Some Generalized Complex Intuitionistic Fuzzy Aggregation Operators and Their Application to Multicriteria Decision-Making Process

• Published in: Arabian journal for science and engineering (2011) Vol. 44; no. 3; pp. 2679 - 2698
• Main Authors: Garg, Harish, Rani, Dimple
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 11.03.2019; Springer Nature B.V
• Subjects: Agglomeration; Decision making; Decision support systems; Engineering; Fuzzy sets; Handles; Humanities and Social Sciences; multidisciplinary; Multiple criterion; Operators; Real numbers; Research Article - Systems Engineering; Science; Uncertainty; Complex intuitionistic fuzzy set; Averaging operators; Multicriteria decision-making; Complex fuzzy set; t-norm operations
• ISSN: 2193-567X; 1319-8025; 2191-4281
• DOI: 10.1007/s13369-018-3413-x

The objective of this manuscript is to present some generalized weighted averaging aggregation operators for aggregating the different complex intuitionistic fuzzy sets using t-norm operations. In the existing studies of fuzzy and its extension, the uncertainties present in the data are handled with the help of degrees of membership which are the subset of real numbers, which may loose some useful information and hence consequently affect on the decision results. As a modification to these, complex intuitionistic fuzzy set handles the uncertainties with the degrees whose ranges are extended from real subset to the complex subset with the unit disk and hence handle the two-dimensional information in a single set. Thus, motivated by this, we developed some new averaging aggregation operators, namely complex intuitionistic fuzzy (CIF) weighted averaging, CIF ordered weighted averaging and CIF hybrid averaging in conjunction with their desirable properties. Then, we utilized these operators to propose a multicriteria decision-making approach and illustrated a numerical example to demonstrate the working of the proposed approach. Finally, the proposed results are compared with existing approaches results.