Robust Optimization for Operating Room Scheduling with Uncertain Surgical Durations: Impact of Risk-Aversion on Delay

Mari Ito, Yoshito Namba, Ryuta Takashima

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationOperations Research and Enterprise Systems - 11th International Conference, ICORES 2022, and 12th International Conference, ICORES 2023, Revised Selected Papers
EditorsFederico Liberatore, Slawo Wesolkowski, Marc Demange, Greg H. Parlier
PublisherSpringer Science and Business Media Deutschland GmbH
Pages168-177
Number of pages10
ISBN (Print)9783031496615
DOIs
Publication statusPublished - 2024
Event11th and 12th International Conferences on Operations Research and Enterprise Systems, ICORES 2022 and 2023 - Lisbon, Portugal
Duration: 19 Feb 202321 Feb 2023

Publication series

NameCommunications in Computer and Information Science
Volume1985 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference11th and 12th International Conferences on Operations Research and Enterprise Systems, ICORES 2022 and 2023
Country/TerritoryPortugal
CityLisbon
Period19/02/2321/02/23

Keywords

  • Operating room scheduling
  • Operations research in health service
  • Robust optimization
  • Stochastic programming

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