Abstract
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.
Highlights
Introduction and Literature ReviewSeveral researchers have adopted the green supply chain management (GSCM) approach to greening their supply chains and are willing to learn more about the key performance measures that are accountable for their implementation
Decision makers provide a matrix of their ( p) own opinion D ( p) = (Bij )m×n, where Bij is given for the alternatives Ai ∈ A with respect to the criteria O j ∈ O by the K p decision maker in the form of q-rung orthopair fuzzy numbers (q-ROFNs)
We introduced a new approach for selecting green suppliers with the q-ROF information, in which the decision makers’
Summary
Several researchers have adopted the GSCM approach to greening their supply chains and are willing to learn more about the key performance measures that are accountable for their implementation. Government rules and regulations have been enacted to restrict the conduct of business; consumers can take into account the environmental impacts of different firms when making their choice [2]. More and more organizations are using the new GSCM environmental sustainability mode to reduce emissions during supply chain operations. GSCM covers many facets of the supply chain, such as product design, vendor selection, processing, storage, shipping, marketing, and recycling. The initial linkage of the supply chain and the impact on the productivity and environmental performance of the supply chain are between the different segments. Green construction, green production, green transport, and reverse logistics are the main pursuits involved in GSCM
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