Complex T-spherical fuzzy Dombi aggregation operators and their applications in multiple-criteria decision-making.

Area of Science:

• Fuzzy Set Theory
• Decision Sciences
• Computational Intelligence

Background:

• Complex fuzzy sets (CFSs) are vital for modeling two-dimensional information.
• Extensions of CFSs, like complex T-spherical fuzzy sets (CTSFS), are increasingly used in decision-making.
• Existing methods require novel aggregation operators for complex fuzzy environments.

Purpose of the Study:

• To introduce Dombi operations for complex T-spherical fuzzy sets (CTSFS).
• To define novel aggregation operators based on Dombi operations for CTSFS.
• To develop and validate a multi-criteria decision-making (MCDM) method using these operators in the CTSF environment.

Main Methods:

• Definition of Dombi operations tailored for CTSFS.
• Development of aggregation operators: CTSDFWAA, CTSDFWGA, CTSDFOWAA, CTSDFOWGA.
• Formulation of an MCDM algorithm within the CTSF framework.

Main Results:

• Successfully defined Dombi operations and aggregation operators for CTSFS.
• Developed a novel MCDM method applicable to complex fuzzy environments.
• Demonstrated the method's efficacy through a COVID-19 diagnosis example and sensitivity analysis.

Conclusions:

• The proposed Dombi operations and aggregation operators offer a robust framework for CTSFS.
• The developed MCDM method provides an effective tool for complex decision-making problems.
• The study highlights the advantages and limitations of the proposed approach in practical applications.