IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-031-35668-1_13.html
   My bibliography  Save this book chapter

Dombi Hamy Mean Operators Based on Complex Intuitionistic Fuzzy Uncertainty and Their Application in Multi-Attribute Decision-Making

In: Fuzzy Optimization, Decision-making and Operations Research

Author

Listed:
  • Tahir Mahmood

    (International Islamic University Islamabad, Department of Mathematics and Statistics)

  • Zeeshan Ali

    (International Islamic University Islamabad, Department of Mathematics and Statistics)

Abstract

To derive the best preference from the collection of preferences, decision-making information is one of the most important and dominant techniques to evaluate most problems in real-life dilemmas. Additionally, Hamy mean (HM) information is also used for aggregating the bundled information into a singleton set, computed based on algebraic laws. The main influence of this theory is to propose Dombi operational laws for complex intuitionistic fuzzy (CIF) information and try to construct the theory of HM information based on Dombi t-norm and t-conorm under the consideration of CIF information, called CIF Dombi HM (CIFDHM), CIF weighted Dombi HM (CIFWDHM), CIF Dombi dual HM (CIFDDHM), and CIF weighted Dombi dual HM (CIFWDDHM) operators. Further, we evaluated some valuable properties and results for the presented information in the investigated analysis. Moreover, MADM “multi-attribute decision-making” information is utilized in this manuscript based on pioneered operators and given some examples to justify the worth and dominancy of the evaluated information. Finally, we compared the evaluated information with some other old or prevailing information to enhance the quality of the derived operators.

Suggested Citation

  • Tahir Mahmood & Zeeshan Ali, 2023. "Dombi Hamy Mean Operators Based on Complex Intuitionistic Fuzzy Uncertainty and Their Application in Multi-Attribute Decision-Making," Springer Books, in: Chiranjibe Jana & Madhumangal Pal & Ghulam Muhiuddin & Peide Liu (ed.), Fuzzy Optimization, Decision-making and Operations Research, chapter 0, pages 257-280, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-35668-1_13
    DOI: 10.1007/978-3-031-35668-1_13
    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

    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:978-3-031-35668-1_13. 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.