An Interval Valued Neutrosophic Decision-Making Structure for Sustainable Supplier Selection

2021 ◽  
pp. 115354
Author(s):  
Morteza Yazdani ◽  
Ali Ebadi Torkayesh ◽  
Željko Stević ◽  
Prasenjit Chatterjee ◽  
Sahand Asgharieh Ahari ◽  
...  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chang Liu ◽  
Pratibha Rani ◽  
Khushboo Pachori

PurposeDue to stern management policies and increased community attentiveness, sustainable supply chain management (SSCM) performs a vast component in endeavor operation and production management. Sustainable circular supplier selection (SCSS) and evaluation presented the environmental and social concerns in the fields of circular economy and sustainable supplier selection. Choosing the optimal SCSS is vital for organizations to persuade SSCM, as specified in various researches. Based on the subjectivity of human behavior, the selection of ideal SCSS often involves uncertain information, and the Pythagorean fuzzy sets (PFSs) have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the multi-criteria decision-making (MCDM) procedure. Here, a framework is developed to assess and establish suitable suppliers in the SSCM and the circular economy.Design/methodology/approachThis paper introduced an extended framework using the evaluation based on distance from average solution (EDAS) with PFSs and implemented it to solve the SCSS in the manufacturing sector. Firstly, the PFSs to handle the uncertain information of decision experts (DEs) is employed. Secondly, a novel divergence measure and parametric score function for calculating the criteria weights are proposed. Thirdly, an extended decision-making approach, known as PF-EDAS, is introduced.FindingsThe outcomes and comparative discussion show that the developed method is efficient and capable of facilitating the DEs to choose desirable SCSS. Therefore, the proposed framework can be used by organizations to assess and establish suitable suppliers in the SCSS process in the circular economy.Originality/valueSelecting the optimal sustainable circular supplier (SCS) in the manufacturing sector is important for organizations to persuade SSCM, as specified in various research. However, corresponding to the subjectivity of human behavior, the selection of the best SCS often involves uncertain information, and the PFSs have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the MCDM procedure. Hence, manufacturing companies' administrators can implement the developed method to assess and establish suitable suppliers in the SCSS process in the circular economy.


2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Muhammad Naeem ◽  
Muhammad Qiyas ◽  
Saleem Abdullah

With respect to multiple criteria group decision-making (MCGDM) problems in which both the criteria weights and the expert weights take the form of crisp numbers and attribute values take the form of interval-valued picture fuzzy uncertain linguistic numbers, some new group decision-making analysis methods are developed. Firstly, some operational laws, expected value, and accuracy function of interval-valued picture fuzzy uncertain linguistic numbers are introduced. Then, an interval-valued picture fuzzy uncertain linguistic averaging and geometric aggregation operators are developed. Furthermore, some desirable properties of the developed operators, such as commutativity, idempotency, and monotonicity, have been studied. Based on these operators, an approach to multiple criteria group decision-making with interval-valued picture fuzzy uncertain linguistic information has been proposed. Finally, a practical example of 3PL supplier selection in logistics service value concretion is taken to test the defined method and to expose the effectiveness of the defined model.


2019 ◽  
Vol 11 (10) ◽  
pp. 2820 ◽  
Author(s):  
Xiaodong Wang ◽  
Jianfeng Cai ◽  
Jichang Xiao

Sustainable supplier selection has become a strategic activity to enhance the competitiveness of sustainable supply chain management. Research on sustainable supplier selection is considering increasingly more practical factors, such as the uncertainty of decision context and the fuzzy recognition of experts. Evaluation values on different criteria with different characteristic should be represented in their suitable information types to reflect the characteristic accurately and represent experts’ judgments entirely. Moreover, it is difficult, or costly, to build a decision criteria set in which all criteria are independent to each other because of the interaction of technical, economic, environmental and social factors. Therefore, the aim of this paper is to propose a novel decision-making framework for sustainable supplier selection which considers the interaction among criteria with heterogeneous decision information. The proposed framework can not only allow the experts to express their judgments completely, but also improve the efficiency of decision-making. First, a normalized dominance decision matrix based on normalized closeness is built with the heterogeneous decision matrix. Then, a defined discrete Choquet integral multi-criteria distance measure is used to compute the comprehensive associated closeness and rank the alternative sustainable suppliers. This framework provides a new way to handle the interaction among criteria for sustainable supplier selection from the perspective of multi-criteria distance measure, and a novel methodology to solve the problems that the evaluation values cannot be aggregated directly. Finally, an example is given to illustrate the proposed framework for sustainable supplier selection with a comparison analysis.


Sign in / Sign up

Export Citation Format

Share Document