Abstract
Nurse rostering is an attractive research domain due to its societal relevance, while academics are intrigued by its combinatorial complexity. Descriptions of nurse rostering problems vary largely across the literature, which makes it almost impossible to track down scientific advances of models and corresponding approaches. The present chapter introduces a mathematical formulation of a generic nurse rostering model. It provides common elements present in most nurse rostering research as well as important hospital constraints that are usually omitted from academic models. The new mathematical model satisfies all the basic requirements for future nurse rostering research and practical developments. Finally, the importance of public datasets is discussed, together with the characteristics of the various benchmark instances and research results obtained working on these instances.
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References
Abernathy, W.J., Baloff, N., Hershey, J.C., Wandel, S.: A three-stage manpower planning and scheduling model - a service-sector example. Operations Research 22, 693–711 (1973)
Awadallah, M.A., Khader, A.T., Al-Betar, M.A., Bolaji, A.L.: Nurse rostering using modified harmony search algorithm. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds.) SEMCCO 2011, Part II. LNCS, vol. 7077, pp. 27–37. Springer, Heidelberg (2011)
Bilgin, B.: Advanced Models and Solution Methods for Automation of Personnel Rostering Optimisation. PhD thesis, KU Leuven (2012)
Bilgin, B., Demeester, P., Misir, M., Vancroonenburg, W., Vanden Berghe, G., Wauters, T.: A hyper-heuristic combined with a greedy shuffle approach to the nurse rostering competition. In: Proceedings of PATAT 2010 (2010)
Bilgin, B., De Causmaecker, P., Rossie, B., Vanden Berghe, G.: Local search neighbourhoods for dealing with a novel nurse rostering model. Annals of Operations Research 194, 33–57 (2012)
Brucker, P., Burke, E.K., Curtois, T., Qu, R., Vanden Berghe, G.: A shift sequence based approach for nurse scheduling and a new benchmark dataset. Journal of Heuristics 16(4), 559–573 (2010)
Burke, E.K., Curtois, T.: New computational results for nurse rostering benchmark instances. Technical report (2011)
Burke, E.K., Cowling, P., De Causmaecker, P., Vanden Berghe, G.: A memetic approach to the nurse rostering problem. Applied Intelligence, Special Issue on Simulated Evolution and Learning 15, 199–214 (2001)
Burke, E.K., Kendall, G., Newall, J., Hart, E., Ross, P., Schulenburg, S.: Hyper-heuristics: An emerging direction in modern search technology. In: Glover, F., Kochenberger, G. (eds.) Handbook of Metaheuristics, vol. 57, pp. 457–474. Springer, New York (2003)
Burke, E.K., De Causmaecker, P., Vanden Berghe, G., Van Landeghem, H.: The state of the art of nurse rostering. Journal of Scheduling 7(6), 441–499 (2004)
Burke, E.K., Curtois, T., Qu, R., Vanden Berghe, G.: A scatter search methodology for the nurse rostering problem. Journal of the Operational Research Society 61(11), 1667–1679 (2010a)
Burke, E.K., Hyde, M., Kendall, G., Ochoa, G., Özcan, E., Woodward, J.R.: A classification of hyper-heuristics approaches. In: Gendreau, M., Potvin, J.-Y. (eds.) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol. 146, pp. 449–468. Springer (2010b)
Burke, E.K., Curtois, T., Fijn Van Draat, L., Van Ommeren, J.-K., Post, G.: Progress control in iterated local search for nurse rostering. Journal of the Operational Research Society 62(2), 360–367 (2011)
Curtois, T.: Employee scheduling benchmark data sets (2012), http://www.cs.nott.ac.uk/~tec/NRP/
Abernathy, W.J., Baloff, N., Hershey, J.C., Wandel, S.: A three-stage manpower planning and scheduling model - a service-sector example. Operations Research 22, 693–711 (1973)
Della Croce, F., Salassa, F.: A variable neighborhood search based matheuristic for nurse rostering problems. Annals of Operations Research (to appear)
Geiger, M.J.: Personnel rostering by means of variable neighborhood search. In: Hu, B., Morasch, K., Pickl, S., Siegle, M. (eds.) Operations Research Proceedings 2010, pp. 219–224. Springer, Heidelberg (2000) ISBN 978-3-642-20009-0
Glass, C.A., Knight, R.A.: The nurse rostering problem: A critical appraisal of the problem structure. European Journal of Operational Research 202(2), 379–389 (2010)
Haspeslagh, S., De Causmaecker, P., Schaerf, A., Stolevik, M.: The first international nurse rostering competition 2010. Annals of Operations Research, 1–16 (2012)
Kellogg, D.L., Walczak, S.: Nurse scheduling: From academia to implementation or not? Interfaces 37(4), 355–369 (2007)
Lü, Z., Hao, J.-K.: Adaptive neighborhood search for nurse rostering. European Journal of Operational Research 218(3), 865–876 (2012) ISSN 0377-2217
Maenhout, B., Vanhoucke, M.: New computational results for the nurse scheduling problem: A scatter search algorithm. In: Gottlieb, J., Raidl, G.R. (eds.) EvoCOP 2006. LNCS, vol. 3906, pp. 159–170. Springer, Heidelberg (2006)
Maenhout, B., Vanhoucke, M.: An electromagnetic meta-heuristic for the nurse scheduling problem. Journal of Heuristics 13, 359–385 (2007) ISSN 1381-1231
Maenhout, B., Vanhoucke, M.: Comparison and hybridization of crossover operators for the nurse scheduling problem. Annals of Operations Research 159, 333–353 (2008) ISSN 0254-5330
Maenhout, B., Vanhoucke, M.: Branching strategies in a branch-and-price approach for a multiple objective nurse scheduling problem. Journal of Scheduling 13, 77–93 (2010) ISSN 1094-6136
Messelis, T., De Causmaecker, P.: An algorithm selection approach for nurse rostering. In: Proceedings of the 23rd Benelux Conference on Artificial Intelligence, pp. 160–166 (2011)
Misir, M., Verbeeck, K., De Causmaecker, P., Vanden Berghe, G.: Design and analysis of an evolutionary selection hyper-heuristic. Technical report, KAHO Sint-Lieven (2012)
Nonobe, K.: An approach using a general constraint optimization solve. In: Proceedings of PATAT 2010 (2010)
Rocha, M., Oliveira, J.F., Carravilla, M.A.: Cyclic staff scheduling: optimization models for some real-life problems. Journal of Scheduling 16(2), 231–242
Smet, P., Martin, S., Ouelhadj, D., Özcan, E., Vanden Berghe, G.: Investigation of fairness measures for nurse rostering. In: Kjenstad, D., Riise, A., Norlander, T.E., McColumn, B., Burke, E.K. (eds.) Proceedings of the 9th International Conference on the Practice and Theory of Automated Timetabling, PATAT, Son, Norway, pp. 369–372 (August 2012)
Smet, P., Bilgin, B., De Causmaecker, P., Vanden Berghe, G.: Modelling and evaluation issues in nurse rostering. Annals of Operations Research (to appear), doi:10.1007/s10479-012-1116-3
Valouxis, C., Housos, E.: Hybrid optimisation techniques for the workshift and rest assignment of nursing personnel. Artificial Intelligence in Medicine 20, 155–175 (2000)
Valouxis, C., Gogos, C., Goulas, G., Alefragis, P., Housos, E.: A systematic two phase approach for the nurse rostering problem. European Journal of Operational Research (2012) ISSN 0377-2217, doi:10.1016/j.ejor.2011.12.042
Vanhoucke, M., Maenhout, B.: NSPLib - a tool to evaluate (meta-) heuristic procedures. In: Brailsford, S., Harper, P. (eds.) Operational Research for Health Policy: Making Better Decisions, Proceedings of the 31st Meeting of the European Working Group on Operational Research Applied to Health Services, pp. 151–165 (2007)
Warner, M.: Nurse staffing, scheduling, and reallocation in the hospital. In: Hospital & Health Services Administration, 77–90 (1976)
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Smet, P., De Causmaecker, P., Bilgin, B., Berghe, G.V. (2013). Nurse Rostering: A Complex Example of Personnel Scheduling with Perspectives. In: Uyar, A., Ozcan, E., Urquhart, N. (eds) Automated Scheduling and Planning. Studies in Computational Intelligence, vol 505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39304-4_6
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