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.

Green supplier selection in steel industry with intuitionistic fuzzy Taxonomy method

2020 ◽  
Vol 39 (5) ◽  
pp. 7247-7258
Author(s):  
Lu Xiao ◽  
Siqi Zhang ◽  
Guiwu Wei ◽  
Jiang Wu ◽  
Cun Wei ◽  
...  
Keyword(s):  
Steel Industry ◽  
Supplier Selection ◽  
Correlation Method ◽  
Green Supply Chain ◽  
Weighting Method ◽  
Green Supplier Selection ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Multiple Attribute ◽  
Criteria Importance

Since people around the world have gradually attached importance to resource conservation, various countries are actively taking measures to promote environmental protection and sustainable development. Green supply chain management (GSCM) have emerged in this context. Thus, in this essay, a novel intuitionistic fuzzy multiple attribute group decision making (MAGDM) method is designed to tackle this issue. First of all, CRITIC (Criteria Importance Through Inter-criteria Correlation) method is utilized to determine the weights of criteria. Later, the conventional Taxonomy method is extended to the intuitionistic fuzzy environment to compute the value of development attribute of each supplier. Then, the optimal one can be determined. Eventually, an application about green supplier selection in steel industry is presented, and a comparative analysis is made to demonstrate the superiority of the proposed method. The main features of the proposed algorithm are that they provide a practical solution for selecting GSCM and presents an objective weighting method to enhance the effectiveness of the algorithm.

scholarly journals A Multi-Criteria Group Decision Making Model for Green Supplier Selection under the Ordered Weighted Hesitant Fuzzy Environment

Symmetry ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 17 ◽  
Author(s):  
Yumin Liu ◽  
Linlin Jin ◽  
Feng Zhu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Weighted Average ◽  
Hesitant Fuzzy Set ◽  
Average Operator ◽  
Green Supplier Selection ◽  
Fuzzy Environment ◽  
Decision Making Model

The green supplier selection (GSS) problem is one of the most pressing issues that can directly affect manufacturer performance. GSS has been studied in previous literature, which is considered to be a typical multiple criteria group decision making (MCGDM) problemThe ordered weighted hesitant fuzzy MCGDM method can present the importance of each possible value, and the priority relationship among criteria has rarely been studied. In this study, we first extend the prioritized average (PA) operator to the ordered weighted hesitant fuzzy set (OWHFS) for solving the both problems. The generalized ordered weighted hesitant fuzzy prioritized weighted average operator (GOWHFPWA) is recommended, and some desirable properties are discussed. Based on this operator, a novel MCGDM method for GSS is developed. A numerical example of GSS is then given to prove the robustness of the proposed approach, and a sensitivity analysis is used to identify the robustness of the proposed method. Finally, a comparative analysis based on the MCGDM approach with the hesitant fuzzy prioritized weighted average (HFPWA) operator is illustrated to indicate the validity and advantages of the proposed approach.

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 q-Rung Orthopair Fuzzy Prioritized Aggregation Operators and Their Application Towards Green Supplier Chain Management

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 976
Author(s):  
Muhammad Riaz ◽  
Dragan Pamucar ◽  
Hafiz Muhammad Athar Farid ◽  
Masooma Raza Hashmi
Keyword(s):  
Supplier Selection ◽  
Weighted Average ◽  
Sustainable Growth ◽  
Fuzzy Information ◽  
Chain Management ◽  
Green Supplier Selection ◽  
Scientific Decision ◽  
Green Suppliers ◽  
Prioritized Aggregation Operators ◽  
Relationship Of

Supply management and environmental concerns are becoming increasingly relevant to scientific decision analysis around the world. Several companies have implemented the green supply chain management (GSCM) approach for attaining economic advantages while retaining sustainable growth for the environment. Green supplier selection has also been analyzed in many literary works as an important part of GSCM, which is considered an important multi-criteria group decision making (MCGDM) problem. The lack of consideration of the relationships of alternatives to the uncertain environment will be the main reason for weak conclusions in some MCGDM problems. To address these drawbacks, we introduce a new approach for selecting green suppliers with the q-rung orthopair fuzzy information, in which the input assessment is considered by using q-rung orthopair fuzzy numbers (q-ROFNs). A q-ROFN is extremely valuable in representing vague information that occurs in these real-world circumstances. The priority relationship of the alternatives to q-rung orthopair fuzzy information is very helpful to deal with GSCM. Consequently, we develop some prioritized operators with q-ROFNs named the q-rung orthopair fuzzy prioritized weighted average (q-ROFPWA) operator and q-rung orthopair fuzzy prioritized weighted geometric (q-ROFPWG) operator. Several important characteristics of these operators such as idempotents, boundary, and monotonicity are also well proven. Finally, an application of the proposed operators is presented for green supplier selection in GSCM. The scientific nature of the proposed methodology is illustrated by a numerical example to validate its rationality, symmetry, and superiority.

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

A GMCDM approach with linguistic Z-numbers based on TOPSIS and Choquet integral considering risk preference

2020 ◽  
Vol 39 (3) ◽  
pp. 4285-4298
Author(s):  
Ran Tao ◽  
Fuyuan Xiao
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Choquet Integral ◽  
Risk Preference ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Uncertain Information ◽  
Human Knowledge ◽  
Mcdm Method ◽  
Evaluation Information

Group multi-criteria decision-making (GMCDM) is an important part of decision theory, which is aimed to assess alternatives according to multiple criteria by collecting the wisdom of experts. However, in the process of evaluating, because of the limitation of human knowledge and the complexity of problems, an efficient GMCDM approach under uncertain environment still need to be further explored. Thus, in this paper, a novel GMCDM approach with linguistic Z-numbers based on TOPSIS and Choquet integral is proposed. Firstly, since linguistic Z-numbers performs better in coping with uncertain information, it is used to express the evaluation information. Secondly, TOPSIS, one of the most useful and systematic multi-criteria decision-making (MCDM) method, is adopted as the framework of the proposed approach. Thirdly, frequently it exists interaction between criteria, so Choquet integral is introduced to capture this kind of influence. What’s more, viewing that decision makers (DMs) show different preferences for uncertainty, the risk preference is regarded as a vital parameter when calculating the score of linguistic Z-numbers. An application in supplier selection is illustrated to demonstrate the effectiveness of the proposed approach. Finally, a further comparison and discussion of the proposed GMCDM method is given.

Using Data Envelopment Analysis for Green Supplier Selection in Manufacturing under Vague Environment

2012 ◽  
Vol 622-623 ◽  
pp. 1682-1685 ◽  
Author(s):  
Atefeh Amindoust ◽  
Ahmed Shamsuddin ◽  
Ali Saghafinia
Keyword(s):  
Data Envelopment Analysis ◽  
Supplier Selection ◽  
Decision Makers ◽  
Central Component ◽  
Data Envelopment ◽  
Linguistic Terms ◽  
Green Supplier Selection ◽  
Growth Of Knowledge ◽  
Using Data

In these days, considering the growth of knowledge about environmental protection and green issues in manufacturing, green supplier selection would be the central component in the management of supply chain. This paper intends to apply data envelopment analysis for supplier selection considering environmental merits. The suppliers’ performances with respect to criteria are not pure numbers and considered in linguistic terms according to decision makers’ opinion. To handle the subjectivity of decision makers’ assessments, fuzzy logic has been applied. A case study is done to present the application of the method.

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