Green supplier selection in straw biomass industry based on cloud model and possibility degree

2019 ◽  
Vol 209 ◽  
pp. 995-1005 ◽  
Author(s):  
Zhiming Lu ◽  
Xiaokun Sun ◽  
Yaxian Wang ◽  
Chuanbo Xu
Keyword(s):  
Supplier Selection ◽  
Cloud Model ◽  
Green Supplier Selection ◽  
Possibility Degree

scholarly journals A CLOUD TOPSIS MODEL FOR GREEN SUPPLIER SELECTION

2020 ◽  
Vol 18 (3) ◽  
pp. 375 ◽  
Author(s):  
Krishnapuram Ravi Ramakrishnan ◽  
Shankar Chakraborty
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Cloud Model ◽  
Evaluation Criteria ◽  
Human Cognition ◽  
Green Supplier Selection ◽  
Adopted Model ◽  
Qualitative Attribute ◽  
Green Suppliers ◽  
Topsis Model

Due to stringent governmental regulations and increasing consciousness of the customers, the present day manufacturing organizations are continuously striving to engage green suppliers in their supply chain management systems. Selection of the most efficient green supplier is now not only dependant on the conventional evaluation criteria but it also includes various other sustainable parameters. This selection process has already been identified as a typical multi-criteria group decision-making task involving subjective judgments of different participating experts. In this paper, a green supplier selection problem for an automobile industry is solved while integrating the Cloud model with the technique for order of preference by similarity to an ideal solution (TOPSIS). The adopted method is capable of dealing with both fuzziness and randomness present in the human cognition process while appraising performance of the alternative green suppliers with respect to various evaluation criteria. This model identifies green supplier S4 as the best choice. The derived ranking results using the adopted model closely match with those obtained from other variants of the TOPSIS method. The Cloud model can efficiently take into account both fuzziness and randomness in a qualitative attribute, and effectively reconstruct the qualitative attribute into the corresponding quantitative score for effective evaluation and appraisal of the considered green suppliers. Comparison of the derived ranking results with other MCDM techniques proves applicability, potentiality and solution accuracy of the Cloud TOPSIS model for the green supplier selection.

Integrated FAHP-VIKOR model for green supplier selection in a Nickle coating SME

2020 ◽  
pp. 133-139
Author(s):  
Sanatan Ratna ◽  
B Kumar
Keyword(s):  
Staff Training ◽  
Supplier Selection ◽  
Fuzzy Ahp ◽  
Research Work ◽  
Supplier Evaluation ◽  
Green Supplier Selection ◽  
The Past ◽  
Coating Industry ◽  
Sustainability Issue ◽  
Selection Of

In the past few decades, there has been lot of focus on the issue of sustainability. This has occurred due to the growing concerns related to climate change and the growing awareness about environmental concerns. Also, the competition at global level has led to the search for the most sustainable route in the industries. The current research work deals with the selection of green supplier in a Nickle coating industry based on certain weighted green attributes. For this purpose, a hybrid tool comprising of Fuzzy AHP (Fuzzy Analytical Hierarchy) and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) is used. The Fuzzy AHP is used for assigning proper weights to the selected criteria for supplier evaluation, while VIKOR is used for final supplier selection based on the weighted criteria. The three criterions for green supplier selection are, Ecological packaging, Corporate socio-environmental responsibility and Staff Training. The outcome of the integrated model may serve as a steppingstone to other SMEs in different sectors for selecting the most suitable supplier for addressing the sustainability issue.

Representing a probabilistic linguistic term set with an interval type-2 fuzzy set and the application in green supplier selection

2021 ◽  
pp. 1-18
Author(s):  
Le Jiang ◽  
Hongbin Liu
Keyword(s):  
Decision Making ◽  
Membership Function ◽  
Fuzzy Set ◽  
Supplier Selection ◽  
Symbolic Model ◽  
Green Supplier Selection ◽  
Linguistic Term ◽  
Interval Type ◽  
Decision Making Model

The use of probabilistic linguistic term sets (PLTSs) means the process of computing with words. The existing methods computing with PLTSs mainly use symbolic model. To provide a semantic model for computing with PLTSs, we propose to represent a PLTS by using an interval type-2 fuzzy set (IT2FS). The key step is to compute the footprint of uncertainty of the IT2FS. To this aim, the upper membership function is computed by aggregating the membership functions of the linguistic terms contained in the PLTS, and the lower membership function is obtained by moving the upper membership function downward with the step being total entropy of the PLTS. The comparison rules, some operations, and an aggregation operator for PLTSs are introduced. Based on the proposed method of computing with PLTSs, a multi-criteria group decision making model is introduced. The proposed decision making model is then applied in green supplier selection problem to show its feasibility.

CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection

2021 ◽  
pp. 1-11
Author(s):  
Huiyuan Zhang ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Comparison Method ◽  
Entropy Method ◽  
Decision Makers ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Psychological Perceptions

The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified.

scholarly journals Green supplier selection using fuzzy Delphi method for developing sustainable supply chain

2021 ◽  
pp. 63-70
Author(s):  
Nejah Ben Mabrouk
Keyword(s):  
Delphi Method ◽  
Supplier Selection ◽  
Expert Knowledge ◽  
Selection Process ◽  
Numerical Data ◽  
Future Research ◽  
Sustainable Supply Chain ◽  
Green Supplier Selection ◽  
Fuzzy Delphi ◽  
Green Packaging

The objective of this paper is to examine the determinants of the supplier selection process with green consideration. Thus, this analysis gathers a collection of factors from established literature of green supplier selection (GSS), including seven categories and 58 attributes. The objective of this research is to classify the key factors which are presented as qualitative information. Fuzzy logic rules are used to transform qualitative expert knowledge into numerical data. Then, we adopt the Delphi method (DM) to filter and rate unneeded factors according to their relevance. The results indicate 24 important factors for the GSS process. Five categories are included: Performance and technology ability, Environmental management, Pollution control, Quality and Service. The most significant factors are recognized as green research and development, eco-design, green image, green packaging and remanufacturing. Finally, the debate is held on the basis of the findings and future research are also recognized and stated.

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