Research Of Interactive Group Decision Making Method Based On Linguistic Assessment Information

As one important field in decision making science, research in group decision making theory and method increasingly attracted attention of scholars. After nearly 50 years, research in group decision-making has made considerable achievements. At present, facing the highly complex decision making problem and process, scientific and rational decision-making process relates to effectiveness of the final result. However, the current research in group decision making process is still relatively small. Therefore, it provides a broad space for the researchers.In this dissertation, based on the analysis of existing literature and theoretical productions, starting from researching group decision-making process, this dissertation makes such attempts:(1) Analyzing of existing research literature in group decision making, it is found that the research literature of group decision-making process is very thin. In particularly, many of researchers ignore interactive process among experts and dealing for it, so that it makes a lot of information loss easily. In this dissertation, for the information interactive progress, it imposes the interactive idea on the research of group decision-making, and proposes phased feedback interactive group decision-making model. This model captures information in interactive progress, corrects and optimizes decision information constantly in decision-making process, so that it can gain the result, fully reflecting group intelligence , and enhance the rationality of group decision-making.(2)On the basis of phased feedback interactive group decision making model, this dissertation utilizes linguistic assessment information to express experts, preference information, so that decision-makers could give their preference information conveniently, and reduce information loss as soon as possible from star. Through such characteristic: formalization, convenience, visualization, matching, approximation process and information loss, this dissertation analyses and chooses 2-Tuple model to process linguistic assessment information, and reduce information deviation.