Multi-attributive Decision-making Method of Interval-valued Intuitionistic Fuzzy Numbers under Incomplete Information Circumstance

Sha Fu, Yezhi Xiao

Abstract



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.

Keywords


Multi-attributive Decision-making, Incomplete Information, Interval-valued Intuitionistic Fuzzy Numbers, Projection, Relative Closeness Degree.



Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.