The Use of Fuzzy Methods in Large-Scale Group Decision Making Problems: A Literature Review

Abstract

Group Decision Making (GDM) methods involve a group of decision-makers or stakeholders collaboratively evaluating several alternatives to determine the most appropriate option for increasingly complex decision-making problems in daily life. The development of technology, the increase in alternative options, the difficulties encountered in the decision-making process, the rise in the number of decision-makers, and the emergence of disagreements have made Large-Scale Group Decision Making (LSDM) methods a focus for researchers. Although Large-Scale Group Decision Making (LSDM) methods help manage more complex decision environments involving more decision makers and resolve significant disagreements, conflicts of opinion among decision-makers are inevitable in studies conducted with LSGDM methods, researchers focused on determining the decision maker weights that include uncertainties, determining the number of clusters, determining the trust relationships between decision makers, determining the degree of cooperation of decision makers, determining the weights of subgroups and ensuring consensus. In many applications, fuzzy logic-based methods are a powerful alternative for modeling uncertainty and subjective judgments. This study systematically examined LSGDM methods used by researchers to solve the problems they focused on in their studies in the last 10 years and the fuzzy sets they used to eliminate uncertainties. The findings show that fuzzy approaches offer significant advantages in managing uncertainty in LSGDM processes, improving decision quality, and ensuring participant satisfaction. Furthermore, the current gaps in literature and future research orientations were also discussed.