Decision-making using novel ranking of intuitionistic fuzzy numbers based on vectorial distance and spread
N. Muhammad Farhan Hakim Nik Badrul Alam,
Ku Muhammad Naim Ku Khalif and
Nor Izzati Jaini
International Journal of Management and Decision Making, 2025, vol. 24, issue 3, 236-256
Abstract:
The intuitionistic fuzzy numbers (IFN) are powerful in handling the uncertainties in the decision-making world. In this research, a novel ranking function of the IFN based on the vectorial distances and spread of the membership and non-membership functions is proposed. The vectorial distance measures the separation of the IFN from the origin while the spread represents the horizontal slit of the IFN. As a validation, some empirical examples are used to illustrate the strength of the proposed ranking method. Some situations where the IFN having different heights and spreads for the membership and non-membership functions are considered to test the robustness of the ranking approach. Further, a decision-making model based on the proposed ranking method is developed, namely the intuitionistic weighted aggregated sum product assessment (IF-WASPAS). The preference of lecturers either to conduct online, hybrid or physical class was adopted to visualise the applicability of the proposed ranking function.
Keywords: decision-making; intuitionistic fuzzy numbers; IFN; ranking function; spread; vectorial distance. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=145915 (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:ids:ijmdma:v:24:y:2025:i:3:p:236-256
Access Statistics for this article
More articles in International Journal of Management and Decision Making from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().