A hybrid model of integer programming and variable neighbourhood search for highly-constrained nurse rostering problems

This paper presents a hybrid multi-objective model that combines integer programming (IP) and variable neighbourhood search (VNS) to deal with highly-constrained nurse rostering problems in modern hospital environments. An IP is first used to solve the subproblem which includes the full set of hard...

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Bibliographic Details
Published inEuropean journal of operational research Vol. 203; no. 2; pp. 484 - 493
Main Authors Burke, Edmund K., Li, Jingpeng, Qu, Rong
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.06.2010
Elsevier
Elsevier Sequoia S.A
SeriesEuropean Journal of Operational Research
Subjects
Applied sciences
Comparative analysis
Decision theory. Utility theory
Exact sciences and technology
Genetic algorithms
Integer programming
Mathematical models
Multi-objective optimization
Nurse rostering
Nurse rostering Multi-objective optimization Integer programming Variable neighbourhood search
Operational research and scientific management
Operational research. Management science
Resource allocation
Studies
Variable neighbourhood search
Netherlands
Integer programming
Nurse rostering
Multi-objective optimization
Variable neighbourhood search
Resource allocation
Multiobjective programming
Beat
Set constraint
Modeling
Optimization
Neighborhood search
Genetic algorithm
Hybrid model
Hospital
Nurse
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Summary:This paper presents a hybrid multi-objective model that combines integer programming (IP) and variable neighbourhood search (VNS) to deal with highly-constrained nurse rostering problems in modern hospital environments. An IP is first used to solve the subproblem which includes the full set of hard constraints and a subset of soft constrains. A basic VNS then follows as a postprocessing procedure to further improve the IP’s resulting solutions. The satisfaction of the excluded constraints from the preceding IP model is the major focus of the VNS. Very promising results are reported compared with a commercial genetic algorithm and a hybrid VNS approach on real instances arising in a Dutch hospital. The comparison results demonstrate that our hybrid approach combines the advantages of both the IP and the VNS to beat other approaches in solving this type of problems. We also believe that the proposed methodology can be applied to other resource allocation problems with a large number of constraints.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2009.07.036