Abstract
We introduce a robust optimization model for scheduling operating rooms with uncertain surgical durations. The model addresses multiple operating rooms and surgical procedures. In the numerical analysis, we verify the influence of the risk-averse tendency on the schedule. The schedules created by the robust optimization are compared with those of stochastic programming. The results suggest that robust optimization avoids long delays, and obtains a solution faster than stochastic programming. In specific control conservative, robust optimization exhibits the same performance as stochastic programming. The robust optimization model is more effective for operating room managers who desire to obtain an accurate solution quickly.
Supported by JSPS KAKENHI (Japan) Grant Number JP21K14371.
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Ito, M., Namba, Y., Takashima, R. (2024). Robust Optimization for Operating Room Scheduling with Uncertain Surgical Durations: Impact of Risk-Aversion on Delay. In: Liberatore, F., Wesolkowski, S., Demange, M., Parlier, G.H. (eds) Operations Research and Enterprise Systems. ICORES ICORES 2022 2023. Communications in Computer and Information Science, vol 1985. Springer, Cham. https://doi.org/10.1007/978-3-031-49662-2_9
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