scholarly journals Green Supplier Selection Based on DEA Model in Interval-Valued Pythagorean Fuzzy Environment

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 108001-108013 ◽  
Author(s):  
Mei-Qin Wu ◽  
Can-Hui Zhang ◽  
Xiao-Na Liu ◽  
Jian-Ping Fan
Keyword(s):  
Supplier Selection ◽  
Dea Model ◽  
Green Supplier Selection ◽  
Fuzzy Environment ◽  
Interval Valued

scholarly journals Large-Scale Green Supplier Selection Approach under a Q-Rung Interval-Valued Orthopair Fuzzy Environment

Processes ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 573 ◽  
Author(s):  
Liu ◽  
Cao ◽  
Shi ◽  
Tang
Keyword(s):  
Supplier Selection ◽  
Large Scale ◽  
Similarity Measures ◽  
Decision Makers ◽  
Entropy Measure ◽  
Green Supplier Selection ◽  
Fuzzy Environment ◽  
Fuzzy Aggregation ◽  
Interval Valued ◽  
Evaluation Information

As enterprises pay more and more attention to environmental issues, the green supply chain management (GSCM) mode has been extensively utilized to guarantee profit and sustainable development. Green supplier selection (GSS), which is a key segment of GSCM, has been investigated to put forward plenty of GSS approaches. At present, enterprises prefer to construct the large-scale teams of decision makers to obtain the more reasonable ranking results during GSS process. However, the existing methods pay little attention to the large-scale GSS procedure. To investigate the GSS issue with a large-scale group of decision makers, a new GSS approach under a q-rung interval-valued orthopair fuzzy environment is developed. The q-rung interval-valued orthopair fuzzy numbers are introduced to describe the evaluation information of green suppliers. Combined with a clustering approach and several clustering principles, the large-scale decision makers are divided into several subgroups. Next, the similarity measures between the evaluation matrices are computed to determine the weights of subgroups, and the collective evaluation information can be obtained using the q-rung interval-valued orthopair fuzzy aggregation operator. According to the weighted entropy measure, the weights of criteria are calculated; then, the q-rung interval-valued orthopair fuzzy multi-objective optimization on the basis of ratio analysis plus the full multiplicative form (q-RIVOF-MULTIMOORA) method is constructed to determine the best green supplier. At last, a practical GSS example is applied to show the feasibility of the proposed approach, and the sensitivity and comparative analyses indicate that for the large-scale GSS issues, the proposed approach can obtain the more robust and reasonable ranking results.

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.

Sign in / Sign up

Export Citation Format

Share Document