Hosseinzadeh Lotfi, F.Allahviranloo, T.Pedrycz, W.Shahriari, M.Sharafi, H.Razipour, GhalehJough, S.2024-05-192024-05-1920231860-949Xhttps://doi.org/10.1007/978-3-031-44742-6_11https://hdl.handle.net/20.500.12713/4474This chapter introduces the concept of Fuzzy MABAC (Multi-Attributive Border Approximation Area Comparison), an innovative Multiple Attribute Decision Making (MADM) method. The chapter begins by providing a comprehensive overview of the MABAC method. To illustrate the practical implementation of MABAC, a numerical example is presented, utilizing crisp data. Building upon the understanding of MABAC, the chapter then explore the intricacies of fuzzy MABAC. The algorithm for fuzzy MABAC is elucidated and its handling in decision-making problems involving imprecise or uncertain data is demonstrated. To illustrate the efficacy of fuzzy MABAC, the method is applied to rank bank clerks according to four criteria. The step-by-step process of employing fuzzy MABAC to determine rankings is discussed. By the end of this chapter, readers will have a comprehensive understanding of both MABAC and fuzzy MABAC, and their practical applications in MADM. The numerical example and the real-life application in ranking bank clerks highlight the potential of fuzzy MABAC as an effective decision-making tool in complex scenarios. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.eninfo:eu-repo/semantics/closedAccessBook Chapter11212752892-s2.0-8518470006910.1007/978-3-031-44742-6_11N/A