Complex linear Diophantine fuzzy sets and their applications in multi-attribute decision making

This study utilizes the concept complex linear Diophantine fuzzy set (CLDFS) which is an advanced framework for handling ambiguity in the presence of periodicity for decision-making. Unlike existing techniques, CLDFS offers a larger solution space, incorporating reference parameters alpha and beta. Two real-life scenarios - bridge design selection and AI system choice - are examined to showcase CLDFS's impact on practical applications. The study presents multi-attribute decision-making (MADM) and multi-attribute group decision-making (MAGDM) algorithms with visualizations, applied to warehouse distributor selection and faculty candidate evaluation. The comparative analysis highlights CLDFS's advantages over other methods