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
  • Panos M. Pardalos
Part of the Springer Optimization and Its Applications book series (SOIA, volume 74)


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.



This material is based upon work supported by the Office of Systems Redesign, Department of Veteran Affairs. This research has been partially supported by CAO funds.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Neng Fan
    • 1
  • Syed Mujahid
    • 2
  • Jicong Zhang
    • 3
  • Pando Georgiev
    • 2
  • Petraq Papajorgji
    • 2
  • Ingrida Steponavice
    • 4
  • Britta Neugaard
    • 5
    • 6
  • Panos M. Pardalos
    • 2
  1. 1.Department of Systems and Industrial EngineeringUniversity of ArizonaTucsonUSA
  2. 2.Department of Industrial and Systems Engineering, Center for Applied OptimizationUniversity of FloridaGainesvilleUSA
  3. 3.Functional Neuroscience and Neurosurgery Laboratory, Department of Neurology/Neurosurgery, School of MedicineThe Johns Hopkins UniversityBaltimoreUSA
  4. 4.Department of Mathematical Information TechnologyUniversity of JyvaskylaJyvaskylaFinland
  5. 5.James A. Haley VAMCTampaUSA
  6. 6.College of Public HealthUniversity of South FloridaTampaUSA

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