Aczel-Alsina Aggregation Operators on Complex Fermatean Fuzzy Information With Application to Multi-Attribute Decision Making

• Published in: IEEE access Vol. 11; pp. 141703 - 141722
• Main Authors: Chen, Li, Zhou, Xiaoqiang, Wu, Mingyuan, Shi, Yuanjun, Wang, Yongzhi
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aczel-Alsina operation; aggregation operator; complex Fermatean fuzzy set; Complexity; Decision making; Fuzzy logic; Fuzzy sets; Fuzzy systems; multi-attribute decision making; Object recognition; Operators; Organizations; Presses; Uncertainty
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2023.3342175

Decision-making problems are often characterized by complexity and uncertainty, presenting significant challenges for individuals or organizations. Aczel Alsina t-norm (TN) and t-conorm (TCN) are more flexible than other TN and TCN due to their variable parameters. They have been applied to various types of fuzzy multi-attribute decision making (MADM). The complex Fermatean fuzzy set (CFFS) model is an extension of the complex fuzzy set and Fermatean fuzzy set, and it can more accurately express the evaluation values of attributes in complex MADM problems. The purpose of this paper is to propose a MADM method based on Aczel-Alsina TN and TCN under complex Fermatean fuzzy environment. First, the Aczel-Alsina sum and product operations of the complex Fermatean fuzzy number(CFFN) are introduced, and some desirable properties of the two operations are studied. Subsequently, several complex Fermatean fuzzy aggregation operators are established, such as the complex Fermatean fuzzy Aczel-Alsina weighted averaging CFFAAWA) operator, complex Fermatean fuzzy Aczel-Alsina ordered weighted averaging (CFFAAOWA) operator, complex Fermatean fuzzy Aczel-Alsina weighted geometric (CFFAAWG) operator, and complex Fermatean fuzzy Aczel-Alsina ordered weighted geometric (CFFAAOWG) operator. In addition, certain significant properties of the aggregation operators are investigated. Finally, a method based on new aggregation operators is proposed, and a numerical example is provided to demonstrate the effectiveness and practicality of the proposed method.