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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Vydáno v:	European journal of operational research Ročník 203; číslo 2; s. 484 - 493
Hlavní autoři:	Burke, Edmund K., Li, Jingpeng, Qu, Rong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 01.06.2010 Elsevier Elsevier Sequoia S.A
Edice:	European Journal of Operational Research
Témata:	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
ISSN:	0377-2217, 1872-6860
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Abstract	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.
AbstractList	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. 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. [PUBLICATION ABSTRACT]
Author	Qu, Rong Burke, Edmund K. Li, Jingpeng
Author_xml	– sequence: 1 givenname: Edmund K. surname: Burke fullname: Burke, Edmund K. email: ekb@cs.nott.ac.uk – sequence: 2 givenname: Jingpeng surname: Li fullname: Li, Jingpeng email: jpl@cs.nott.ac.uk – sequence: 3 givenname: Rong surname: Qu fullname: Qu, Rong email: rxq@cs.nott.ac.uk
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Snippet	This paper presents a hybrid multi-objective model that combines integer programming (IP) and variable neighbourhood search (VNS) to deal with...
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SubjectTerms	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
Title	A hybrid model of integer programming and variable neighbourhood search for highly-constrained nurse rostering problems
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