Optimizing Computer Engineering Problems Using CODAS Method with Bipolar Complex Fuzzy Soft Frank Aggregation Operators

Abstract

In this article, we start by explaining why Bipolar Complex Fuzzy Soft Set (BCFSS) is better than existing approaches by highlighting its abilities to enhance Computer Engineering (CpE) by removing ambiguity more effectively than Fuzzy Set (FS), Fuzzy Soft Set (FSS), Complex Fuzzy Soft Set (CFSS), Bipolar Fuzzy Set (BFS), Bipolar Fuzzy  Soft Set (BFSS), and Bipolar Complex Fuzzy Set (BCFS). This will improve effectiveness as well as clarity. Make sure that those new to fuzzy sets properly understand the key issue in CpE. Reveal first the BCFSS’s new strategy and then detail how it differs from existing approaches, pointing out the overlooked features of previous approaches that justified your research. Enhance the preparation concept link by explaining how BCFSS enhances CpE Decision-Making(DM) in situations when conventional models are inadequate when paired with Frank Aggregation Operator (AO) (Frank Arithmetic Aggregation Operator (FAAO) and Frank Geometric Aggregation Operator (FGAO)). Moreover, keeping in mind the effectiveness of the “Combinative Distance-based Assessment (CODAS) method” we developed this method in the framework of BCFSSs and used this method and develop AOs to solve some decision-making problems related to CpE. Our sentence structure should also be refined to provide smooth transitions between ideas and to enhance readability and navigation. Lastly, provide comparison studies that highlight the improvement’s superiority over current methods to show that it is feasible.