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Integer programming model extensions for a multi-stage nurse rostering problem.

Florian Mischek1, Nysret Musliu1

  • 1Database and Artificial Intelligence Group, Vienna University of Technology, Vienna, Austria.

Annals of Operations Research
|March 19, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces an integer programming model for a complex nurse rostering problem. The enhanced model with new constraints significantly improves solution quality, achieving competitive results.

Keywords:
INRC-IIInteger programmingNurse rostering

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Area of Science:

  • Operations Research
  • Computer Science
  • Healthcare Management

Background:

  • The nurse rostering problem is a well-studied combinatorial optimization challenge.
  • A specific variant involves sequentially dependent stages, increasing complexity.
  • Previous solutions from the Second International Nurse Rostering Competition provide a benchmark.

Purpose of the Study:

  • To develop an integer programming model for a complex nurse rostering problem variant.
  • To introduce novel constraints to handle incomplete information in nurse scheduling.
  • To evaluate the effectiveness of the extended model against competition results.

Main Methods:

  • Formulation of an integer programming (IP) model.
  • Development of additional constraints to address information gaps.
  • Comparison of the IP model's solutions with those from the Second International Nurse Rostering Competition.

Main Results:

  • The proposed integer programming model effectively addresses the multi-stage nurse rostering problem.
  • The extended model, incorporating new constraints, significantly enhances solution quality.
  • The developed approach yields results competitive with top-performing solutions from the competition.

Conclusions:

  • Integer programming provides a viable method for solving complex nurse rostering problems.
  • Handling incomplete information through extended constraints is crucial for improving scheduling outcomes.
  • The proposed model offers a competitive alternative for nurse scheduling optimization.