An edge computing approach to EOQ optimization for deteriorating items with nonlinear demand and Weibull deterioration

In this paper deals with perishable commodities or products that are prone to obsolescence face a significant difficulty in effectively managing their inventory of deteriorating materials. When considering complex real-world circumstances, like nonlinear demand patterns and the deterioration of things over time, traditional Economic Order Quantity (EOQ) models frequently fail. To properly represent the time-varying degradation of goods, this paper suggests an improved EOQ model that includes Weibull deterioration and nonlinear demand, represented as a cubic function. By combining variables including real-time demand variations, item condition, and environmental elements that affect deterioration, edge computing facilitates quicker decision-making. We explain how this integrated method ensures optimal stock availability while minimizing overall inventory expenses, including holding, ordering, and deterioration costs.