A hybrid heuristic ordering and Variable Neighbourhood Search for the nurse rostering problem

Edmund Burke; Timothy Curtois; P. De Causmaecker; Gerhard F. Post; G. van den Berghe

A hybrid heuristic ordering and Variable Neighbourhood Search for the nurse rostering problem

Edmund Burke, Timothy Curtois, P. De Causmaecker, Gerhard F. Post, G. van den Berghe

Discrete Mathematics and Mathematical Programming

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

This paper is concerned with the development of intelligent decision support methodologies for nurse rostering problems in large modern hospital environments. We present an approach which hybridises heuristic ordering with variable neighbourhood search. We show that the search can be extended and the solution quality can be significantly improved by the careful combination and repeated use of heuristic ordering, variable neighbourhood search and backtracking. The amount of computational time that is allowed plays a significant role and we analyse and discuss this. The algorithms are evaluated against a commercial Genetic Algorithm on commercial data. We demonstrate that this methodology can significantly outperform the commercial algorithm. This paper is one of the few in the scientific nurse rostering literature which deal with commercial data and which compare against a commercially implemented algorithms.

Original language	Undefined
Title of host publication	Proceedings of The 5th international conference on the Practice and Theory of Automated Timetabling
Editors	M.A. Trick, E.K. Burke
Pages	445-446
Number of pages	2
Publication status	Published - 18 Aug 2004
Event	5th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2004 - Pittsburgh, United States Duration: 18 Aug 2004 → 20 Aug 2004 Conference number: 5 http://patatconference.org/patat2004/

Conference

Conference	5th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2004
Abbreviated title	PATAT 2004
Country/Territory	United States
City	Pittsburgh
Period	18/08/04 → 20/08/04
Internet address	http://patatconference.org/patat2004/

Keywords

METIS-219906
IR-48446

Access to Document

burke04hybrid

Cite this

@inproceedings{f6f2473cc502404da1c3a89d711490b6,

title = "A hybrid heuristic ordering and Variable Neighbourhood Search for the nurse rostering problem",

abstract = "This paper is concerned with the development of intelligent decision support methodologies for nurse rostering problems in large modern hospital environments. We present an approach which hybridises heuristic ordering with variable neighbourhood search. We show that the search can be extended and the solution quality can be significantly improved by the careful combination and repeated use of heuristic ordering, variable neighbourhood search and backtracking. The amount of computational time that is allowed plays a significant role and we analyse and discuss this. The algorithms are evaluated against a commercial Genetic Algorithm on commercial data. We demonstrate that this methodology can significantly outperform the commercial algorithm. This paper is one of the few in the scientific nurse rostering literature which deal with commercial data and which compare against a commercially implemented algorithms.",

keywords = "METIS-219906, IR-48446",

author = "Edmund Burke and Timothy Curtois and {De Causmaecker}, P. and Post, {Gerhard F.} and {van den Berghe}, G.",

year = "2004",

month = aug,

day = "18",

language = "Undefined",

isbn = "0-88748-413-1",

pages = "445--446",

editor = "M.A. Trick and E.K. Burke",

booktitle = "Proceedings of The 5th international conference on the Practice and Theory of Automated Timetabling",

note = "5th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2004 ; Conference date: 18-08-2004 Through 20-08-2004",

url = "http://patatconference.org/patat2004/",

}

Burke, E, Curtois, T, De Causmaecker, P, Post, GF & van den Berghe, G 2004, A hybrid heuristic ordering and Variable Neighbourhood Search for the nurse rostering problem. in MA Trick & EK Burke (eds), Proceedings of The 5th international conference on the Practice and Theory of Automated Timetabling. pp. 445-446, 5th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2004, Pittsburgh, Pennsylvania, United States, 18/08/04.

A hybrid heuristic ordering and Variable Neighbourhood Search for the nurse rostering problem. / Burke, Edmund; Curtois, Timothy; De Causmaecker, P. et al.
Proceedings of The 5th international conference on the Practice and Theory of Automated Timetabling. ed. / M.A. Trick; E.K. Burke. 2004. p. 445-446.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - A hybrid heuristic ordering and Variable Neighbourhood Search for the nurse rostering problem

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AU - De Causmaecker, P.

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N2 - This paper is concerned with the development of intelligent decision support methodologies for nurse rostering problems in large modern hospital environments. We present an approach which hybridises heuristic ordering with variable neighbourhood search. We show that the search can be extended and the solution quality can be significantly improved by the careful combination and repeated use of heuristic ordering, variable neighbourhood search and backtracking. The amount of computational time that is allowed plays a significant role and we analyse and discuss this. The algorithms are evaluated against a commercial Genetic Algorithm on commercial data. We demonstrate that this methodology can significantly outperform the commercial algorithm. This paper is one of the few in the scientific nurse rostering literature which deal with commercial data and which compare against a commercially implemented algorithms.

AB - This paper is concerned with the development of intelligent decision support methodologies for nurse rostering problems in large modern hospital environments. We present an approach which hybridises heuristic ordering with variable neighbourhood search. We show that the search can be extended and the solution quality can be significantly improved by the careful combination and repeated use of heuristic ordering, variable neighbourhood search and backtracking. The amount of computational time that is allowed plays a significant role and we analyse and discuss this. The algorithms are evaluated against a commercial Genetic Algorithm on commercial data. We demonstrate that this methodology can significantly outperform the commercial algorithm. This paper is one of the few in the scientific nurse rostering literature which deal with commercial data and which compare against a commercially implemented algorithms.

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