JURADO FLORES, ISABEL, Maestre, J. M. , VELARDE RUEDA, PABLO ANIBAL, Ocampo-Martinez, C. , Fernandez, I. , Isla Tejera, B. , del Prado, J. R.
No
Comput Biol Med
Article
Científica
1.836
0.554
01/05/2016
000375812500024
2-s2.0-84951759183
One of the most important problems in the pharmacy department of a hospital is stock management. The clinical need for drugs must be satisfied with limited work labor while minimizing the use of economic 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. (C) 2015 Elsevier Ltd. All rights reserved.
Hospital pharmacy; Inventory management; Model predictive control; Chance constraints; Stochastic Control; Pharmacy Management Stockout Risk