International Journal of Computational Intelligence Systems

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Volume 12, Issue 2, 2019, Pages 1361 - 1370

EDAS Method for Multiple Attribute Group Decision Making with Probabilistic Uncertain Linguistic Information and Its Application to Green Supplier Selection

Authors
Yan He1, Fan Lei1, Guiwu Wei2, *, Rui Wang2, Jiang Wu3, Cun Wei3
1School of Mathematical Sciences, Sichuan Normal University, Chengdu, 610101, P.R. China
2School of Business, Sichuan Normal University, Chengdu, 610101, P.R. China
3School of Statistics, Southwestern University of Finance and Economics, Chengdu, 611130, P.R. China
*Corresponding author. Email: weiguiwu@163.com
Corresponding Author
Guiwu Wei
Received 28 September 2019, Accepted 18 October 2019, Available Online 14 November 2019.
DOI
10.2991/ijcis.d.191028.001How to use a DOI?
Keywords
Multiple attribute group decision making (MAGDM); Probabilistic uncertain linguistic term sets (PULTSs); Information entropy; EDAS method; Green supplier selection
Abstract

In order to adapt to the development of the new times, enterprises should not only care for the economic benefits, but also properly cope with environmental and social problems to achieve the integration of environmental, economic and social performance of sustainable development, so as to maximize the efficiency of resource use and minimize the negative effects of environmental pollution. Hence, in order to select a proper green supplier, integration of the information entropy and Evaluation based on Distance from Average Solution (EDAS) under probabilistic uncertain linguistic sets (PULTSs) offered a novel integrated model, in which information entropy is used for deriving priority weights of each attribute and EDAS with PULTSs is employed to obtain the final ranking of green supplier. Furthermore, in order to show the applicability of the proposed method, it is validated by a case study for green supplier selection along with some comparative analysis. Thus, the advantage of this proposed method is that it is simple to understand and easy to compute. The proposed method can also contribute to the selection of suitable alternative successfully in other selection issues.

Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
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/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
12 - 2
Pages
1361 - 1370
Publication Date
2019/11/14
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.191028.001How to use a DOI?
Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
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

risenwbib
TY  - JOUR
AU  - Yan He
AU  - Fan Lei
AU  - Guiwu Wei
AU  - Rui Wang
AU  - Jiang Wu
AU  - Cun Wei
PY  - 2019
DA  - 2019/11/14
TI  - EDAS Method for Multiple Attribute Group Decision Making with Probabilistic Uncertain Linguistic Information and Its Application to Green Supplier Selection
JO  - International Journal of Computational Intelligence Systems
SP  - 1361
EP  - 1370
VL  - 12
IS  - 2
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.191028.001
DO  - 10.2991/ijcis.d.191028.001
ID  - He2019
ER  -