IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v15y2024i6d10.1007_s13198-023-02243-1.html
   My bibliography  Save this article

Recent development and applications of neutrosophic fuzzy optimization approach

Author

Listed:
  • Debasmita Sarkar

    (Jaypee Institute of Information Technology)

  • Pankaj Kumar Srivastava

    (Jaypee Institute of Information Technology)

Abstract

In order to handle incomplete, ambiguous, and inconsistent data, the concept of a neutrosophic set (NS) has gained immense popularity. Due to its independent indeterminacy component, it has been shown to be a successful tactic and expanded in literature by numerous experts. The primary aim of the current study is to discuss the generality of the NS and its development processes within the studied field. According to the requirements in various sectors, there have been numerous techniques and improvements toward neutrosophic perception during these periods. To understand the most current developments in the neutrosophic approach, a review of the last ten years literature has been conducted in the current study. To comprehend the advantages and disadvantages of various approaches, tabular and graphical comparisons are included. Based on the outcomes of the review papers, managerial implications have been investigated. For further comprehension, the research gap between existing methods and corresponding future approach is also emphasized.

Suggested Citation

  • Debasmita Sarkar & Pankaj Kumar Srivastava, 2024. "Recent development and applications of neutrosophic fuzzy optimization approach," 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. 15(6), pages 2042-2066, June.
    • Handle: RePEc:spr:ijsaem:v:15:y:2024:i:6:d:10.1007_s13198-023-02243-1
    DOI: 10.1007/s13198-023-02243-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-023-02243-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-023-02243-1?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Foroogh Behroozi & Seyed Mohammad Hassan Hosseini & Shib Sankar Sana, 2021. "Teaching–learning-based genetic algorithm (TLBGA): an improved solution method for continuous optimization problems," 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. 12(6), pages 1362-1384, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Swarupa Pinninti & Srinivasa Rao Sura, 2023. "Renewables based dynamic cost-effective optimal scheduling of distributed generators using teaching–learning-based optimization," 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. 14(1), pages 353-373, March.

    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:spr:ijsaem:v:15:y:2024:i:6:d:10.1007_s13198-023-02243-1. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.