A stochastic model for operating room planning under capacity constraints

Aida Jebali, Ali Diabat

    Research output: Contribution to journalArticle

    Abstract

    The present paper describes a two-stage stochastic programme for operating room planning that takes into account capacity constraints of three hospital resources: operating rooms, beds in the intensive care unit (ICU) and beds in the ward (or medium care unit). Operating room planning consists of deciding on the elective surgeries to perform over each period of the planning horizon, while considering uncertainties related to surgery duration as well as patient length of stay in the ICU and the ward. Sample average approximation is then used to solve the planning problem, aiming to minimise the sum of patient-related costs and expected resource utilisation costs. Computational experiments are conducted to evaluate the performance of the proposed solution method. The obtained results highlight the robustness of operating room plans obtained by a stochastic approach, in comparison to those generated by a deterministic approach, and the importance of considering both ICU and ward beds in operating room planning.

    Original languageEnglish (US)
    Pages (from-to)7252-7270
    Number of pages19
    JournalInternational Journal of Production Research
    Volume53
    Issue number24
    DOIs
    StatePublished - Dec 17 2015

    Fingerprint

    Operating rooms
    Stochastic models
    Hospital beds
    Intensive care units
    Planning
    Surgery
    Costs
    Stochastic model
    Capacity constraints
    Operating room
    Intensive care unit
    Experiments

    Keywords

    • capacity constraints
    • operating room planning
    • sample average approximation
    • two-stage stochastic programming

    ASJC Scopus subject areas

    • Strategy and Management
    • Management Science and Operations Research
    • Industrial and Manufacturing Engineering

    Cite this

    A stochastic model for operating room planning under capacity constraints. / Jebali, Aida; Diabat, Ali.

    In: International Journal of Production Research, Vol. 53, No. 24, 17.12.2015, p. 7252-7270.

    Research output: Contribution to journalArticle

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