTO using genetic algorithm," Energy, Elsevier, vol. 260(C).
    4. Rehan Ali Khan & Shiyou Yang & Shafiullah Khan & Shah Fahad & Kalimullah, 2021. "A Multimodal Improved Particle Swarm Optimization for High Dimensional Problems in Electromagnetic Devices," Energies, MDPI, vol. 14(24), pages 1-19, December.
    5. De Vincenzo, Ilario & Massari, Giovanni F. & Giannoccaro, Ilaria & Carbone, Giuseppe & Grigolini, Paolo, 2018. "Mimicking the collective intelligence of human groups as an optimization tool for complex problems," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 259-266.
    6. Afroz Alam & Preeti Verma & Mohd Tariq & Adil Sarwar & Basem Alamri & Noore Zahra & Shabana Urooj, 2021. "Jellyfish Search Optimization Algorithm for MPP Tracking of PV System," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
    7. Hilkija Gaïus Tosso & Saulo Anderson Bibiano Jardim & Rafael Bloise & Max Mauro Dias Santos, 2022. "Spark Ignition Engine Modeling Using Optimized Artificial Neural Network," Energies, MDPI, vol. 15(18), pages 1-23, September.
    8. Khamis, Nurulaqilla & Selamat, Hazlina & Ismail, Fatimah Sham & Lutfy, Omar Farouq & Haniff, Mohamad Fadzli & Nordin, Ili Najaa Aimi Mohd, 2020. "Optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    9. Memon, Mudasir Ahmed & Mekhilef, Saad & Mubin, Marizan & Aamir, Muhammad, 2018. "Selective harmonic elimination in inverters using bio-inspired intelligent algorithms for renewable energy conversion applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2235-2253.
    10. Shafiq Ahmad, 2022. "Electromagnetic Field Optimization Based Selective Harmonic Elimination in a Cascaded Symmetric H-Bridge Inverter," Energies, MDPI, vol. 15(20), pages 1-18, October.
    11. Mustafa Erkan Turan, 2016. "Fuzzy Systems Tuned By Swarm Based Optimization Algorithms for Predicting Stream flow," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4345-4362, September.
    12. Hossein Hassani & Mohammad Reza Yeganegi & Xu Huang, 2021. "Fusing Nature with Computational Science for Optimal Signal Extraction," Stats, MDPI, vol. 4(1), pages 1-15, January.
    13. Sangeeta & Kapil Sharma & Manju Bala, 2020. "An ecological space based hybrid swarm-evolutionary algorithm for software reliability model parameter estimation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(1), pages 77-92, February.
    14. Islam, Towhidul & Meade, Nigel & Carson, Richard T. & Louviere, Jordan J. & Wang, Juan, 2022. "The usefulness of socio-demographic variables in predicting purchase decisions: Evidence from machine learning procedures," Journal of Business Research, Elsevier, vol. 151(C), pages 324-338.
    15. Ming Liu & Yang Xu & Abdul-Wahid Mohammed, 2016. "Decentralized Opportunistic Spectrum Resources Access Model and Algorithm toward Cooperative Ad-Hoc Networks," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-21, January.
    16. Himansu Das & Sanjay Prajapati & Mahendra Kumar Gourisaria & Radha Mohan Pattanayak & Abdalla Alameen & Manjur Kolhar, 2023. "Feature Selection Using Golden Jackal Optimization for Software Fault Prediction," Mathematics, MDPI, vol. 11(11), pages 1-28, May.
    17. Hormozi, Elham & Hu, Shuwen & Ding, Zhe & Tian, Yu-Chu & Wang, You-Gan & Yu, Zu-Guo & Zhang, Weizhe, 2022. "Energy-efficient virtual machine placement in data centres via an accelerated Genetic Algorithm with improved fitness computation," Energy, Elsevier, vol. 252(C).
    18. Shah Fahad & Shiyou Yang & Rehan Ali Khan & Shafiullah Khan & Shoaib Ahmed Khan, 2021. "A Multimodal Smart Quantum Particle Swarm Optimization for Electromagnetic Design Optimization Problems," Energies, MDPI, vol. 14(15), pages 1-11, July.
    19. Mohammad Javad Amoshahy & Mousa Shamsi & Mohammad Hossein Sedaaghi, 2016. "A Novel Flexible Inertia Weight Particle Swarm Optimization Algorithm," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-42, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0122827. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.