Inventory Models use of Fuzzy Theory (Journal of Advances and Scholarly Researches in Allied Education, 2023)
An essential part of optimising the supply chain is inventory management, but conventional models have a hard time taking into consideration the inherent uncertainties and inaccuracies in real-world data. To make inventory models more accurate and resilient, fuzzy logic—a mathematical framework for dealing with ambiguity and uncertainty—offers a potential solution. Demand forecasting, lead time estimate, and order quantity determination are some of the inventory management components that are examined in this work as they pertain to fuzzy theory integration. There are a lot of reasons that make it hard to anticipate with any degree of accuracy how demand will change for different items. The fuzziness of demand patterns may be captured by using fuzzy demand forecasting approaches, which enable the representation of imprecise information. Our demand forecasting algorithm is built on fuzzy logic and incorporates expert views and historical data to make future demand predictions more accurate and flexible.