Abstract
Real-world decision-making challenges tend to evolve into more intricate scenarios over time. In this context, the Fermatean fuzzy set emerges as an efficient and convenient framework, adept at illustrating the uncertainties inherent in multi-criteria decision-making (MCDM) problems. To address decision-making challenges intertwined with uncertainties, the fundamental objective of this study is to develop a Fermatean fuzzy MCDM tool. This tool aims to expand users’ scope to articulate their opinions and viewpoints. As a preliminary step, the study begins by elucidating the computation of the degree of proximity between the optimal alternative and its counterparts. This article presents the concept, representation, and pertinent characteristics of the Spearman rank correlation coefficient (CC) within the context of Fermatean fuzzy sets. Subsequent to this, a multi-criteria decision-making technique, fortified by incorporating Fermatean fuzzy operators (FFOs), is formulated based on the proposed Spearman rank CC. Ultimately, we demonstrate the significance and efficacy of the introduced approach by showcasing its application in a real-world context, specifically within the domain of supplier selection decision-making. The results revealed that the primary advantage of the provided decision rule lies in its potential to effectively reduce production costs and streamline complexity within the context of supplier selection problems, both in theory and practical application. We demonstrate the superiority of the proposed method in delivering reliable outcomes through a comprehensive analysis of FFOs and a comparative assessment against established techniques. A concrete case study is employed to firmly establish the stability and credibility of FFOs when combined with the Spearman rank CC. Additionally, this study carefully conducts a comprehensive comparative evaluation, comparing the previously developed methods with the newly proposed approach. This reinforces the robustness and authenticity of the FFO-based methodology and highlights its unique and practical nature.
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MA: conceptulization, methodolgy, data curation, writing—original draft. TR: investigation, supervision. AA: writing—review and editing, validation, supervision.
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Amman, M., Rashid, T. & Ali, A. Fermatean fuzzy multi-criteria decision-making based on Spearman rank correlation coefficient. Granul. Comput. 8, 2005–2019 (2023). https://doi.org/10.1007/s41066-023-00421-x
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DOI: https://doi.org/10.1007/s41066-023-00421-x