An Integrated Inventory Classification And Cycle Replenishment Offset Model For E-Fulfillment Optimization – A Case Study Of Kingfood Mart

Abstract

Making the supply chain function better and be more robust in evolving corporate environments depends on efficiently managing the e-supply chain and optimizing inventory delivery. Combining the Dynamic Classification and Inventory Offset Cycle models helps the research concentrate on reducing high out-of-stock rates, particularly for high-margin frozen items, enhancing service levels, and maximizing gross profit. By concentrating on these crucial areas, the research aims to make the business more competitive and efficient. The aim of this study is to develop a method using Mixed Integer Linear Programming (MILP) to identify the optimal strategy for restocking under uncertain demand changing conditions. The MILP model is built to manage complex decision-making processes so that product levels match real-time demand patterns. This paper helps to enhance e-supply chain management generally by developing a robust strategy for supply optimization. Kingfood Mart can make it simpler for consumers to locate items, generate more income, and raise customer happiness by applying more sophisticated inventory control strategies.