Volume 24 , Issue 4 , PP: 50-58, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
C. Balakrishna Moorthy 1 , D. Rajani 2 , A. P. Pushpalatha 3 * , S. Ramya 4 , A. Selvaraj 5 * , Mohit Tiwari 6
Doi: https://doi.org/10.54216/IJNS.240403
Optimal inventory management is one of the most critical components for companies to thrive in the competitive market while meeting their customers’ demands, reducing costs, and developing their operations. In this paper, the utilization of different technologies and instruments ranging from the most modern ones to mathematical ones was analyzed to demonstrate how the system can function successfully. It is expected that Neutrosophic fuzzy logic is one of the most complicated approaches that allow for proper uncertainty management, forecasting, and inventory control improvements. Fundamentally, the process could be that much more insightful due to the availability of mathematical modelling and on-the-go support systems. Through the use of dynamic programming with the help of Python tools to process these models, Full optimization under fuzzy demand is possible to achieve. Therefore, one could conclude that companies have many opportunities to develop their operations, reduce costs, and keep their customers happy even in a highly dynamic and uncertain business environment.
Inventory Management , Neutrosophic Fuzzy Logic , Mathematical Techniques , Uncertainty Handling, Optimization
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