Model for Supplier Selection in Interval-Valued Intuitionistic Fuzzy Setting

2011 ◽  
Vol 6 (11) ◽  
pp. 12-16 ◽  
Author(s):  
Baofeng Li ◽  
Xiaoyun Yue ◽  
Guanchen Zhou
Keyword(s):  
Supplier Selection ◽  
Intuitionistic Fuzzy ◽  
Interval Valued ◽  
Fuzzy Setting

Interval-valued intuitionistic fuzzy multiple attribute decision making and their applications

2021 ◽  
Vol 25 (2) ◽  
pp. 251-277
Author(s):  
Hong-Jun Wang
Keyword(s):  
Supplier Selection ◽  
Fuzzy Numbers ◽  
Multiple Attribute Decision Making ◽  
Green Supply Chain Management ◽  
Green Supply Chain ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Operator Interval ◽  
Multiple Attribute ◽  
Interval Valued

In this paper, we expand the Muirhead mean (MM) operator and dual Muirhead mean (DMM) operator with interval-valued intuitionistic fuzzy numbers (IVIFNs) to propose the interval -valued intuitionistic fuzzy Muirhead mean (IVIFMM) operator, interval-valued intuitionistic fuzzy weighted Muirhead mean (IVIFWMM) operator, interval-valued intuitionistic fuzzy dual Muirhead mean (IVIFDMM) operator and interval-valued intuitionistic fuzzy weighted dual Muirhead mean (IVIFWDMM) operator. Then the MADM methods are proposed with these operators. In the end, we utilize an applicable example for green supplier selection in green supply chain management to prove the proposed methods.

scholarly journals A Scientific Decision Framework for Supplier Selection under Interval Valued Intuitionistic Fuzzy Environment

2017 ◽  
Vol 2017 ◽  
pp. 1-18 ◽  
Author(s):  
R. Krishankumar ◽  
K. S. Ravichandran ◽  
R. Ramprakash
Keyword(s):  
Supplier Selection ◽  
Second Phase ◽  
Decision Framework ◽  
Loss Of Information ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Criteria Weights ◽  
Two Phases ◽  
Scientific Decision ◽  
Interval Valued

This paper proposes a new scientific decision framework (SDF) under interval valued intuitionistic fuzzy (IVIF) environment for supplier selection (SS). The framework consists of two phases, where, in the first phase, criteria weights are estimated in a sensible manner using newly proposed IVIF based statistical variance (SV) method and, in the second phase, the suitable supplier is selected using ELECTRE (ELimination and Choice Expressing REality) ranking method under IVIF environment. This method involves three categories of outranking, namely, strong, moderate, and weak. Previous studies on ELECTRE ranking reveal that scholars have only used two categories of outranking, namely, strong and weak, in the formulation of IVIF based ELECTRE, which eventually aggravates fuzziness and vagueness in decision making process due to the potential loss of information. Motivated by this challenge, third outranking category, called moderate, is proposed, which considerably reduces the loss of information by improving checks to the concordance and discordance matrices. Thus, in this paper, IVIF-ELECTRE (IVIFE) method is presented and popular TOPSIS method is integrated with IVIFE for obtaining a linear ranking. Finally, the practicality of the proposed framework is demonstrated using SS example and the strength of proposed SDF is realized by comparing the framework with other similar methods.

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