Selection of Database Management System by Using Multi-Attribute Decision-Making Approach Based on Probability Complex Fuzzy Aggregation Operators

Abstract

A database management system (DBMS) is a piece of software that makes it easier to create, organize, store, retrieve, and manage structured data. It functions as a central system for effectively managing data storage and access, ensuring data integrity and security, and offering tools for querying and reporting. Because of its multi-criteria nature, choosing an optimal DBMS is a multi-attribute decision-making (MADM) dilemma. Thus, in this script, we devise some elementary operations and interpret probability AOs within the cartesian form of complex fuzzy set (CFS) such as probability complex fuzzy weighted averaging (P-CFWA), probability complex fuzzy ordered weighted averaging (P-CFOWA), immediate P-CFOWA (IP-CFOWA), probability complex fuzzy weighted geometric (P-CFWG), probability complex fuzzy ordered weighted geometric (P-CFOWG), immediate P-CFOWG (IP-CFOWG) operators. Further, we devise a technique of MADM within the structure of CFS to tackle complicated and awkward genuine life MADM dilemmas that contain extra fuzzy information. After that, in this article, we investigate a numerical example “selection of the optimal database management system” to cope with a MADM dilemma within CFS. In the last of this article, we compare the invented theory with certain other prevailing theories to reveal supremacy and dominance.