Dual Hesitant Fuzzy Set and Intuitionistic Fuzzy Ideal Based Computational Method for MCGDM Problem

Akanksha Singh and Sanjay Kumar
Additional contact information
Akanksha Singh: G. B. Pant University of Ag. & Technology, Pantnagar, India
Sanjay Kumar: G. B. Pant University of Ag. & Technology, Pantnagar, India

International Journal of Natural Computing Research (IJNCR), 2018, vol. 7, issue 3, 17-41

Abstract: In this article, the authors propose a computational method for multi criteria decision making problems using dual hesitant fuzzy information. In this study, the authors mention limitation of fuzzy ideals over a semi ring of positive integers and propose fuzzy ideal over a semi ring over subset of rationals. An intuitionistic fuzzy ideal of semi rings is also defined in this article which is used in idealizing aggregated dual hesitant group preference matrixes. The proposed approach appears in the form of simple computational algorithms. The main characteristic of the proposed approach is it considers the relationship between attributes, and so it takes into account relative preferences of attributes to find out the ranking order of attributes while other methods consider various attributes independently. An example of a supplier selection problem is undertaken to understand the implementation of the proposed computational approach based on MCGDM with dual hesitant information and ranking results compared with different methods.

Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJNCR.2018070102 (application/pdf)

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:igg:jncr00:v:7:y:2018:i:3:p:17-41

Access Statistics for this article

International Journal of Natural Computing Research (IJNCR) is currently edited by Xuewen Xia

More articles in International Journal of Natural Computing Research (IJNCR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().