Assessment of Green Supplier Development Programs by a New Group Decision-Making Model Considering Possibilistic Statistical Uncertainty

Abstract

The assessment and selection of green supplier development programs are an intriguing and functional research subject. This paper proposes a group decision-making approach considering possibilistic statistical concepts under uncertainty to assess green supplier development programs (GSDPs) via interval-valued fuzzy sets (IVFSs). Possibility theory is employed to regard uncertainty by IVFSs. A new version of a technique for order preference by similarity to ideal solution (TOPSIS) is proposed to solve the decision problem. Possibilistic mean, standard deviation, and cube-root of skewness matrices are provided to consider relative closeness coefficients. In addition, a new version of an entropy method is introduced to obtain criteria weights under uncertainty. Finally, an illustrative example in an automobile manufacturing system is given to show the capability of the presented approach in addition to comparisons with recent fuzzy decision techniques for GSDPs.