Green supplier selection by developing a new group decision-making method under type 2 fuzzy uncertainty

Abstract

One of the most important issues in green supply chain management is supplier selection. This issue has proven to be one of the most important decision-making processes for production, operations, and purchasing managers. This problem has to be dealt with in both industry and service environments and is essential to help the firms keep their competitive edge over their rivals. However, this vital process has imprecision and ambiguity. It enhances the difficulty of this important decision-making task. Dealing with uncertainty requires appropriate tools and techniques. In this paper, a new method of supplier selection is presented that uses interval type 2 fuzzy sets (IT2FSs) to deal with today’s uncertain environment. To show the importance and the level of knowledge of each decision-maker in the process, the model applies a novel approach that gives the decision-makers a new weight based on their level of knowledge and the gathered judgments. Moreover, the concept of relative preference relation of IT2FSs is developed to address the weight of selection criteria. Eventually, the proposed uncertain supplier selection model develops the concept of multi-objective optimization by ratio analysis plus the full multiplicative form under type 2 fuzzy uncertainty to enhance the capability of the proposed model to function under real-world problems. Finally, to illustrate the capabilities of the introduced approach, first, two existing case studies at the manufacturing system level are taken from the literature and are solved. Then, to present the method in a step-by-step approach, a case study is adopted and solved by the proposed model and the results are presented.