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Application of robust model predictive control to inventory management in hospitalary pharmacy

Authors

VELARDE RUEDA, PABLO ANIBAL, Maestre J.M. , JURADO FLORES, ISABEL, Fernández I. , Tejera B.I. , Del Prado J.R. , Martinez Garcia H. , ; Grau A.

External publication

No

Means

IEEE Int. Conf. Emerg. Technol. Fact. Autom., ETFA

Scope

Conference Paper

Nature

Científica

JCR Quartile

SJR Quartile

Publication date

01/01/2014

Scopus Id

2-s2.0-84946689227

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 robust and advanced control techniques for pharmacy management in two Spanish hospitals, we propose, assess and compare three robust model predictive control(Chance-Constraints, Multi-Scenarios approach and Tree-Based Methods) as a mean to relieve this issue. © 2014 IEEE.

Keywords

Factory automation; Hospitals; Inventory control; Robust control; Advanced control; Chance constraint; Complex problems; Inventory management; Multi scenarios; Optimization criteria; Robust model predictive control; Tree-based methods; Model predictive control