Clustering surgical procedures for master surgical scheduling

Abstract

The sound management of operating rooms is a very important task in each hospital. To use this crucial resource efficiently, cyclic master surgery schedules are often developed. To derive sensible schedules, high-quality input data are necessary. In this paper, we focus on the (elective) surgical procedures’ stochastic durations to determine reasonable, cyclically scheduled surgical clusters. Therefore, we adapt the approach of van Oostrum et al (2008), which was specifically designed for clustering surgical procedures for master surgical scheduling, and present a two-stage solution approach that consists of a new construction heuristic and an improvement heuristic. We conducted a numerical study based on real-world data from a German hospital. The results reveal clusters with considerably reduced variability compared to those of van Oostrum et al(2008).