Stock Management in Hospital Pharmacy using Chance-Constrained Model Predictive Control

Abstract

One of the most important problems in the pharmacy department of a hospital is stock management. The clinical needs of drugs must be satisfied with limited work labor while minimizing the use of economical resources. The complexity of the problem re sides in the random nature of the drug demand and the multiple constraints that must be taken into account in every decision. In this article, chance-constrained model predic tive control is proposed to deal with this problem. The flexibility of model predictive control allows taking into account explicitly the different objectives and constraints involved in the problem while the use of chance constraints provides a trade-off be tween conservativeness and efficiency. The solution proposed is assessed to study its implementation in two Spanish hospitals.