Decision‐making in selecting reverse logistics alternative using interval‐valued fuzzy sets combined with VIKOR approach

Reverse logistics has become a strong strategic tool in today's turbulent marketplace. Recently many companies have been found adapting reverse logistics strategies in order to achieve competitive advantage in global business by solving environmental problems as well as by reducing production costs. The growing need for the proper implication of reverse logistics strategies in the contemporary company has now been well understood. However, the managerial‐decision regarding selection of an appropriate reverse manufacturing alternative has always been a key strategic consideration of any product recovery system. Such decision‐making problems are basically complicated, multidimensional, and unstructured due to uncertainty in environment and imprecise‐vague information regarding time, quantity and quality of returns, etc. Fuzzy decision‐modelling offers an alternative framework to deal with such kinds of reverse logistics system complicacies and to determine suitable decision strategies for best alternative selection for reprocessing. In this paper, an expert decision modelling tool which utilises concept of Interval‐Valued Fuzzy Sets (IVFS) in combination with VIKOR method has been developed and implemented in a real case study. The proposed model facilitates in designing effective product recovery policy depending on various criteria‐attributes.