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 services unit is a well-known problem in the operations research field. The complexity of the problem is greatly compounded when uncertainties in the parameters are considered and is an issue that has been addressed in few works in the literature. Uncertainties 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 performance of the scheduling process. The technique presented here addresses the uncertainties in the optimal scheduling of a given set of elective surgery cases by means of simulated-based optimization. The main advantage of this approach over previous works is that detailed systems? simulations can be constructed without losing computational performance, thus improving the robustness of the scheduling solution.