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

Journal Article (2016)


Computers in Biology and Medicine





Doc link


Download the digital copy of the doc pdf document


  • Jurado, Isabel

  • Maestre Torreblanca, José María

  • Velarde, Pablo

  • Ocampo Martínez, Carlos A.

  • Fernández, Isabel

  • Isla Tejera, B.

  • del Prado Llergo, J.R.


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.


control system synthesis, control theory, optimisation, predictive control.

Author keywords

hospital pharmacy, inventory management, model predictive control, chance constraints

Scientific reference

I. Jurado, J.M. Maestre, P. Velarde, C. Ocampo-Martínez, I. Fernández, B. Isla and J. del Prado. Stock management in hospital pharmacy using chance-constrained model predictive control. Computers in Biology and Medicine, 72: 248-255, 2016.