Title Stock management in hospital pharmacy using chance-constrained model predictive control
Authors JURADO FLORES, ISABEL, Maestre, J. M., Velarde, P., Ocampo-Martinez, C., Fernandez, I., Isla Tejera, B., del Prado, J. R., JURADO FLORES, ISABEL
External publication No
Means Comput. Biol. Med.
Scope Article
Nature Científica
JCR Quartile 2
SJR Quartile 2
JCR Impact 1.83600
SJR Impact 0.55400
Area International
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-84951759183&doi=10.1016%2fj.compbiomed.2015.11.011&partnerID=40&md5=4d3cc0dfbd52ff045b13a915ddcd67ad
Publication date 01/05/2016
ISI 000375812500024
Scopus Id 2-s2.0-84951759183
DOI 10.1016/j.compbiomed.2015.11.011
Abstract 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.
Keywords Hospital pharmacy; Inventory management; Model predictive control; Chance constraints; Stochastic Control; Pharmacy Management Stockout Risk
Universidad Loyola members