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The nurse scheduling problem: a combinatorial problem, solved by the combination of constraint programming and real
Studies in Health Technology and Informatics
|June 29, 1999
Summary
Constraint Programming (CP) offers a flexible solution for the complex Nurse Scheduling Problem (NSP). This approach effectively handles individual requests and unforeseen absences, improving upon traditional operational research methods.
Area of Science:
- Operations Research
- Computer Science
- Healthcare Management
Background:
- The Nurse Scheduling Problem (NSP) is a complex challenge in healthcare management.
- Traditional operational research methods lack flexibility for individual nurse requests and managing absences.
Purpose of the Study:
- To explore the application of Constraint Programming (CP) for solving the NSP.
- To introduce Gymnaste, a CP-based package for automated nurse scheduling.
Main Methods:
- Modeling the NSP using Constraint Programming (CP).
- Developing the Gymnaste package with a focus on user interface for heuristic selection.
- Beta-testing Gymnaste on pilot sites.
Main Results:
- Gymnaste generates schedules rapidly (under a minute for 20-30 nurses over 4 weeks).
- The CP approach accommodates individual requests and unforeseen absences more effectively.
- Preliminary evaluations indicate positive sociological and organizational impacts.
Conclusions:
- Constraint Programming provides a powerful and flexible tool for the NSP.
- Gymnaste demonstrates the practical viability of CP in real-world nurse scheduling.
- Further evaluation is ongoing to fully assess the system's benefits.