Affiliations: [a] School of Management, Anhui Science and Technology University, Bengbu, China
| [b] School of Business, Nanjing Audit University, Nanjing, China
| [c] Business and Law School, Foshan University, Foshan, Guangdong, China
| [d] School of Business IT and Logistics, RMIT University, Melbourne VIC 3000, Australia
Abstract: With the changing business environment and the active participation of various stakeholders in the decision making process, it plays an increasingly important role to the weight of decision makers and the preference information given by decision makers. This paper presents a novel approach for group decision making under uncertainty with the involvement of the third-party evaluator in the decision making process. Recognizing the challenge in adequately determining the weight of decision makers in group decision making, the evidence theory is appropriately used with the involvement of the third-party evaluator. To effectively model the uncertainty and imprecision in the decision making process, fuzzy preference relations are used for better representing the subjective assessment of individual decision makers. To adequately determine the ranking of available alternatives, the logarithmic least square method is applied for appropriately aggregating the fuzzy preference relation of individual decision makers. A group consensus index is developed for facilitating consensus building in group decision making. This leads to better group decisions being made. A real-world application is presented that shows the proposed approach is effective in solving group decision making problems under uncertainty.
Keywords: Group decision making, uncertainty modeling, fuzzy numbers
