Affiliations: [a] College of Computer and Information Engineering, Henan Normal University, Xinxiang, China
| [b] Engineering Lab of Henan Province for Intelligence Business and Internet of Things, Xinxiang, China
Abstract: Over the last decade, a lot of attentions have been drawn in the problem of multiple attribute decision-making associated with incomplete information tables. The filling missing value method and minimum decision cost are two important challenges for incomplete information tables. But most published studies focus on the optimization of data reckoning without considering the risk appetite of decision makers and decision-making environments. In this paper, considering the above factors, we presented an attribute weight determination method and an effective computing method for dealing with intuitionistic fuzzy incomplete information tables. Then, delay-refused decision in the boundary region and the risk assessment based on cross-entropy were proposed. Finally, a secondary decision strategy based on the probability entropy of delay-accepted decision and the application algorithms were given for improving the quality of decisions.
