IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-19-1449-2_6.html
   My bibliography  Save this book chapter

Knowledge Measure-Based q-Rung Orthopair Fuzzy Inventory Model

In: q-Rung Orthopair Fuzzy Sets

Author

Listed:
  • C. Sugapriya

    (Queen Mary’s College, University of Madras, Department of Mathematics)

  • S. Rajeswari

    (Queen Mary’s College, University of Madras, Department of Mathematics)

  • D. Nagarajan

    (Rajalakshmi Institute of Technology, Department of Mathematics)

  • K. Jeganathan

    (University of Madras, Amanujan Institute for Advanced Study in Mathematics)

Abstract

As a generalization of intuitionistic fuzzy set and Pythagorean fuzzy set, the q-Rung Orthopair Fuzzy Set (qROFS) and its application are implemented in some decision-making problems. So far the notion of qROFS is not yet applied in any inventory management problems. This chapter analyzed an inventory model under the q-rung orthopair fuzzy environment and utilized the knowledge measure of qROFS to the proposed model. This study explores an economic order quantity model with faulty products and screening errors. To satisfy the customers’ demand with perfect items, the proposed research utilized the product warranty claim strategy from the supplier. Since some of the faulty products are returned from the supplier without being replaced as good ones, this study examines under two cases say, the warranty unclaimed products are restored by mending option and the warranty unclaimed products are recovered by the emergency purchase option. For both cases, the q-Rung Orthopair Fuzzy (qROF) inventory model is framed by presuming the proportion of faulty products and the proportion of misclassification errors as q-Rung Orthopair Fuzzy Variables (qROFVs). The Knowledge Measure-based q-Rung Orthopair Fuzzy (KM-qROF) inventory model is proposed by computing the knowledge measure of qROFVs. The proposed model is illustrated with a numerical example along with the sensitivity analysis.

Suggested Citation

  • C. Sugapriya & S. Rajeswari & D. Nagarajan & K. Jeganathan, 2022. "Knowledge Measure-Based q-Rung Orthopair Fuzzy Inventory Model," Springer Books, in: Harish Garg (ed.), q-Rung Orthopair Fuzzy Sets, chapter 0, pages 139-166, Springer.
    • Handle: RePEc:spr:sprchp:978-981-19-1449-2_6
    DOI: 10.1007/978-981-19-1449-2_6
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:spr:sprchp:978-981-19-1449-2_6. 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: 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.