A variable neighborhood search based matheuristic for nurse rostering problems

Annals of Operations Research

Volumn 218, Issue 1, 2014, Pages 185-199

  Della Croce, Federico ^a   Salassa, Fabio ^a  

^a POLITECNICO DI TORINO   (Italy)

Author keywords

Matheuristics; Nurse rostering problem; Timetabling; Variable neighborhood search

Indexed keywords

EID: 84904211195     PISSN: 02545330     EISSN: 15729338     Source Type: Journal    
DOI: 10.1007/s10479-012-1235-x     Document Type: Article

References (21)

1. Bellanti, F., Carello, G., Della Croce, F., & Tadei, R. (2004). A greedy-based neighborhood search approach to a nurse rostering problem. European Journal of Operational Research, 153, 28-40.
2. Burke, E. K., De Causmaecker, P., Petrovic, S., & Vanden Berghe, G. (2004a). Variable neighborhood search for nurse rostering problems. In Applied optimization: Vol. 86. Metaheuristics: computer decision-making (pp. 153-172). Norwell: Kluwer Academic.
3. Burke, E. K., De Causmaecker, P., Vanden Berghe, G., & van Landeghem, H. (2004b). The state of the art of nurse rostering. Journal of Scheduling, 7, 441-499.
4. Burke, E. K., Curtois, T., Qu, R., & Vanden Berghe, G. (2010a). A scatter search methodology for the nurse rostering problem. Journal of the Operational Research Society, 61, 1667-1679.
5. Burke, E. K., Li, J., & Qu, R. (2010b). A hybrid model of integer programming and variable neighbourhood search for highly-constrained nurse rostering problems. European Journal of Operational Research, 203, 484-493.
6. Cheang, B., Li, H., Lim, A., & Rodrigues, B. (2003). Nurse rostering problems-a bibliographic survey. European Journal of Operational Research, 151, 447-460.
7. Della Croce, F., Grosso, A., & Salassa, F. (2011). A matheuristic approach for the total completion time permutation flow shop problem. Annals of Operations Research. doi: 10. 1007/s10479-011-0928-x.
8. Ernst, A. T., Jiang, H., Krishnamoorthy, M., Owens, B., & Sier, D. (2004a). An annotated bibliography of personnel scheduling and rostering. Annals of Operations Research, 127, 21-144.
9. Ernst, A. T., Jiang, H., Krishnamoorthy, M., & Sier, D. (2004b). Staff scheduling and rostering: a review of applications, methods and models. European Journal of Operational Research, 153, 3-27.
10. Fischetti, M., Lodi, A., & Branching, L. (2003). Local branching. Mathematical Programming Series B, 98, 23-47.
11. Hansen, P., & Mladenovic, N. (2001). Variable neighborhood search: principles and applications. European Journal of Operational Research, 130, 449-467.
12. Hansen, P., Mladenovic, N., & Urosevic, D. (2006). Variable neighborhood search and local branching. Computers & Operations Research, 33, 3034-3045.
13. Lu, Z., & Hao, J. K. (2012). Adaptive neighborhood search for nurse rostering. European Journal of Operational Research, 218, 865-876.
14. Maenhout, B., & Vanhoucke, M. (2007). An electromagnetic meta-heuristic for the nurse scheduling problem. Journal of Heuristics, 13, 359-385.
15. Maniezzo, V., Stutzle, T., & Voss, S. (Eds.) (2009). Annals of information systems: Vol. 10. Matheuristics: hybridizing metaheuristics and mathematical programming (pp. 1-270). Berlin: Springer.
16. Miller, H. E. (1976). Nurse scheduling using mathematical programming. Operations Research, 24, 857-870.
17. Mladenovic, N., & Hansen, P. (1997). Variable neighborhood search. Computers & Operations Research, 24, 1097-1100.
18. Nanda, R., & Browner, J. (1992). Introduction to employee scheduling. New York: van Nostrand Reinhold.
19. Puchinger, J., & Raidl, G. R. (2005). Combining metaheuristics and exact algorithms in combinatorial optimization: a survey and classification. In LNCS: Vol. 3562. Proceedings of the first international work-conference on the interplay between natural and artificial computation, part II (pp. 41-53).
20. Raidl, G. R., & Puchinger, J. (2008). Combining (integer) linear programming techniques and metaheuristics for combinatorial optimization. Studies in Computational Intelligence, 114, 31-62.
21. Warner, D. M. (1976). Scheduling nursing personnel according to nursing preference: a mathematical programming approach. Operations Research, 24, 842-856.