Waste Reduction and Recycling: Schweizer-Sklar Aggregation Operators Based on Neutrosophic Fuzzy Rough Sets and Their Application in Green Supply Chain Management

Abstract

Green supply chain management (GSCM) is a valuable application that is used to reduce the overall environmental impact of the supply chain. Waste reduction and recycling are crucial components of sustainable technique that aims to reduce ecological impact and encourage reserve effectiveness. In this manuscript, we initiate the technique of Schweizer-Sklar (SS) operational laws based on neutrosophic fuzzy rough (NFR) values for SS t-norm (SSTN) and SS t-conorm (SSTCN). Further, we derive the NFR SS weighted averaging (NFRSSWA) operator and the NFR SS weighted geometric (NFRSSWG) operator. Some basic properties for the above-initiated techniques are derived. Additionally, we describe the application in green supply chain management, called waste reeducation and recycling based on initiated operators in multi-attribute decision-making (MADM) problems. Finally, we illustrate an example for comparing the ranking values of the proposed techniques with the ranking values of the existing technique to enhance the worth of the derived theory.