Stock management in hospital pharmacy using chance-constrained model predictive control
Journal Article (2016)
Computers in Biology and Medicine
Maestre Torreblanca, José María
Isla Tejera, B.
del Prado Llergo, J.R.
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 resides 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 predictive 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 between conservativeness and efficiency. The solution proposed is assessed to study its implementation in two Spanish hospitals.
control system synthesis, control theory, optimisation, predictive control.
hospital pharmacy, inventory management, model predictive control, chance constraints
I. Jurado, J.M. Maestre, P. Velarde, C. Ocampo-Martínez, I. Fernández, B. Isla and J. del Prado. Stock management in hospital pharmacy using chance-constrained model predictive control. Computers in Biology and Medicine, 72: 248-255, 2016.