Open AccessDynamic multi-attribute decision making model based on triangular intuitionistic fuzzy numbers
Author(s) -
Yanlai Chen,
Bing Li
Publication year - 2011
Publication title -
scientia iranica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.299
H-Index - 51
eISSN - 2345-3605
pISSN - 1026-3098
DOI - 10.1016/j.scient.2011.03.022
Subject(s) - operator (biology) , aggregate (composite) , entropy (arrow of time) , measure (data warehouse) , mathematics , fuzzy number , basis (linear algebra) , group decision making , computer science , attribute domain , data mining , fuzzy logic , mathematical optimization , fuzzy set , artificial intelligence , rough set , geometry , physics , gene , materials science , repressor , chemistry , composite material , biochemistry , quantum mechanics , transcription factor , law , political science
Triangular Intuitionistic Fuzzy Numbers (TIFNs) express more abundant and flexible information than Triangular Fuzzy Numbers (TFNs). The main purpose of this paper is to propose a Dynamic Multi-Attribute Decision Making (DMADM) model on the basis of TIFNs, to solve the DMADM problem, where all the decision information takes the form of TIFNs. A new distance measure between two TIFNs is developed to aid in determining attribute weights, using the entropy method. An aggregation operator, the weighted arithmetic averaging operator on TIFNs (TIFN-WAA), is presented to aggregate the decision information with TIFNs. Finally, the effectiveness and applicability of the proposed DMADM model, as well as analysis of comparison with another model, are illustrated with an investment example