Multi-retailer Sales Model under Uncertain Demand in a Pharmaceutical Two-Echelon Supply Chain with Vendor Managed Inventory System

The Vendor Managed Inventory (VMI) system enables vendors to manage their own and their retailers' inventories to improve the performance of two-echelon supply chains. However, most VMI systems consider the demand patterns of the retailers as deterministic, which is uncommon in practice where variability is significant. This can lead to inefficient results, particularly within the pharmaceutical industry where an efficient supply chain through VMI is vital. The present work proposes a multi-retailer VMI model to maximize the profits of a two-echelon supply chain in the presence of non-deterministic or uncertain demand. Due to the complexity of the model, a micro-genetic algorithm was developed to determine the lot size strategy considering the variability of the non-deterministic demand within the profit function and reduce the stockout risk. Through computer simulation, the proposed VMI model was tested, showing that it is more efficient to reduce stockout events than those using deterministic demand patterns.