Stock management in hospital pharmacy using chance-constrained model predictive control

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 t...

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Autores: Jurado Flores, Isabel, Maestre Torreblanca, José María, Velarde Rueda, Pablo Aníbal, Ocampo-Martínez, Carlos, Isla Tejera, Beatriz, Prado Llergo, José Ramón Del
Tipo de recurso: artículo
Fecha de publicación:2015
País:España
Institución:Universidad Loyola Andalucía
Repositorio:Brújula
OAI Identifier:oai:repositorio.uloyola.es:20.500.12412/5635
Acceso en línea:https://hdl.handle.net/20.500.12412/5635
Access Level:acceso abierto
Palabra clave:Hospital Pharmacy
Inventory management
Model Predictive Control
Chance constraints
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spelling Stock management in hospital pharmacy using chance-constrained model predictive controlJurado Flores, IsabelMaestre Torreblanca, José MaríaVelarde Rueda, Pablo AníbalOcampo-Martínez, CarlosIsla Tejera, BeatrizPrado Llergo, José Ramón DelHospital PharmacyInventory managementModel Predictive ControlChance constraintsOne 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.2015info:eu-repo/semantics/articlehttps://hdl.handle.net/20.500.12412/5635reponame:Brújulainstname:Universidad Loyola AndalucíaIngléshttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:repositorio.uloyola.es:20.500.12412/56352026-06-24T12:48:37Z
dc.title.none.fl_str_mv Stock management in hospital pharmacy using chance-constrained model predictive control
title Stock management in hospital pharmacy using chance-constrained model predictive control
spellingShingle Stock management in hospital pharmacy using chance-constrained model predictive control
Jurado Flores, Isabel
Hospital Pharmacy
Inventory management
Model Predictive Control
Chance constraints
title_short Stock management in hospital pharmacy using chance-constrained model predictive control
title_full Stock management in hospital pharmacy using chance-constrained model predictive control
title_fullStr Stock management in hospital pharmacy using chance-constrained model predictive control
title_full_unstemmed Stock management in hospital pharmacy using chance-constrained model predictive control
title_sort Stock management in hospital pharmacy using chance-constrained model predictive control
dc.creator.none.fl_str_mv Jurado Flores, Isabel
Maestre Torreblanca, José María
Velarde Rueda, Pablo Aníbal
Ocampo-Martínez, Carlos
Isla Tejera, Beatriz
Prado Llergo, José Ramón Del
author Jurado Flores, Isabel
author_facet Jurado Flores, Isabel
Maestre Torreblanca, José María
Velarde Rueda, Pablo Aníbal
Ocampo-Martínez, Carlos
Isla Tejera, Beatriz
Prado Llergo, José Ramón Del
author_role author
author2 Maestre Torreblanca, José María
Velarde Rueda, Pablo Aníbal
Ocampo-Martínez, Carlos
Isla Tejera, Beatriz
Prado Llergo, José Ramón Del
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Hospital Pharmacy
Inventory management
Model Predictive Control
Chance constraints
topic Hospital Pharmacy
Inventory management
Model Predictive Control
Chance constraints
description 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.
publishDate 2015
dc.date.none.fl_str_mv 2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.12412/5635
url https://hdl.handle.net/20.500.12412/5635
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Brújula
instname:Universidad Loyola Andalucía
instname_str Universidad Loyola Andalucía
reponame_str Brújula
collection Brújula
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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