Supplier Selection Using Multi-Attributive Border Approximation Area Comparison (MABAC) Model in Different Fuzzy Environments

Abstract

The main objective of this study is to develop a supplier selection approach that incorpo rates Multi-Attribute Border Approximation Area Comparison (MABAC) in three different fuzzy environments: Intuitionistic fuzzy MABAC, fuzzy MABAC, and Pythagorean fuzzy MABAC. By addressing uncertainties and assessments related to qualitative aspects such as quality, responsiveness, and reliability, the technique aims to optimize competing crite ria. Initially, the fuzzy MABAC methods utilize fuzzy evaluations to determine supplier ranks. Subsequently,fuzzy technologies that address imprecision in decision-making are integrated to assess the consistency of supplier rankings. The robustness of the approach is demonstrated by the consistent rankings of the best and worst suppliers across all three fuzzy environments. This innovative approach provides a reliable method for selecting sup pliers, ensuring that businesses can make informed decisions that consider both qualitative and quantitative factors even in uncertain circumstances.