Patient scheduling optimization through an application of the cutting stock problem

Efficiently using hospital beds is increasingly important, as healthcare expenditures are constantly rising. In this paper we present a research on this topic, taking into account both unscheduled and scheduled admissions. We used a modified version of the cutting stock problem to define an integer linear program model and tested our results in two simulations. In a case study on the VUmc neurology and neurosurgery department we achieved strategies requiring 28 beds for a blocking probability of 5% which is a significant improvement on the current 30 beds required by the VUmc for the same blocking probability.