RT Journal Article
T1 Stock management in hospital pharmacy using chance-constrained model predictive control.
A1 Jurado, I
A1 Maestre, J M
A1 Velarde, P
A1 Ocampo-Martinez, C
A1 Fernández, I
A1 Tejera, B Isla
A1 Prado, J R Del
K1 Chance constraints
K1 Hospital pharmacy
K1 Inventory management
K1 Model predictive control
K1 Pharmacy Management Stockout Risk
K1 Stochastic Control
AB 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.
YR 2015
FD 2015-12-02
LK http://hdl.handle.net/10668/9697
UL http://hdl.handle.net/10668/9697
LA en
DS RISalud
RD Apr 5, 2025