A categorisation of nurse rostering problems

• Aickelin, U., & Li, J. (2007). An estimation of distribution algorithm for nurse scheduling. Annals of Operations Research, 155(1), 289–309.

  Article  Google Scholar 

• Aickelin, U., Burke, E. K., & Li, J. (2007). An estimation of distribution algorithm with intelligent local search for rule-based nurse rostering. Journal of the Operational Research Society, 58(12), 1574–1585.

  Article  Google Scholar 

• Azaiez, M. N., & Al-Sharif, S. S. (2005). A 0-1 goal programming model for nurse scheduling. Computers and Operations Research, 32(3), 507–491.

  Article  Google Scholar 

• Bard, J. F., & Purnomo, H. W. (2005a). A column generation-based approach to solve the preference scheduling problem for nurses with downgrading. Socio-Economic Planning Sciences, 39, 139–213.

  Article  Google Scholar 

• Bard, J. F., & Purnomo, H. W. (2005b). Preference scheduling for nurses using column generation. European Journal of Operational Research, 164, 510–534.

  Article  Google Scholar 

• Bard, J. F., & Purnomo, H. W. (2005c). Hospital-wide reactive scheduling of nurses with preference considerations. IIE Transactions, 37, 589–608.

  Article  Google Scholar 

• Bard, J. F., & Purnomo, H. W. (2006). Incremental changes in the workforce to accommodate changes in demand. Health Care Management Science, 9, 71–85.

  Article  Google Scholar 

• Bard, J. F., & Purnomo, H. W. (2007). Cyclic preference scheduling of nurses using a Lagrangian-based heuristic. Journal of Scheduling, 10(1), 5–23.

  Article  Google Scholar 

• Beddoe, G. R., & Petrovic, S. (2006). Selecting and weighting features using a genetic algorithm in a case-based reasoning approach to personnel rostering. European Journal of Operational Research, 10(1), 649–671.

  Article  Google Scholar 

• Beddoe, G. R., & Petrovic, S. (2007). Enhancing case-based reasoning for personnel rostering with selected tabu search concepts. Journal of the Operational Research Society, 58(12), 1586–1598.

  Article  Google Scholar 

• Beddoe, G., Petrovic, S., & Li, J. (2009). A hybrid metaheuristic case-based reasoning system for nurse rostering. Journal of Scheduling, 12(2), 99–119.

  Article  Google Scholar 

• Bellanti, F., Carello, G., Della Croce, F., & Tadei, R. (2004). A greedy-based neighbourhood search approach to a nurse rostering problem. European Journal of Operational Research, 153(1), 28–40.

  Article  Google Scholar 

• Bester, M. J., Nieuwoudt, I., & Van Vuuren, J. H. (2007). Finding good nurse duty schedules: a case study. Journal of Scheduling, 10, 387–405.

  Article  Google Scholar 

• Bilgin, B., De Causmaecker, P., Rossie, B., & Vanden Berghe, G. (2011). Local search neighbourhoods for dealing with a novel nurse rostering model. Annals of Operations Research, accepted.

• Bilgin, B., De Causmaecker, P., Rossie, B., & Vanden Berghe, G. (2008). Local search neighbourhoods to deal with a novel nurse rostering model. In Proceedings of the 7th international conference on practice and theory of automated timetabling, Montreal, August 2008.

  Google Scholar 

• Bourdais, S., Galinier, Ph., & Pesant, G. (2003). Hibiscus: A constraint programming application to staff scheduling in health care. In Lecture notes in computer science. CP 2003 (Vol. 2833, pp. 153–167).

• Brucker, P. (2004). Scheduling algorithms (4th ed.). Berlin: Springer.

  Google Scholar 

• Brucker, P., Drexl, A., Möhring, R., Neumann, K., & Pesch, E. (1999). Resource-constrained project scheduling: Notation, classification, models, and methods. European Journal of Operational Research 112, 3–41.

  Article  Google Scholar 

• Brucker, P., Burke, E. K., Curtois, T., Qu, R., & Vanden Berghe, G. (2010). Adaptive construction of nurse schedules: A shift sequence based approach. Journal of Heuristics 16(4), 559–573.

  Article  Google Scholar 

• Burke, E. K., Cowling, P., De Causmaecker, P., & Vanden Berghe, G. (2001a). A memetic approach to the nurse rostering problem. Applied Intelligence, 15, 199–214. Special issue on simulated evolution and learning.

  Article  Google Scholar 

• Burke, E. K., De Causmaecker, P., Petrovic, S., & Vanden Berghe, G. (2001b). Fitness evaluation for nurse scheduling problems. In Proceedings of the congress on evolutionary computation (CEC2001) (pp. 1139–1146), Seoul, Korea, May 27–30, 2001. New York: IEEE Press.

  Google Scholar 

• Burke, E. K., De Causmaecker, P., Vanden Berghe, G., & Van Landeghem, H. (2004). The state of the art of nurse rostering. Journal of Scheduling, 7(6), 441–499.

  Article  Google Scholar 

• Burke, E. K., De Causmaecker, P., Petrovic, S., & Vanden Berghe, G. (2006). Metaheuristics for handling time interval coverage constraints in nurse scheduling. Applied Artificial Intelligence, 20(9), 743–766.

  Article  Google Scholar 

• Burke, E. K., Curtois, T., Qu, R., & Vanden Berghe, G. (2007). A time pre-defined variable depth search for nurse rostering (Technical report). University of Nottingham.

• Burke, E. K., Curtois, T., Post, G., Qu, R., & Veltman, B. (2008). A hybrid heuristic ordering and variable neighbourhood search for the nurse rostering problem. European Journal of Operational Research, 188, 330–341.

  Article  Google Scholar 

• Burke, E. K., Curtois, T., Qu, R., & Vanden Berghe, G. (2010). A scatter search approach for the nurse rostering problem. Journal of the Operational Research Society, 61, 1667–1679.

  Article  Google Scholar 

• Chiarandini, M., Schaerf, A., & Tiozzo, F. (2000). Solving employee timetabling problems with flexible workload using tabu search. In E. K. Burke & W. Erben (Eds.), Proceedings of the 3th international conference on the practice and theory of automated timetabling, PATAT (pp. 298–302). Konstanz, Germany, August 2000.

  Google Scholar 

• Chun, A. H. W., Chan, S. H. C., Lam, G. P. S., Tsang, F. M. P., Wong, J., & Yeung, D. W. M. (2000). Nurse rostering at the hospital authority of Hong Kong. In Proceedings of the 17th national conference on AAAI and 12th conference on IAAI (pp. 951–956).

  Google Scholar 

• De Causmaecker, P. (2008). Towards a reference model for timetabling and rostering. In E. K. Burke & M. Gendreau (Eds.), The practice and theory of automated timetabling, proceedings of the 5th international conference, Montreal, August 2008.

  Google Scholar 

• De Causmaecker, P., & Vanden Berghe, G. (2003). Relaxation of coverage constraints in hospital personnel rostering. In E. K. Burke & P. De Causmaecker (Eds.), Lecture notes in computer science: Vol. 2740. Practice and theory of automated timetabling (pp. 129–147). Berlin: Springer.

  Chapter  Google Scholar 

• De Causmaecker P., & Vanden Berghe G. (2011). Towards a reference model for timetabling and rostering. Annals of Operations Research, accepted.

• Dias, T. M., Ferber, D. F., de Sousa, C. C., & Moura, A. V. (2003). Constructing nurse schedules at large hospitals. International Transactions in Operational Research 10, 245–265.

  Article  Google Scholar 

• Duenas, A., Mort, N., Reeves, C., & Petrovic, D. (2003). Handling preferences using genetic algorithms for the nurse scheduling problem. In G. Kendall, E.K. Burke, & S. Petrovic (Eds.), Proceedings of the 1st multidisciplinary international conference on scheduling: Theory and applications (MISTA) Nottingham, UK (pp. 180–196).

  Google Scholar 

• Dyckhoff, H. (1990). A typology of cutting and packing problems. European Journal of Operational Research, 44, 145–159.

  Article  Google Scholar 

• Graham, R. L., Lawler, E. L., Lenstra, J. K., & Rinnooy Kan, A. H. G. (1979). Optimization and approximation in deterministic sequencing and scheduling: a survey. Annals of Discrete Mathematics, 4, 287–326.

  Article  Google Scholar 

• Gutjahr, W. J., & Rauner, M. S. (2007). An ACO algorithm for a dynamic regional nurse-scheduling problem in Austria. Computers & Operations Research, 34(3), 642–666.

  Article  Google Scholar 

• Herroelen, W., Demeulemeester, E., & De Reyck, B. (1999). A classification scheme for project scheduling. International series in operations research and management science: Vol. 14 (pp. 77–106). Project scheduling—recent models, algorithms and applications. Kluwer Academic Publishers.

• Lawler, E. L., Lenstra, J. K., Rinnooy Kan, A. H. G., & Shmoys, D. B. (1993). Handbook in operations research and management science. Vol. 4. Amsterdam: North Holland.

  Google Scholar 

• Lodree, E. J. Jr., Geiger, C. D., & Jiang, X. (2009). Taxonomy for integrating scheduling theory and human factors: Review and research opportunities. International Journal of Industrial Ergonomics, 39(1), 39–51.

  Article  Google Scholar 

• Maenhout, B., & Vanhoucke, M. (2008). Comparison and hybridization of crossover operators for the nurse scheduling problem. Annals of Operations Research, 159(1), 333–353.

  Article  Google Scholar 

• Messelis, T., Haspeslagh, S., Bilgin, B., De Causmaecker, P., & Vanden Berghe, G. (2009). Towards prediction of algorithm performance in real world optimisation problems. In Proceedings of the 21st Benelux conference on artificial intelligence (Vol. 21, pp. 177–183), BNAIC. Eindhoven, October 2009.

  Google Scholar 

• Moz, M., & Pato, M. V. (2007). A genetic algorithm approach to a nurse rerostering problem. Computers & Operations Research, 34(3), 667–691.

  Article  Google Scholar 

• Osogami, T., & Imai, H. Classification of various neighborhood operations for the nurse scheduling problem (Technical Report 135). The Institute of Statistical Mathematics.

• Ozcan, E. (2005). Memetic algorithms for nurse rostering. In Lecture notes in computer science: Vol. 3733. Computer and information sciences—Proceedings ISCIS (pp. 482–492).

  Chapter  Google Scholar 

• Parr, D., & Thompson, J. M. (2007). Solving the multi-objective nurse scheduling problem with a weighted cost function. Annals of Operations Research, 155(1), 279–288. Special issue on personnel scheduling and planning.

  Article  Google Scholar 

• Pinedo, M. (2002). Scheduling, theory, algorithms, and systems (2nd ed.). New York: Prentice Hall.

  Google Scholar 

• Siferd, S. P. & Benton, W.C. (1992). Workforce staffing and scheduling: Hospital nursing specific models. European Journal of Operational Research, 60, 233–246.

  Article  Google Scholar 

• Topaloglu, S. & Selim, H. (2007). Nurse scheduling using fuzzy multiple objective programming. In H. G. Okuno & M. Ali (Eds.), Lecture notes in artificial intelligence: Vol. 4570. IEA/AIE 2007 (pp. 54–63). Berlin: Springer.

  Google Scholar 

• Vanhoucke, M., & Maenhout, B. (2007). NSPLib—a nurse scheduling problem library: a tool to evaluate (meta-)heuristic procedures. In S. Brailsford & P. Harper (Eds.), Operational research for health policy: making better decisions, proceedings of the 31st annual meeting of the working group on operations research applied to health services (pp. 151–165).

  Google Scholar 

• Vanhoucke, M., & Maenhout, B. (2009). On the characterisation and generation of nurse scheduling problem instances. European Journal of Operational Research, 196(2), 457–467.

  Article  Google Scholar 

• Wäscher, G., Haussner, H., & Schumann, H. (2007). An improved typology of cutting and packing problems. European Journal of Operational Research, 183, 1109–1130.

  Article  Google Scholar 

• Wong, G. Y. C. & Chun A.H.W. (2004). Constraint-based rostering using meta-level reasoning and probability-based ordering. Engineering Applications of Artificial Intelligence, 17(6), 599–610.

  Article  Google Scholar 

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