On the characterization and generation of nurse scheduling problem instances

European Journal of Operational Research

Volumn 196, Issue 2, 2009, Pages 457-467

  Vanhoucke, Mario ^a,b   Maenhout, Broos ^a  

^a GHENT UNIVERSITY   (Belgium)

^b VLERICK BUSINESS SCHOOL   (Belgium)

Author keywords

Nurse scheduling; Problem characterization

Indexed keywords

BENCHMARKING; COMPUTATIONAL COMPLEXITY; NURSING; ONLINE SEARCHING; SCHEDULING;

COMPARATIVE TESTS; COMPLEXITY INDICATORS; COMPUTATIONAL EFFORTS; FUTURE RESEARCHES; IP MODELS; NURSE SCHEDULING; NURSE SCHEDULING PROBLEMS; OVERALL QUALITIES; PARTICULAR SOLUTIONS; PROBLEM CHARACTERIZATION; PROBLEM GENERATORS; RESEARCH COMMUNITIES; SELECTION OF THE BESTS; SOLUTION PROCEDURES; TIME LIMITS; WORKPLACE CONDITIONS;

HEURISTIC METHODS;

EID: 58149214098     PISSN: 03772217     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejor.2008.03.044     Document Type: Article

References (46)

1. Aickelin U., and Dowsland K.A. Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem. Journal of Scheduling 3 (2000) 139-153
2. Aickelin U., and Dowsland K.A. An indirect genetic algorithm for a nurse scheduling problem. Computers & Operations Research 31 (2004) 761-778
3. Aickelin U., Burke E.K., and Li J. An estimation of distribution algorithm with intelligent local search for rule-based nurse rostering. Journal of the Operational Research Society 58 (2007) 1574-1585
4. Azaiez M.N., and Al Sharif S.S. A 0-1 goal programming model for nurse scheduling. Computers & Operations Research 32 (2005) 491-507
5. Bard J.F., and Purnomo H.W. Preference scheduling for nurses using column generation. European Journal of Operational Research 164 (2005) 510-534
6. Bellanti F., Carello G., Della Croce F., and Tadei R. A greedy-based neighbourhood search approach to a nurse rostering problem. European Journal of Operational Research 153 (2004) 28-40
7. Berrada I., Ferland J., and Michelon P. A multi-objective approach to nurse scheduling with both hard and soft constraints. Socio-Economic Planning Sciences 30 (1996) 183-193
8. Bester M.J., Nieuwoudt I., and Van Vuuren J.H. Finding good nurse duty schedules: A case study. Journal of Scheduling 10 (2007) 387-405
9. Burke E.K., De Causmaecker P., and Vanden Berghe G. A hybrid Tabu search algorithm for the nurse rostering problem. Lecture Notes in Artificial Intelligence 1585 (1999) 187-194
10. Burke E.K., Cowling P., De Causmaecker P., and Vanden Berghe G. Fitness evaluation for nurse scheduling problems. Proceedings of the Congress on Evolutionary Computation (CEC2001) (2001), IEEE Press 1139-1146
11. Burke E.K., Cowling P., De Causmaecker P., and Vanden Berghe G. A memetic approach to the nurse rostering problem. Applied Intelligence 3 (2001) 199-214
12. Burke E.K., De Causmaecker P., Vanden Berghe G., and Van Landeghem H. The state of the art of nurse rostering. Journal of Scheduling 7 (2004) 441-499
13. Burke E.K., Curtois T., Post G., Qu R., and Veltman B. A hybrid heuristic ordering and variable neighbourhood search for the nurse rostering problem. European Journal of Operational Research 188 (2008) 330-341
14. Caprara A., Monaci M., and Toth P. Models and algorithms for a staff scheduling problem. Mathematical Programming 98 (2003) 445-476
15. Cheang B., Li H., Lim A., and Rodrigues B. Nurse rostering problems - A bibliographic survey. European Journal of Operational Research 151 (2003) 447-460
16. Cline D., Reilly C., and Moore J.F. What's behind RN turnover?. Nursing Management 34 (2003) 50-53
17. Dowsland K.A. Nurse scheduling with tabu search and strategic oscillation. European Journal of Operational Research 106 (1998) 393-407
18. Elmaghraby S.E., and Herroelen W. On the measurement of complexity in activity networks. European Journal of Operational Research 5 (1980) 223-234
19. Ernst A.T., Jiang H., Krishamoorty M., Owens B., and Sier D. Staff scheduling and rostering: A review of applications, methods and models. European Journal of Operational Research 153 (2004) 3-27
20. Goodman, M.D., Dowsland, K.A., Thompson, J.M., 2007. A grasp-knapsack hybrid for a nurse-scheduling problem. Journal of Scheduling. doi:10.1007/S10732-007-9066-7.
21. Gutjahr W.J., and Rauner M.S. An ACO algorithm for a dynamic regional nurse-scheduling problem in Austria. Computers & Operations Research 41 (2007) 642-666
22. Harper P.R., and Winslett D.J. Classification trees: A possible method for maternity risk grouping. European Journal of Operational Research 169 (2006) 146-156
23. Jan A., Yamamoto M., and Ohuchi A. Evolutionary algorithms for nurse scheduling problem. Proceedings of the Congress on Evolutionary Computation (CEC2000) (2000), IEEE Press 196-203
24. Jaumard B., Semet F., and Vovor T. A generalized linear programming model for nurse scheduling. European Journal of Operational Research 107 (1998) 1-18
25. Kass G.V. An exploratory technique for investigating large quantities of categorical data. Journal of the Royal Statistical Society Series C - Applied Statistics 29 (1980) 119-127
26. Koop G.J. Multiple shift workforce lower bounds. Management Science 34 (1988) 1221-1230
27. Kruskal W.H., and Wallis W.A. Use of ranks in one-criterion analysis of variance. Journal of the American Statistical Association 47 (1952) 583-621
28. Labro E., and Vanhoucke M. A simulation analysis of errors in the design of costing systems. The Accounting Review 82 (2007) 939-962
29. Maenhout B., and Vanhoucke M. New computational results for the nurse scheduling problem: A scatter search algorithm. Lecture Notes in Computer Science 3906 (2006) 158-170
30. Maenhout B., and Vanhoucke M. An electromagnetic meta-heuristic for the nurse scheduling problem. Journal of Heuristics 13 (2007) 359-385
31. Maenhout B., and Vanhoucke M. A comparison and hybridization of crossover operators for the nurse scheduling problem. Annals of Operations Research 159 (2008) 333-353
32. Maenhout, B., 2007. Exact and Meta-heuristic Algorithms for Nurse Shift Scheduling Problems, PhD, Ghent University.
33. Mann H.B., and Whitney D.R. On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics 18 (1947) 50-60
34. Millar H.H., and Kiragu M. Cyclic and non-cyclic scheduling of 12 h shift nurses by network programming. European Journal of Operational Research 104 (1998) 582-592
35. Miller H.E., Pierskalla W.P., and Rath G.J. Nurse scheduling using mathematical programming. Operations Research 24 (1976) 857-871
36. Musa A.A., and Saxena U. Scheduling nurses using goal programming techniques. IIE Transactions 16 (1984) 216-221
37. Osogami T., and Imai H. Classification of various neighbourhood operations for the nurse scheduling problem. Lecture Notes in Computer Science 1969 (2000) 72-83
38. Parr D., and Thompson J.M. Solving the multi-objective nurse scheduling problem with a weighted cost function. Annals of Operations Research 155 (2007) 279-288
39. Ridley S., Jones S., Shahani A., Brampton W., Nielsen M., and Rowan K. Classification trees for iso-resource grouping in intensive care. Anaesthesia 53 (1998) 833-840
40. Schrage L. LINDO: Optimization Software for Linear Programming (1995), LINDO Systems Inc., Chicago, IL
41. Trivedi V.M., and Warner M. A branch and bound algorithm for optimum allocation of float nurses. Management Science 22 (1976) 972-981
42. Vanhoucke, M., Maenhout, B., 2005. Characterisation and generation of nurse scheduling problem instances. Working Paper 05/339. Ghent University, 31p.
43. Vanhoucke, M., Maenhout, B., 2007. NSPLib - A nurse scheduling problem library: A tool to evaluate (meta-)heuristic procedures. In: Brailsford, S., Harper, P. (Eds.), Operational Research for Health Policy: Making Better Decisions, Proceedings for the 31st Annual Meeting of the Working Group on Operations Research Applied to Health Services, pp. 151-165.
44. Vanhoucke M., Coelho J.S., Debels D., Maenhout B., and Tavares L.V. An evaluation of the adequacy of project network generators with systematically sampled networks. European Journal of Operational Research 187 (2008) 511-524
45. Warner H.W. Scheduling nursing personnel according to nursing preference: A mathematical approach. Operations Research 24 (1976) 842-856
46. Zurn P., Dolea C., and Stilwell B. Nurse retention and recruitment: Developing a motivated workforce. The Global Nursing Review Initiative (WHO) 4 (2005) 1-31