An Optimization of Inventory Control in Supply Chain Under Time Varying Holding Costs with Exponential Demand Rate

Supply chains are complex networks of interconnected elements involved in production and distribution of goods & services, and they are subject to various uncertainties such as demand fluctuations, supplier issues, natural disasters, geopolitical events, and regulatory changes. Controlling inventory is a key component of production systems followed by SCM, since it requires striking a balance between the costs of keeping inventory levels at a certain level and satisfying the expectations of customers at different echelons. An adaptive method for inventory control in a system is dissected and studied in this article. This strategy seeks to optimize inventory decisions by using a dynamic inventory control model as its foundation. This model includes real-time data on exponential demand patterns and inventory levels to do so. As per the proposed approach, the adaptive strategy is superior to the static method in terms of lowering expenses associated with inventory and raising the quality of service provided to customers. The present research also demonstrates that the performance of the adaptive strategy is particularly strong when demand patterns are varying and difficult to forecast with time varying holding cost. This was one of the hypotheses that the study tested. The research emphasizes how critical it is to include real-time data into inventory decision-making and underlines the potential benefits of utilizing adaptive ways to handle the issues of managing inventory in an environment that is both dynamic and unpredictable.