Volume 21 , Issue 4 , PP: 08-20, 2023 | Cite this article as | XML | Html | PDF | Full Length Article
Ankit Dubey 1 * , Ranjan Kumar 2
Doi: https://doi.org/10.54216/IJNS.210401
This paper provides a comprehensive evaluation and categorization of the various uncertain environment employed by researchers and scientists to model and analyze inventory management systems in diverse sectors, including healthcare, supply chain, and routing issues. Additionally, it examines the challenges associated with the classical inventory model and introduces the concepts of fuzzy theory and the extended fuzzy principle in inventory management. The article presents important definitions related to fuzzy theory, including the fuzzy inventory model and its challenges. It also explores the applications of the extended fuzzy principle in real-life problems. The study focuses on inventory management under the extended fuzzy principle (Intuitionistic, Neutrosophic, Pythagorean, and so on), considering uncertain demand and imprecise data. The research contributes to the field by providing insights into the potential of fuzzy theory in overcoming the challenges of classical models and improving decision-making in inventory management.
Triangular fuzzy number(TFN) , Triangular neutrosophic number(TNN) , Neutrosophic inventory management(NIM) , Supply chain , Economic order quantity (EOQ).
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