IDEAS home Printed from https://ideas.repec.org/a/igg/jsir00/v15y2024i1p1-29.html
   My bibliography  Save this article

A Survey on Manta Ray Foraging Optimization Algorithm of Variants and Applications

Author

Listed:
  • Yangyang Zheng

    (Zhejiang Normal University, China)

  • Leyi Wang

    (Zhejiang Normal University, China)

  • Jialing Hu

    (Zhejiang Normal University, China)

  • Zhaolong Ouyang

    (Zhejiang Normal University, China)

  • Donglin Zhu

    (Zhejiang Normal University, China)

  • Xuhua Zhao

    (Zhejiang Guangsha Vocational and Technical University of Construction, China)

Abstract

This review paper delves into the original MRFO and its variants, focusing on single-objective algorithms including but not limited to hybrid algorithms, learning strategies, multiple populations and dynamic parameter adjustment, highlighting the improvements made to enhance the algorithm's efficiency in global optimization, accelerate convergence rates, and improve its capacity to evade local optima. MRFO has emerged as an effective tool for solving complex optimization problems across various domains, including energy optimization, biomedical field, engineering problems, and others. A comprehensive analysis of applications of MRFO in different fields is provided, emphasizing its adaptability and efficacy. The paper concludes with a discussion on the challenges faced by MRFO and potential future research directions, aiming to consolidate the current research status and guide future investigations.

Suggested Citation

  • Yangyang Zheng & Leyi Wang & Jialing Hu & Zhaolong Ouyang & Donglin Zhu & Xuhua Zhao, 2024. "A Survey on Manta Ray Foraging Optimization Algorithm of Variants and Applications," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 15(1), pages 1-29, January.
    • Handle: RePEc:igg:jsir00:v:15:y:2024:i:1:p:1-29
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSIR.349907
    Download Restriction: no
    ---><---

    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:igg:jsir00:v:15:y:2024:i:1:p:1-29. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.