Optimizing inventory planning in multi-echelon supply chains under uncertainty: a decision-making approach using review policies

This study conducts a comparative analysis of three inventory review policies within a multi-stage supply chain framework to determine the best policies to adopt. Optimizing supply chain inventory planning is challenging due to uncertain demand. The problem involves minimizing the overall operating costs and determining the optimal reorder plan for the operational network. Three models are developed, employing a multi-period planning approach that considers supply flows, and inventory levels at facilities. To test the models, a real-world supply chain case study is solved. The uncertain demand faced by retailers is addressed by defining the optimal safety stock that guarantees a given service level at each facility. Using the guaranteed service approach to model time delays in distribution flows, we effectively capture the stochastic nature of demand uncertainty. We developed multi-period planning formulations that indicate the precise amount and timing of inventory replenishments. Additionally, this work emphasizes the importance of lead time in multi-period planning modeling, a topic often overlooked in the literature. The combination of inventory planning with inventory policies enables better operational decisions for supply chain managers. The results obtained allow the decision makers to choose the best inventory policy option based on the conditions of their supply chain.