Relaxation of Coverage Constraints in Hospital Personnel Rostering
- 960 Downloads
Hospital personnel scheduling deals with a large number of constraints of a different nature, some of which need to be satisfied at all costs. It is, for example, unacceptable not to fully support patient care needs and therefore a sufficient number of skilled personnel has to be scheduled at any time. In addition to personnel coverage constraints, nurse rostering problems deal with time-related constraints arranging work load, free time, and personal requests for the staff.
Real-world nurse rostering problems are usually over-constrained but schedulers in hospitals manage to produce solutions anyway. In practice, coverage constraints, which are generally defined as hard constraints, are often relaxed by the head nurse or personnel manager.
The work presented in this paper builds upon a previously developed nurse rostering system that is used in several Belgian hospitals. In order to deal with widely varying problems and objectives, all the data in the model are modifiable by the users.
We introduce a set of specific algorithms for handling and even relaxing coverage constraints, some of which were not supposed to be violated in the original model. The motivation is that such practices are common in real scheduling environments. Relaxations enable the generation of better-quality schedules without enlarging the search space or the computation time.
KeywordsSoft Constraint Hard Constraint Shift Type Relaxation Algorithm Nurse Rostering
Unable to display preview. Download preview PDF.
- 1.Ahmad, J., Yamamoto, M., Ohuchi, A.: Evolutionary Algorithms for Nurse Scheduling Problem. In: Proc. 2000 Congress Evolut. Comput., CEC 2000, San Diego, CA, pp. 196–203 (2000)Google Scholar
- 5.Burke, E.K., De Causmaecker, P., Petrovic, S., Vanden Berghe, G.: Floating Personnel Requirements in a Shift Based Timetable, Working Paper, KaHo St-Lieven (2001)Google Scholar
- 6.Burke, E.K., De Causmaecker, P., Petrovic, S., Vanden Berghe, G.: Fitness Evaluation for Nurse Scheduling Problems. In: Proc. Congress Evolut. Comput., CEC 2001, Seoul, South Korea, pp. 1139–1146. IEEE Press, Los Alamitos (2001)Google Scholar
- 7.Burke, E.K., De Causmaecker, P., Petrovic, S., Vanden Berghe, G.: Variable Neighbourhood Search for Nurse Rostering Problems. In: Proc. 4th Metaheuristics Int. Conf., MIC 2001, Porto, Portugal, pp. 755–760 (2001) (accepted for publication in the selected papers volume by Kluwer) Google Scholar
- 9.Chen, J.-G., Yeung, T.: Hybrid Expert System Approach to Nurse Scheduling. Comput. Nursing 11, 183–192 (1993)Google Scholar
- 10.Chiarandini, M., Schaerf, A., Tiozzo, F.: Solving Employee Timetabling Problems with Flexible Workload using Tabu Search. In: Burke, E.K., Ross, P. (eds.) PATAT 1995. LNCS, vol. 1153, pp. 298–302. Springer, Heidelberg (1996)Google Scholar
- 12.Isken, M., Hancock, W.: A Heuristic Approach to Nurse Scheduling in Hospital Units with Non-Stationary, Urgent Demand, and a Fixed Staff Size. J. Soc. Health Syst. 2, 24–41 (1990)Google Scholar
- 13.Kawanaka, H., Yamamoto, K., Yoshikawa, T., Shinogi, T., Tsuruoka, S.: Genetic Algorithm with the Constraints for Nurse Scheduling Problem. In: Proc. Congress Evolut. Comput., CEC 2001, Seoul, South Korea, pp. 1123–1130. IEEE Press, Los Alamitos (2001)Google Scholar
- 14.Meisels, A., Gudes, E., Solotorevski, G.: Employee Timetabling, Constraint Networks and Knowledge-Based Rules: a Mixed Approach. In: Burke, E.K., Ross, P. (eds.) PATAT 1995. LNCS, vol. 1153, pp. 93–105. Springer, Heidelberg (1996)Google Scholar
- 19.Vanden Berghe, G.: Soft constraints in the Nurse Rostering Problem (2001), http://www.cs.nott.ac.uk/~gvb/constraints.ps