Utilization of Intuitive Fuzzy WASPAS Method with Interval Values to Evaluation of Reverse Logistics Implementation Actions in the LARG Supply Chain

Abstract

Attention to environmental issues has led to the application of reverse logistics in the supply chain. But, the implementation of reverse logistics is weak because of the type of inventory management models. Therefore, in this research, to improve supply chain performance was used lean, agile, resilient, and green (LARG) paradigms. The purpose of this research is to identify and prioritize the solutions of reverse logistics implementation in the LARG supply chain to improve supply chain performance. In this research, the Interval-valued Intuitionistic Fuzzy expert-driven approach was used. Interval-valued Intuitionistic Fuzzy sets were used for weighting the evaluation criteria, and the Interval-valued Intuitionistic Fuzzy WASPAS method was used to prioritize solutions. The findings indicated that the first solution (creation, development, and investment in reverse logistics technology), the Tenth solution (development of the closed-loop supply chain through integration with reverse logistics), and the ninth solution (building electronic collaboration for rapid and effective coordination in among the members of the supply chain), respectively, were introduced as the best solutions in this study. The development and investment in reverse logistics technologies, electronic integration, and collaboration, and improved coordination are essential to improve the performance of reverse logistics implementation in the supply chain.