Application of Optimization Techniques to Solve Inventory Problems

This manuscript explores the critical role of optimization methods in addressing various challenges associated with inventory management. Effective inventory management is essential for maintaining operational efficiency, minimizing costs, and enhancing customer satisfaction. This paper provides a comprehensive review of key optimization techniques, including Economic Order Quantity (EOQ)[1], Just-In-Time (JIT)[2], ABC analysis[9], dynamic programming[4], and machine learning[5], among others. Each technique is discussed in the context of specific inventory problems, such as stockouts, overstocking, demand variability, and lead time uncertainty. Through detailed analysis and case studies, the manuscript demonstrates how these techniques can be applied to real-world scenarios to optimize inventory levels, reduce costs, and improve overall supply chain performance. The findings highlight the importance of selecting appropriate optimization methods based on the unique characteristics of the inventory problem at hand, offering valuable insights for both practitioners and researchers in the field of supply chain management.