Stochastic inventory control and distribution of blood products

Inventory control in perishable products supply chain is one of the biggest challenges today, especially for medicines and blood products supply chain. Shortage can increase the mortality risk at hospitals, on the contrary, high levels of inventory could generate wastage of these resources. This paper studies the problem of inventory control and distribution of blood products. This study determines the number of blood units to be processed by the blood center and the number of units of blood products to be ordered by hospitals to minimize the total cost and the shortage and wastage levels in blood supply chain. Two optimization models are formulated: A Mixed Integer Linear Programming (MILP) Model for known demands and a Stochastic Programming (SP) Model for the case where demands are uncertain, considering multiple periods, types of blood and life time of products. Datasets are generated to evaluate the efficiency of proposed models for a multi-hospitals single-blood center system. An algorithm is developed to simulate the supply chain and evaluate the mathematical models. The results show that the SP Model obtains lower expected rates of shortage and wastage compared to the deterministic model. In this last, demands are approximated by their mean values.