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An application of chance-constrained model predictive control to inventory management in Hospitalary Pharmacy

Authors

Maestre J.M. , VELARDE RUEDA, PABLO ANIBAL, JURADO FLORES, ISABEL, Ocampo-Martinez C. , Fernandez I. , Isla Tejera B. , Del Prado J.R.

External publication

No

Means

Proc IEEE Conf Decis Control

Scope

Conference Paper

Nature

Científica

JCR Quartile

SJR Quartile

Publication date

01/01/2014

Scopus Id

2-s2.0-84988274759

Abstract

Inventory management is one of the main tasks that the pharmacy department has to carry out in a hospital. It is a complex problem that requires to establish a tradeoff between different and contradictory optimization criteria. The complexity of the problem is increased due to the constraints that naturally arise in this type of applications. In this paper, which corresponds to preliminary works performed to implement advanced control techniques for pharmacy management in two Spanish hospitals, we propose and assess chance-constrained model predictive control (CC-MPC) as a mean to relieve this issue. © 2014 IEEE.

Keywords

Hospitals; Inventory control; Predictive control systems; Advanced control; Chance-constrained model; Complex problems; Inventory management; Main tasks; Optimization criteria; Model predictive control