Nurse Scheduling Problem: An Integer Programming Model with a Practical Application
Neng Fan,
Syed Mujahid,
Jicong Zhang,
Pando Georgiev (),
Petraq Papajorgji,
Ingrida Steponavice,
Britta Neugaard and
Panos M. Pardalos
Additional contact information
Neng Fan: University of Arizona
Syed Mujahid: University of Florida
Jicong Zhang: The Johns Hopkins University
Pando Georgiev: University of Florida
Petraq Papajorgji: University of Florida
Ingrida Steponavice: University of Jyvaskyla
Britta Neugaard: James A. Haley VAMC
Panos M. Pardalos: University of Florida
A chapter in Systems Analysis Tools for Better Health Care Delivery, 2013, pp 65-98 from Springer
Abstract:
Abstract We use a binary integer programming model to formulate and solve a nurse scheduling problem (NSP) which maximally satisfies nurse preferences. In a practical application of a VA hospital, besides considering the scheduling of two types of nurses (registered nurses and licensed practical nurses), two other types of employees (nursing assistants and health care techs), one nurse manager, and a clinical nurse leader are also included in our model. Most of these employees are working full-time. In addition, we distinguish the schedule of weekdays and weekends with different requirements and different preferences for employees. Besides the requirements for each shift, we consider requirements for specific employees in some shifts in practical situations. The seven shifts each day do not necessarily have the same length in our model. Vacation time of employees is also considered in our model. Thus, the requirements for nurse scheduling are complicated and the objective is to maximize the satisfaction of preferred schedules of all these employees, including both nurses and other staffs. The presented model is complex, but efficiently solvable, satisfying the set of requirements in a particular application in a VA hospital.
Keywords: Nurse Scheduling Problem; Nurse Leader; Tech Health Care (HCT); Nurse Managers; Registered Nurses (RN) (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-1-4614-5094-8_5
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DOI: 10.1007/978-1-4614-5094-8_5
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