Simulation-based optimization for the scheduling of elective surgery under uncertainty and downstream capacity constraints

Abstract

The generation of an optimal schedule of elective surgery cases for a hospital surgery ser-vices unit is a well-known problem in the operations research field. The complexity of the problem is greatly compounded when uncertainties in the pa-rameters are considered and is an issue that has been addressed in few works in the literature. Uncertain-ties appear in surgery durations and the availability of downstream resources such as surgical intensive care units (SICU), presenting large deviations from their expected value and impacting in the perfor-mance of the scheduling process. The technique pre-sented here addresses the uncertainties in the optimal scheduling of a given set of elective surgery cases by means of simulated-based optimization. The main ad-vantage of this approach over previous works is that detailed systems' simulations can be constructed without losing computational performance, thus im-proving the robustness of the scheduling solution.