IDEAS home Printed from https://ideas.repec.org/a/wsi/nmncxx/v15y2019i02ns1793005719500169.html
   My bibliography  Save this article

NonLinear Programming Approach for Single-Valued Neutrosophic TOPSIS Method

Author

Listed:
  • Pranab Biswas

    (Department of Mathematics, Jadavpur University, Kolkata 700032, West Bengal, India)

  • Surapati Pramanik

    (#x2020;Department of Mathematics, Nandalal Ghosh B.T. College, Panpur, Narayanpur 743126, West Bengal, India)

  • Bibhas C. Giri

    (Department of Mathematics, Jadavpur University, Kolkata 700032, West Bengal, India)

Abstract

We propose an approach for multi-attribute group decision-making (MAGDM) problems under neutrosophic information, where the preference values of alternatives over the attributes and the importance of attributes are expressed in terms of single-valued neutrosophic sets. Firstly, we develop a nonlinear programming approach based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to determine relative closeness intervals of alternatives. Secondly, we aggregate closeness intervals to find out the ranking order of all alternatives by computing their optimal membership degrees based on the ranking method of interval numbers. Finally, we provide an illustrative example to show the effectiveness of the proposed approach.

Suggested Citation

  • Pranab Biswas & Surapati Pramanik & Bibhas C. Giri, 2019. "NonLinear Programming Approach for Single-Valued Neutrosophic TOPSIS Method," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 307-326, July.
    • Handle: RePEc:wsi:nmncxx:v:15:y:2019:i:02:n:s1793005719500169
    DOI: 10.1142/S1793005719500169
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S1793005719500169
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S1793005719500169?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.

    Citations

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


    Cited by:

    1. Maysam Abedi, 2021. "Non-Euclidean distance measures in spatial data decision analysis: investigations for mineral potential mapping," Annals of Operations Research, Springer, vol. 303(1), pages 29-50, August.

    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:wsi:nmncxx:v:15:y:2019:i:02:n:s1793005719500169. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/nmnc/nmnc.shtml .

    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.