Open AccessSIMULATION-BASED OPTIMIZATION FOR THE SCHEDULING OF ELECTIVE SURGERY UNDER UNCERTAINTY AND DOWNSTREAM CAPACITY CONSTRAINTS
Author(s) -
Guillermo Durand,
J. Alberto Bandoni
Publication year - 2020
Publication title -
latin american applied research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.123
H-Index - 23
eISSN - 1851-8796
pISSN - 0327-0793
DOI - 10.52292/j.laar.2020.472
Subject(s) - elective surgery , scheduling (production processes) , computer science , robustness (evolution) , schedule , robust optimization , operations research , mathematical optimization , medicine , surgery , engineering , mathematics , biochemistry , chemistry , gene , operating system
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.