Multi-Attributive Decision-Making Method Of Interval-Valued Intuitionistic Fuzzy Numbers Under Incomplete Information Circumstance

In the case where the interval-valued intuitionistic fuzzy numbers serve as the solution property values, and the attribute weight information is incomplete, this paper proposed a decision-making analysis method of interval-valued intuitionistic fuzzy numbers. To comprehensively consider the circumstance of incomplete weight information of each evaluation index, by regarding the positive and negative ideal solution of each index as reference point, the index weight can be obtained by projection-based multi-objective programming model, and the evaluation information can be gathered using weighted arithmetic averaging operator. Subsequently, combining the Euclidean distance of interval-valued intuitionistic fuzzy numbers (IVIFN), it provided the relative closeness degree formula of IVIFN to the max IVIFN, so as to determine the closeness degree and obtain the sorting and selection result of each scheme. Finally, the feasibility and effectiveness of the proposed method were verified based on analysis of examples.