Operating room management under uncertainty


The operating room management problems are legion. This paper tackles the scheduling of surgical procedures in an operating theatre containing up to two operating rooms and two surgeons. We first solve a deterministic version that uses the constraint programming paradigm and then a stochastic version which embeds the former in a sample average approximation scheme. The latter produces more robust schedules that cope better with the surgeries’ time variability

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We sincerely thank Etienne Beauchamp, Polytechnique Montréal, for all the work he has provided during the implementation of the model in AIMMS. We would like to thank Professor Louis-Martin Rousseau, Polytechnique Montréal, for his support.

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Correspondence to Antoine Legrain.

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Gauthier, J.B., Legrain, A. Operating room management under uncertainty. Constraints 21, 577–596 (2016). https://doi.org/10.1007/s10601-015-9236-4

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  • Operating room management
  • Uncertainty
  • Stochastic
  • Constraint programming
  • Sample average approximation