EconPapers    
Economics at your fingertips  
 

On some new fuzzy entropy measure of Pythagorean fuzzy sets for decision-making based on an extended TOPSIS approach

H. D. Arora and Anjali Naithani

Journal of Management Analytics, 2024, vol. 11, issue 1, 87-109

Abstract: Fuzzy entropy measures are valuable tools in decision-making when dealing with uncertain or imprecise information. There exist many entropy measures for Pythagorean Fuzzy Sets (PFS) in the literature that fail to deal with the problem of providing reasonable or consistent results to the decision-makers. To deal with the shortcomings of the existing measures, this paper proposes a robust fuzzy entropy measure for PFS to facilitate decision-making under uncertainty. The usefulness of the measure is illustrated through an illustration of decision-making in a supplier selection problem and compared with existing fuzzy entropy measures. The Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) approach is also explored to solve the decision-making problem. The results demonstrate that the proposed measure can effectively capture the degree of uncertainty in the decision-making process, leading to more accurate decision outcomes by providing a reliable and robust ranking of alternatives.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/23270012.2024.2301748 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjmaxx:v:11:y:2024:i:1:p:87-109

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjma20

DOI: 10.1080/23270012.2024.2301748

Access Statistics for this article

Journal of Management Analytics is currently edited by Li Xu

More articles in Journal of Management Analytics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tjmaxx:v:11:y:2024:i:1:p:87-109