| Title | Stock management in hospital pharmacy using chance-constrained model predictive control |
|---|---|
| Authors | JURADO FLORES, ISABEL, Maestre, J. M. , VELARDE RUEDA, PABLO ANIBAL, Ocampo-Martinez, C. , Fernandez, I. , Isla Tejera, B. , del Prado, J. R. |
| 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 |
| 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 |
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