International Journal of Computational Intelligence Systems

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Volume 11, Issue 1, 2018, Pages 256 - 271

A Novel MAGDM Approach With Proportional Hesitant Fuzzy Sets

Authors
Sheng-Hua Xiong1, xsh@my.swjtu.edu.cn, Zhen-Song Chen2, *, zschen@whu.edu.cn, Kwai-Sang Chin3, mekschin@cityu.edu.hk
1College of Civil Aviation Safety Engineering, Civil Aviation Flight University of China, 46# Section 4, Nanchang Road, Guanghan, Sichuan 618307, People’s Republic of China
2School of Civil Engineering, Wuhan University, Wuhan 430072, China
3Department of Systems Engineering and Engineering Management, City University of Hong Kong, Kowloon Tong, Hong Kong, People’s Republic of China
*Corresponding author
Corresponding Author
Zhen-Song Chenzschen@whu.edu.cn
Received 11 September 2017, Accepted 30 October 2017, Available Online 1 January 2018.
DOI
10.2991/ijcis.11.1.20How to use a DOI?
Keywords
Fuzzy sets; hesitant fuzzy sets; proportional hesitant fuzzy sets; multi-attribute group decision making
Abstract

In this paper, we propose an extension of hesitant fuzzy sets, i.e., proportional hesitant fuzzy sets (PHFSs), with the purpose of accommodating proportional hesitant fuzzy environments. The components of PHFSs, which are referred to as proportional hesitant fuzzy elements (PHFEs), contain two aspects of information provided by a decision-making team: the possible membership degrees in the hesitant fuzzy elements and their associated proportions. Based on the PHFSs, we provide a novel approach to addressing fuzzy multi-attribute group decision making (MAGDM) problems. Different from the traditional approach, this paper first converts fuzzy MAGDM (expressed by classical fuzzy numbers) into proportional hesitant fuzzy multi-attribute decision making (represented by PHFEs), and then solves the latter through the proposal of a proportional hesitant fuzzy TOPSIS approach. In this process, preferences of the decision-making team are calculated as the proportions of the associated membership degrees. Finally, a numerical example and a comparison are provided to illustrate the reliability and effectiveness of the proposed approach.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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<Previous Article In Issue
Next Article In Issue>
Journal
International Journal of Computational Intelligence Systems
Volume-Issue
11 - 1
Pages
256 - 271
Publication Date
2018/01/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.11.1.20How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Sheng-Hua Xiong
AU  - Zhen-Song Chen
AU  - Kwai-Sang Chin
PY  - 2018
DA  - 2018/01/01
TI  - A Novel MAGDM Approach With Proportional Hesitant Fuzzy Sets
JO  - International Journal of Computational Intelligence Systems
SP  - 256
EP  - 271
VL  - 11
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.11.1.20
DO  - 10.2991/ijcis.11.1.20
ID  - Xiong2018
ER  -