An application of stochastic programming method for nurse scheduling problem in real word hospital

•Modeling nurse scheduling problem which considers uncertainties.•Sample Average Approximation (SAA) method is used to obtain an optimal schedule.•A case study conducted in Department of Heart Surgery in Razavi Hospital.•The main objective of the model is to minimize the total costs.•The problem SNS...

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Published in:	Computers & industrial engineering Vol. 96; pp. 192 - 200
Main Authors:	Bagheri, Mohsen, Gholinejad Devin, Ali, Izanloo, Azra
Format:	Journal Article
Language:	English
Published:	New York Elsevier Ltd 01.06.2016 Pergamon Press Inc
Subjects:	Assignment problem Health care Hospitals Mathematical models Nurse scheduling Nurses Recourse action Sample average approximation Samples Schedules Scheduling algorithms Statistical analysis Statistical methods Stochastic models Stochastic programming Studies Uncertainty Iran Recourse action Uncertainty Nurse scheduling Stochastic programming Sample average approximation
ISSN:	0360-8352, 1879-0550
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Abstract	•Modeling nurse scheduling problem which considers uncertainties.•Sample Average Approximation (SAA) method is used to obtain an optimal schedule.•A case study conducted in Department of Heart Surgery in Razavi Hospital.•The main objective of the model is to minimize the total costs.•The problem SNSP was formulated using the recourse model. Given its complexity and relevance in healthcare, the well-known Nurse Scheduling Problem (NSP) has been the subject of several researches and different approaches have been used for its solution. The importance of this problem comes from its critical role in healthcare processes as NSP assigns nurses to daily shifts while respecting both the preferences of the nurses and the objectives of hospital. Most models in NSP literature have dealt with this problem in a deterministic environment, while in the real-world applications of NSP, the vagueness of information about management objectives and nurse preferences are sources of uncertainties that need to be managed so as to provide a qualified schedule. In this study, we propose a stochastic optimization model for the Department of Heart Surgery in Razavi Hospital, which accounts for uncertainties in the demand and stay period of patients over time. Sample Average Approximation (SAA) method is used to obtain an optimal schedule for minimizing the regular and overtime assignment costs, with the numerical experiments demonstrating the convergence of statistical bounds and moderate sample size for a given numerical experiment. The results confirm the validity of the model.
AbstractList	Given its complexity and relevance in healthcare, the well-known Nurse Scheduling Problem (NSP) has been the subject of several researches and different approaches have been used for its solution. The importance of this problem comes from its critical role in healthcare processes as NSP assigns nurses to daily shifts while respecting both the preferences of the nurses and the objectives of hospital. Most models in NSP literature have dealt with this problem in a deterministic environment, while in the real-world applications of NSP, the vagueness of information about management objectives and nurse preferences are sources of uncertainties that need to be managed so as to provide a qualified schedule. In this study, we propose a stochastic optimization model for the Department of Heart Surgery in Razavi Hospital, which accounts for uncertainties in the demand and stay period of patients over time. Sample Average Approximation (SAA) method is used to obtain an optimal schedule for minimizing the regular and overtime assignment costs, with the numerical experiments demonstrating the convergence of statistical bounds and moderate sample size for a given numerical experiment. The results confirm the validity of the model. •Modeling nurse scheduling problem which considers uncertainties.•Sample Average Approximation (SAA) method is used to obtain an optimal schedule.•A case study conducted in Department of Heart Surgery in Razavi Hospital.•The main objective of the model is to minimize the total costs.•The problem SNSP was formulated using the recourse model. Given its complexity and relevance in healthcare, the well-known Nurse Scheduling Problem (NSP) has been the subject of several researches and different approaches have been used for its solution. The importance of this problem comes from its critical role in healthcare processes as NSP assigns nurses to daily shifts while respecting both the preferences of the nurses and the objectives of hospital. Most models in NSP literature have dealt with this problem in a deterministic environment, while in the real-world applications of NSP, the vagueness of information about management objectives and nurse preferences are sources of uncertainties that need to be managed so as to provide a qualified schedule. In this study, we propose a stochastic optimization model for the Department of Heart Surgery in Razavi Hospital, which accounts for uncertainties in the demand and stay period of patients over time. Sample Average Approximation (SAA) method is used to obtain an optimal schedule for minimizing the regular and overtime assignment costs, with the numerical experiments demonstrating the convergence of statistical bounds and moderate sample size for a given numerical experiment. The results confirm the validity of the model.
Author	Bagheri, Mohsen Izanloo, Azra Gholinejad Devin, Ali
Author_xml	– sequence: 1 givenname: Mohsen surname: Bagheri fullname: Bagheri, Mohsen email: M_Bagheri@sadjad.ac.ir organization: Department of Industrial Engineering, Sadjad University of Technology, Mashhad, Iran – sequence: 2 givenname: Ali orcidid: 0000-0002-8666-2253 surname: Gholinejad Devin fullname: Gholinejad Devin, Ali email: Al.Gh130@sadjad.ac.ir organization: Department of Industrial Engineering, Sadjad University of Technology, Mashhad, Iran – sequence: 3 givenname: Azra surname: Izanloo fullname: Izanloo, Azra email: A.izanloo@yahoo.com organization: Research and Education Department, Razavi Hospital, Mashhad, Iran
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Snippet	•Modeling nurse scheduling problem which considers uncertainties.•Sample Average Approximation (SAA) method is used to obtain an optimal schedule.•A case study... Given its complexity and relevance in healthcare, the well-known Nurse Scheduling Problem (NSP) has been the subject of several researches and different...
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SubjectTerms	Assignment problem Health care Hospitals Mathematical models Nurse scheduling Nurses Recourse action Sample average approximation Samples Schedules Scheduling algorithms Statistical analysis Statistical methods Stochastic models Stochastic programming Studies Uncertainty
Title	An application of stochastic programming method for nurse scheduling problem in real word hospital
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