A group consensus model with prospect theory under probabilistic linguistic term sets

The challenges encountered in the realm of multi-attribute group decision-making (MAGDM) involving probabilistic linguistic term sets (PLTSs) have garnered substantial attention. Within the PLTS context, this study introduces a consensus reaching process (CRP) that iteratively refines the weights assigned to decision-makers (DMs) by leveraging the principles of prospect theory (PT). The primary goal of this iterative weight adjustment process is to enhance the overall decision-making procedure when dealing with PLTSs. To circumvent any data loss during transformation and compute the prospect values of PLTSs directly, a novel transformation formula is developed. Acknowledging the distinct cognitive levels among different DMs, the integration of multiple weights into the consensus process is characterized by its dynamic and iterative nature. Concerning the measurement of consensus, this study employs a method based on the gap between prospect values, which enhances objectivity while overcoming the limitations associated with the distance formula of PLTSs. Furthermore, the feedback mechanism incorporated into the modification process incorporates dynamic adjustment parameters that are tailored to different evaluation values, thereby preventing excessive adjustments that are either too low or too high. By utilizing the newly proposed prospect value function, this research aggregates the group evaluation value and identifies the optimal alternative. In conclusion, this paper concludes with a comparative analysis involving various counterparts, shedding light on the feasibility and validity of the proposed model.