Fusion of probabilistic linguistic term sets for enhanced group decision-making: Foundations, survey and challenges

Abstract

Probabilistic linguistic term set (PLTS) provides a flexible and comprehensive approach to reflecting qualitative information about decision makers (DMs) by fusing linguistic terms and probability distributions. This fusion makes PLTS an important focus of fuzzy decision theory. Dealing with uncertainty and ambiguity has always been a major challenge in the group decision-making (GDM) process, and PLTS provides a versatile and effective approach to address these issues. PLTS is able to more accurately represent the preferences and opinions of the DMs, thus improving the accuracy and consistency of decision-making, thereby improving the accuracy and consistency of decision-making. Therefore, the application of PLTSs in GDM (PLTS-GDM) has attracted more and more attention and shown great potential. In this paper, we provide a comprehensive overview of the underlying theories of PLTS-GDM, the existing approaches and the challenges they face. Specifically, we explore how the PLTS utilizes fuzzy information systems to manage imprecise and ambiguous data to enhance the effectiveness of decision-making. In addition, through an extensive review and analysis of the current literature, we summarize the major advances in the field and identify important gaps in the existing research. Finally, we point out future research directions aimed at addressing these challenges and further advancing the application and development of PLTS-GDM. In summary, this paper provides a valuable resource for scholars and practitioners to help them understand and promote the practical applications of PLTS-GDM.