Schweizer-Sklar power aggregation operators and EDAS model for circular interval-valued (p, q)-rung orthopair fuzzy sets & its application to green supply chain management

Abstract

Lifecycle Assessment is an automatic and systematic technique used to address or ensure the ecological or green impacts linked with many of the phases of a product's life from raw substantial removal to recycling or disposal. In green supply chain management, lifecycle assessment plays a critical role in reducing, quantifying, and identifying environmental burdens throughout the supply chain. In this manuscript, we aim to assess the major role of the lifecycle assessment in green supply chain management; for this, we focus on the evaluation of the novel technique of circular interval-valued (p, q)-rung orthopair fuzzy information and develop or construct their important and basic operational laws for algebraic norms as well as for Schweizer-Sklar norms. Further, we presented some weighted averaging and geometric operators for both norms and hence discuss their fundamental properties. Later, we presented decision-making techniques named as “Evaluation based on Distance from the Average Solution” technique for solving the multi-attribute decision-making problems using the proposed operators. Finally, we clarify some numerical examples for the evaluation of the comparative analysis among the proposed ranking model with the ranking theory of prevailing information to describe the efficiency and rationality of the derived approaches.