INTEGRATED COST OPTIMIZATION IN SUPPLY CHAINS: A MIXED INTEGER LINEAR PROGRAMMING APPROACH

This Paper presents an integrated supply chain optimization model designed to minimize total costs in supply chain management using a Mixed Integer Linear Programming (MILP). The primary objective is to reduce overall transportation costs within the supply chain, including costs at each stage and inventory costs at warehouses. The model also ensures customer demands are met while considering the capacity constraints of suppliers, manufacturers, warehouses and customer zones. The supply chain in this Paper includes four echelons: supplier, manufacturer, warehouse and customer. Specifically, it comprises six suppliers, two manufacturers, five warehouses and five customer locations. By integrating these elements into a cohesive optimization model, businesses can make data-driven decisions to enhance supply chain efficiency and lower overall costs.