Stochastic programming for nurse assignment

Prattana Punnakitikashem; Jay M. Rosenberger; Deborah Buckley Behan

doi:10.1007/s10589-007-9084-2

Stochastic programming for nurse assignment

Prattana Punnakitikashem
, Jay M. Rosenberger
, Deborah Buckley Behan

National Institute of Development Administration
University of Texas at Arlington College of Engineering
University of Texas at Arlington

Research output: Contribution to journal › Article › peer-review

67 Citations (Scopus)

Abstract

We present a brief overview of four phases of nurse planning. For the last phase, which assigns nurses to patients, a stochastic integer programming model is developed. A Benders' decomposition approach is proposed to solve this problem, and a greedy algorithm is employed to solve the recourse subproblem. To improve the efficiency of the algorithm, we introduce sets of valid inequalities to strengthen a relaxed master problem. Computational results are provided based upon data from Baylor Regional Medical Center in Grapevine, Texas. Finally, areas of future research are discussed.

Original language	English
Pages (from-to)	321-349
Number of pages	29
Journal	Computational Optimization and Applications
Volume	40
Issue number	3
DOIs	https://doi.org/10.1007/s10589-007-9084-2
Publication status	Published - Jul 2008
Externally published	Yes

Keywords

Benders' decomposition
L-shaped method
Nurse assignment
Stochastic programming

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10.1007/s10589-007-9084-2

Cite this

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AU - Rosenberger, Jay M.

AU - Buckley Behan, Deborah

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AB - We present a brief overview of four phases of nurse planning. For the last phase, which assigns nurses to patients, a stochastic integer programming model is developed. A Benders' decomposition approach is proposed to solve this problem, and a greedy algorithm is employed to solve the recourse subproblem. To improve the efficiency of the algorithm, we introduce sets of valid inequalities to strengthen a relaxed master problem. Computational results are provided based upon data from Baylor Regional Medical Center in Grapevine, Texas. Finally, areas of future research are discussed.

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KW - L-shaped method

KW - Nurse assignment

KW - Stochastic programming

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Stochastic programming for nurse assignment

Abstract

Keywords

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