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A simulation-based optimization approach for the calibration of a discrete event simulation model of an emergency department

Author

Listed:
  • Alberto Santis

    (SAPIENZA Università di Roma)

  • Tommaso Giovannelli

    (Lehigh University)

  • Stefano Lucidi

    (SAPIENZA Università di Roma)

  • Mauro Messedaglia

    (ACTOR Start up of SAPIENZA Università di Roma)

  • Massimo Roma

    (SAPIENZA Università di Roma)

Abstract

Accurate modeling of the patient flow within an Emergency Department (ED) is required by all studies dealing with the increasing and well-known problem of overcrowding. Since Discrete Event Simulation (DES) models are often adopted with the aim of assessing solutions for reducing the impact of this worldwide phenomenon, an accurate estimation of the service time of the ED processes is necessary to guarantee the reliability of the results. However, simulation models concerning EDs are frequently affected by missing data, thus requiring a proper estimation of some unknown parameters. In this paper, a simulation-based optimization approach is used to estimate the incomplete data in the patient flow within an ED by adopting a model calibration procedure. The objective function of the resulting minimization problem represents the deviation between simulation output and real data, while the constraints ensure that the response of the simulation is sufficiently accurate according to the precision required. Data from a real case study related to a big ED in Italy is used to test the effectiveness of the proposed approach. The experimental results show that the model calibration allows recovering the missing parameters, thus leading to an accurate DES model.

Suggested Citation

  • Alberto Santis & Tommaso Giovannelli & Stefano Lucidi & Mauro Messedaglia & Massimo Roma, 2023. "A simulation-based optimization approach for the calibration of a discrete event simulation model of an emergency department," Annals of Operations Research, Springer, vol. 320(2), pages 727-756, January.
    • Handle: RePEc:spr:annopr:v:320:y:2023:i:2:d:10.1007_s10479-021-04382-9
    DOI: 10.1007/s10479-021-04382-9
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    References listed on IDEAS

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    Cited by:

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    2. Shahab Sadri & Arsalan Paleshi & Lihui Bai & Monica Gentili, 2024. "A Simulation Study for a Safe Reopening and Operation of the Trager Institute Optimal Aging Clinic During the COVID-19 Pandemic," Interfaces, INFORMS, vol. 54(2), pages 188-204, March.

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