Novel Gained and Lost Dominance Score Method Based on Cumulative Prospect Theory for Group Decision-Making Problems in Probabilistic Hesitant Fuzzy Environment

The paper aims to present a new method to solve the multi-attribute group decision-making (MAGDM) problem under the probabilistic hesitant fuzzy environment. For this, we present the novel concept of gained and lost dominance score (GLDS) method based on cumulative prospect theory (CPT). The major advantage of the proposed GLDS method is that it concentrates on the loss aversion of the decision-makers (DMs), while we integrated the CPT to evaluate the risk aversion considering the DM’s rational behavior. Meanwhile, the weights among criterions are evaluated by using the process of analytic hierarchy process (AHP) method. The stated MAGDM algorithm has been implemented in a numerical example of sustainable supplier selection (SSS) for medical device manufacturing enterprises. SSS is an active development with the global advocacy of green economy and green supply chain and considered it as the typical MAGDM issue. The results have been compared with several of the existing approaches to validate its supremacy.