scholarly journals Green Supplier Selection Under Cloud Manufacturing Environment: A Hybrid MCDM Model

SAGE Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 215824402110571
Author(s):  
Dan-Ping Li ◽  
Li Xie ◽  
Peng-Fei Cheng ◽  
Xiang-Hong Zhou ◽  
Cheng-Xun Fu
Keyword(s):  
Supplier Selection ◽  
Risk Attitude ◽  
Cloud Manufacturing ◽  
Selection Model ◽  
Assessment Process ◽  
Manufacturing Environment ◽  
Green Supplier Selection ◽  
Todim Method ◽  
Manufacturing Platform ◽  
Evaluation Information

In the cloud manufacturing environment, the interaction and cooperation between enterprises become more convenient. The most optimal green supplier selection through cloud manufacturing platform can improve the production quality and sustainable development efficiency of enterprises. However, as alternative suppliers are all over the world, there is a risk that the selected supplier is not ideal. Therefore, in this paper, a hybrid supplier selection model based on TODIM method is proposed to choose the optimal green supplier under cloud manufacturing platform. Considering the characteristics of suppliers in the cloud manufacturing environment and green criteria, the comprehensive green supplier evaluation index system is constructed. The creative application of heterogeneous evaluation information including crisp numbers, interval numbers, and probabilistic linguistic values, can express the evaluation information of different subjects comprehensively. In order to consider human judgment and the importance of information provided by raw data, the criteria weights are determined by integrating fuzzy BWM (Best-worst method) weights and objective entropy weights. Then, with the full consideration of decision maker’s risk attitude, the TODIM method is used to process heterogeneous evaluation information and calculate the priority of the green suppliers. The proposed method is novel, and allows multi-subjects to participate in the assessment process and considers the risk attitude of decision-makers in the green supplier selection process. An empirical study of green supplier selection in the cloud manufacturing environment is conducted. Sensitivity analysis and comparative analysis indicate that the proposed selection model for green supplier is reliable and effective.

A green supplier selection model for high-tech industry

2009 ◽  
Vol 36 (4) ◽  
pp. 7917-7927 ◽  
Author(s):  
Amy H.I. Lee ◽  
He-Yau Kang ◽  
Chang-Fu Hsu ◽  
Hsiao-Chu Hung
Keyword(s):  
Supplier Selection ◽  
Selection Model ◽  
High Tech ◽  
High Tech Industry ◽  
Green Supplier Selection

scholarly journals A Novel Approach for Green Supplier Selection under a q-Rung Orthopair Fuzzy Environment

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 687 ◽  
Author(s):  
Rui Wang ◽  
Yanlai Li
Keyword(s):  
Supplier Selection ◽  
Weighted Average ◽  
Economic Benefits ◽  
Decision Makers ◽  
Weighting Method ◽  
Green Supplier Selection ◽  
Fuzzy Environment ◽  
Novel Approach ◽  
Evaluation Matrix ◽  
Evaluation Information

With environmental issues becoming increasingly important worldwide, plenty of enterprises have applied the green supply chain management (GSCM) mode to achieve economic benefits while ensuring environmental sustainable development. As an important part of GSCM, green supplier selection has been researched in many literatures, which is regarded as a multiple criteria group decision making (MCGDM) problem. However, these existing approaches present several shortcomings, including determining the weights of decision makers subjectively, ignoring the consensus level of decision makers, and that the complexity and uncertainty of evaluation information cannot be adequately expressed. To overcome these drawbacks, a new method for green supplier selection based on the q-rung orthopair fuzzy set is proposed, in which the evaluation information of decision makers is represented by the q-rung orthopair fuzzy numbers. Combined with an iteration-based consensus model and the q-rung orthopair fuzzy power weighted average (q-ROFPWA) operator, an evaluation matrix that is accepted by decision makers or an enterprise is obtained. Then, a comprehensive weighting method can be developed to compute the weights of criteria, which is composed of the subjective weighting method and a deviation maximization model. Finally, the TODIM (TOmada de Decisao Interativa e Multicritevio) method, based on the prospect theory, can be extended into the q-rung orthopair fuzzy environment to obtain the ranking result. A numerical example of green supplier selection in an electric automobile company was implemented to illustrate the practicability and advantages of the proposed approach.

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 Green Supplier Selection With a Continuous Interval-Valued Linguistic TODIM Method

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 124315-124328 ◽  
Author(s):  
Song Nie ◽  
Huchang Liao ◽  
Xingli Wu ◽  
Zeshui Xu
Keyword(s):  
Supplier Selection ◽  
Green Supplier Selection ◽  
Todim Method ◽  
Interval Valued
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