A robust approach for scheduling in hospitals using multiple objectives

Abstract

Scheduling in hospitals is a challenging task and stochastic influences have a major impact on the final schedule. Therefore, uncertainties of treatment durations and of emergency arrivals have to be taken into account explicitly. In order to avoid re-scheduling we integrate information on stochastic parameters into a scenario-based mixed-integer optimization model. Besides, we focus on different stakeholders’ objectives that are simultaneously considered within a multi-criteria optimization model. Individually optimal solutions are likely to differ and the overall aim is to identify a good and acceptable compromise solution. The presented approach is based on fuzzy sets and merges the interests of several stakeholders. Different schedules are calculated and later on evaluated with randomly generated scenarios for surgery times and emergencies. The resulting objective function values are close to the individually optimal solutions. Finally, the schedules lead to a high rate of utilization and a low amount of overtime.

Keywords:

• surgical scheduling
• compromise decision
• multi-objective optimization
• robust optimization
• fuzzy sets

Acknowledgements

The authors would like to thank anonymous referees for valuable comments on a previous version which helped to improve the paper.