Title
Green Supplier Selection With An Uncertain Probabilistic Linguistic Mabac Method
Abstract
In recent years, with the increased voice for protecting the environment by the people all over the world, the governments also have actively adopted more and more measures to further promote environmental conservation and sustainable development. Traditional procurement approaches have not well updated to the current needs of the society, especially for the retail industry which is in relation to the national economy due to numerous products and different suppliers being involved. Therefore, the need for green procurement is more important. The qualified green supplier selection is the core of green procurement, which is the utmost importance in the business competition throughout the supply chain in today's strong business competition. Thus, in order to obtain the optimal green supplier, integration of Entropy weights and multi-attributive border approximation area comparison (MABAC) under uncertain probabilistic linguistic sets (UPLTSs) has offered a novel integrated model, in which information Entropy is utilized for calculating objective weights with UPLTSs to acquire the final ranking result of green supplier. Besides, so as to indicate the applicability of devised method, it is confirmed by a numerical case for green supplier selection. Some comparative studies are made with some existing methods. The proposed method can also serve for selecting suitable alternative successfully in other selection problems.
Year
DOI
Venue
2020
10.3233/JIFS-191584
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
DocType
Volume
Multiple attribute group decision making (MAGDM), uncertain probabilistic linguistic term sets (UPLTSs), MABAC method, entropy method, green supplier selection
Journal
39
Issue
ISSN
Citations 
3
1064-1246
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Guiwu Wei13568107.94
Yan He200.68
Fan Lei312.71
Jiang Wu402.37
Cun Wei5510.52
Yanfeng Guo623.06