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A Comparison and Hybridization of Crossover Operators for the Nurse Scheduling Problem

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  • B. MAENHOUT

    ()

  • M. VANHOUCKE

    ()

Abstract

In this paper, we present a hybrid genetic algorithm for the well-known nurse scheduling problem (NSP). The NSP involves the construction of roster schedules for nursing staff in order to maximize the quality of the roster schedule and to minimize the violations of the minimal coverage requirements subject to various hard case-specific constraints. In literature, several genetic algorithms have been proposed in literature to solve the NSP under various assumptions. The contribution of this paper is twofold. First, we extensively compare the various crossover operators and test them on a standard dataset in a solitary approach. Second, we propose several options to hybridize the various crossover operators.

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File URL: http://www.feb.ugent.be/nl/Ondz/wp/Papers/wp_06_366.pdf
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Bibliographic Info

Paper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 06/366.

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Length: 20 pages
Date of creation: Jan 2006
Date of revision:
Handle: RePEc:rug:rugwps:06/366

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Keywords: meta-heuristics; hybridization; nurse scheduling;

This paper has been announced in the following NEP Reports:

References

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  1. Giovanni Felici & Claudio Gentile, 2004. "A Polyhedral Approach for the Staff Rostering Problem," Management Science, INFORMS, vol. 50(3), pages 381-393, March.
  2. Ernst, A. T. & Jiang, H. & Krishnamoorthy, M. & Sier, D., 2004. "Staff scheduling and rostering: A review of applications, methods and models," European Journal of Operational Research, Elsevier, vol. 153(1), pages 3-27, February.
  3. Cheang, B. & Li, H. & Lim, A. & Rodrigues, B., 2003. "Nurse rostering problems--a bibliographic survey," European Journal of Operational Research, Elsevier, vol. 151(3), pages 447-460, December.
  4. B. Maenhout & M. Vanhoucke, 2005. "New Computational Results for the Nurse Scheduling Problem: A Scatter Search Algorithm," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/341, Ghent University, Faculty of Economics and Business Administration.
  5. M. Vanhoucke & B. Maenhout, 2005. "Characterisation and Generation of Nurse Scheduling Problem Instances," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/339, Ghent University, Faculty of Economics and Business Administration.
  6. B. Maenhout & M. Vanhoucke, 2005. "An Electromagnetic Meta-Heuristic for the Nurse Scheduling Problem," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/316, Ghent University, Faculty of Economics and Business Administration.
  7. Gary M. Thompson, 1995. "Improved Implicit Optimal Modeling of the Labor Shift Scheduling Problem," Management Science, INFORMS, vol. 41(4), pages 595-607, April.
  8. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
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