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Stochastic programming for nurse assignment

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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.

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Authors and Affiliations

  1. School of Business Administration, National Institute of Development Administration, Bangkok, 10240, Thailand

    Prattana Punnakitikashem

  2. Department of Industrial and Manufacturing Systems Engineering, The University of Texas at Arlington, Arlington, TX, 76019-0407, USA

    Jay M. Rosenberger

  3. School of Nursing, The University of Texas at Arlington, Arlington, TX, 76019-0017, USA

    Deborah Buckley Behan

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  1. Prattana Punnakitikashem
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  2. Jay M. Rosenberger
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  3. Deborah Buckley Behan
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Correspondence to Prattana Punnakitikashem.

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Punnakitikashem, P., Rosenberger, J.M. & Buckley Behan, D. Stochastic programming for nurse assignment. Comput Optim Appl 40, 321–349 (2008). https://doi.org/10.1007/s10589-007-9084-2

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  • DOI: https://doi.org/10.1007/s10589-007-9084-2

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