International Journal of Computational Intelligence Systems

Volume 14, Issue 1, 2021, Pages 386 - 411

Multi-Attribute Decision-Making Using Hesitant Fuzzy Dombi–Archimedean Weighted Aggregation Operators

Authors
Peide Liu1, *, ORCID, Abhijit Saha2, Debjit Dutta3, Samarjit Kar4
1School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan Shandong, 250014, China
2Faculty of Mathematics, Techno College of Engineering Agartala, Tripura, 799004, India
3Faculty of Basic and Applied Science, NIT Arunachal Pradesh, Arunachal Pradesh, 791112, India
4Faculty of Mathematics, NIT Durgapur, West Bengal, 713209, India
*Corresponding author. Email: peide.liu@gmail.com
Corresponding Author
Peide Liu
Received 7 September 2020, Accepted 11 December 2020, Available Online 22 December 2020.
DOI
10.2991/ijcis.d.201215.003How to use a DOI?
Keywords
Hesitant fuzzy set; Archimedean t-norm and t-conorm; Dombi t-norm and t-conorm; Dombi–Archimedean weighted aggregation operators; multi-attribute decision-making
Abstract

Multi-attribute decision-making (MADM) has been receiving great attention in recent years due to two major issues which are basically to describe attribute values and secondly to aggregate the described information to generate a ranking of alternatives. For the first case it entails the hesitant fuzzy elements (HFEs) as a more flexible and general tool in comparison to fuzzy set theory and for the second one, we allow the aggregation operator (AO) as an effective tool. Having said that there is not yet reported an AO which can provide desirable generality and flexibility in aggregating attribute values under hesitant fuzzy (HF) environment, although many AOs have been developed earlier to attempt to meet above such eventualities. So, the primary objective of this paper is to develop some general as well as flexible AOs that can be exploited to solve MADM problems with the HF information. From this perspective, at the very beginning, we develop some operations between HFEs by uniting the features of Dombi and Archimedean operations. Next, we bring up some HF weighted AOs based on Dombi and Archimedean operations. We discuss in detail some intriguing properties of the proposed AOs. Secondly, we emphasize establishing a procedure of MADM endowed by the proposed operators under the HF environment. Finally, we present a practical example concerning human resource selection to gloss the decision steps of the proposed method and at the same time, we explore the feasibility of the new method.

Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)
View full text (HTML)

Journal
International Journal of Computational Intelligence Systems
Volume-Issue
14 - 1
Pages
386 - 411
Publication Date
2020/12/22
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.201215.003How to use a DOI?
Copyright
© 2021 The Authors. Published by Atlantis Press B.V.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Peide Liu
AU  - Abhijit Saha
AU  - Debjit Dutta
AU  - Samarjit Kar
PY  - 2020
DA  - 2020/12/22
TI  - Multi-Attribute Decision-Making Using Hesitant Fuzzy Dombi–Archimedean Weighted Aggregation Operators
JO  - International Journal of Computational Intelligence Systems
SP  - 386
EP  - 411
VL  - 14
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.201215.003
DO  - 10.2991/ijcis.d.201215.003
ID  - Liu2020
ER  -