Abstract
Nurse rostering is the process of creating a plan for nurse working hours over a given time horizon. This problem, most variants of which are NP-hard, has been studied extensively for many years. Still, practical nurse rostering is mostly done manually, often by highly qualified health care personnel. This underlines the need to address the challenges of realistic, applied nurse rostering, and the implementation of advanced rostering methods in commercial software.
In this paper, we present an industrial case study of a nurse rostering software currently used in several hospitals and other health care institutions in Norway and Sweden. The presented problem model has a rich set of hard and soft constraints, as required by Norwegian hospitals. Our solution approach is a hybrid: An Iterated Local Search framework that uses Constraint Programming for initial solution construction and diversification, and a Variable Neighborhood Descent for iterative improvement. The search method shows good results in terms of solution quality and computation time on a set of real world instances. We make these test instances available on-line.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Abdennadher, S., Schlenker, H.: Nurse scheduling using constraint logic programming. In: Proceedings of the Sixteenth National Conference on Artificial Intelligence and the Eleventh Innovative Applications of Artificial Intelligence Conference Innovative Applications of Artificial Intelligence, AAAI 1999/IAAI 1999, pp. 838–843. American Association for Artificial Intelligence, Menlo Park (1999)
Meyer, H., Meyer auf’m Hofe, H.: Conplan/siedaplan: Personnel assignment as a problem of hierarchical constraint satisfaction. In: Proceedings on the 3rd International Conference on Practical Applications of Constraint Technologies, pp. 257–272. Practical Application Company Ltd. (1997)
Beaumont, N.: Scheduling staff using mixed integer programming. European Journal of Operational Research 98(3), 473–484 (1997)
Borning, A., Freeman-Benson, B., Wilson, M.: Constraint hierarchies. LISP and Symbolic Computation 5(3), 223–270 (1992), 10.1007/BF01807506
Brusco, M.J., Jacobs, L.W.: Cost analysis of alternative formulations for personnel scheduling in continuously operating organizations. European Journal of Operational Research 86(2), 249–261 (1995)
Burke, E.K., De Causmaecker, P., Berghe, G.V.: A hybrid tabu search algorithm for the nurse rostering problem. In: McKay, B., Yao, X., Newton, C.S., Kim, J.-H., Furuhashi, T. (eds.) SEAL 1998. LNCS (LNAI), vol. 1585, pp. 187–194. Springer, Heidelberg (1999)
Burke, E.K., Curtois, T., Post, G., Qu, R., Veltman, B.: A hybrid heuristic ordering and variable neighbourhood search for the nurse rostering problem. European Journal of Operational Research 188(2), 330–341 (2008)
Burke, E.K., De Causmaecker, P., Berghe, G.V., Van Landeghem, H.: The state of the art of nurse rostering. Journal of Scheduling 7(6), 441–499 (2004)
Burke, E.K., Li, J., Qu, R.: A hybrid model of integer programming and variable neighbourhood search for highly-constrained nurse rostering problems. European Journal of Operational Research 203(2), 484–493 (2010)
Carchrae, T., Beck, J.C.: Cost-based large neighborhood search. In: Workshop on Combination of Metaheuristic and Local Search with Constraint Programming Techniques, pp. 28–29 (2005)
Chen, J.-G., Yeung, T.: Hybrid expert system approach to nurse scheduling. Computers in Nursing, 183–192 (1993)
Dowsland, K.A.: Nurse scheduling with tabu search and strategic oscillation. European Journal of Operational Research 106(2-3), 393–407 (1998)
Hansen, P., Mladenovic, N.: Variable neighborhood search. In: Burke, E.K., Kendall, G. (eds.) Search Methodologies - Introductory Tutorials in Optimization and Decision Support Techniques, pp. 211–238. Springer, Heidelberg (2005)
Hattori, H., Ito, T., Ozono, T., Shintani, T.: A nurse scheduling system based on dynamic constraint satisfaction problem. In: Ali, M., Esposito, F. (eds.) IEA/AIE 2005. LNCS (LNAI), vol. 3533, pp. 799–808. Springer, Heidelberg (2005)
He, F., Qu, R.: A constraint-directed local search approach to nurse rostering problems. In: Deville, Y., Solnon, C. (eds.) Proceedings 6th International Workshop on Local Search Techniques in Constraint Satisfaction, pp. 69–80 (2009)
Hoos, H.H., Stützle, T.: Stochastic Local Search: Foundations & Applications. Morgan Kaufmann Publishers Inc., San Francisco (2004)
Karp, R.M.: Reducibility among combinatorial problems. In: Miller, R.E., Thatcher, J.W. (eds.) Complexity of Computer Computations, pp. 85–103. Plenum Press, New York (1972)
Kellogg, D.L., Walczak, S.: Nurse Scheduling: From Academia to Implementation or Not? INTERFACES 37(4), 355–369 (2007)
Li, H., Lim, A., Rodrigues, B.: A hybrid ai approach for nurse rostering problem. In: Proceedings of the 2003 ACM Symposium on Applied Computing, SAC 2003, pp. 730–735. ACM, New York (2003)
Lourenço, H.R., Martin, O.C., Stützle, T.: Iterated Local Search, pp. 321–353. Kluwer Academic Publishers, Dordrecht (2003)
Meisels, A., Schaerf, A.: Modelling and solving employee timetabling problems. Annals of Mathematics and Artificial Intelligence 39(1), 41–59 (2003)
Heus, K., Chan, G.W.P.: Nurse scheduling with global constraints in chip: Gymnaste. In: Practical Applications of Constraint Technology, PACT (1998)
Post, G., Veltman, B.: Harmonious personnel scheduling. In: Burke, E.K., Trick, M.A. (eds.) PATAT 2004. LNCS, vol. 3616, pp. 557–559. Springer, Heidelberg (2005)
Schrimpf, G., Schneider, J., Stamm-Wilbrandt, H., Dueck, G.: Record breaking optimization results using the ruin and recreate principle. Journal of Computational Physics 159(2), 139–171 (2000)
Stølevik, M., Nordlander, T.E., Riise, A.: SINTEF ICT: Nurse rostering data (2010), http://www.comihc.org/index.php/Test-Beds/sintef-ict-nurse-rostering-data.html (accessed October 13, 2010)
Stølevik, M., Nordlander, T.E., Riise, A.: A mathematical model for the nurse rostering problem. SINTEF Technical Report A19133 (2011), http://www.comihc.org/index.php/Models/sintef-ict-nurse-rostering-model.html (accessed April 08, 2011)
Tsang, E., Voudouris, C.: Fast local search and guided local search and their application to british telecom’s workforce scheduling problem. Operations Research Letters 20(3), 119–127 (1997)
Valouxis, C., Housos, E.: Hybrid optimization techniques for the workshift and rest assignment of nursing personnel. Artificial Intelligence in Medicine 20(2), 155–175 (2000); Planning and Scheduling in the Hospital
Wong, G.Y.C., Chun, H.W.: Nurse rostering using constraint programming and meta-level reasoning. In: Chung, P.W.H., Hinde, C.J., Ali, M. (eds.) IEA/AIE 2003. LNCS, vol. 2718, pp. 712–721. Springer, Heidelberg (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Stølevik, M., Nordlander, T.E., Riise, A., Frøyseth, H. (2011). A Hybrid Approach for Solving Real-World Nurse Rostering Problems. In: Lee, J. (eds) Principles and Practice of Constraint Programming – CP 2011. CP 2011. Lecture Notes in Computer Science, vol 6876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23786-7_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-23786-7_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23785-0
Online ISBN: 978-3-642-23786-7
eBook Packages: Computer ScienceComputer Science (R0)