IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v49y2017i4p367-380.html
   My bibliography  Save this article

A sample gradient-based algorithm for a multiple-OR and PACU surgery scheduling problem

Author

Listed:
  • Miao Bai
  • Robert H. Storer
  • Gregory L. Tonkay

Abstract

In this article, we study a surgery scheduling problem in multiple Operating Rooms (ORs) constrained by the Post-Anesthesia Care Unit (PACU) capacity within the block-booking framework. With surgery sequences predetermined in each OR, a Discrete-Event Dynamic System (DEDS) is devised for the problem. A DEDS-based stochastic optimization model is formulated in order to minimize the cost incurred from patient waiting time, OR idle time, OR blocking time, OR overtime, and PACU overtime. A sample gradient-based algorithm is proposed for the sample average approximation of our formulation. Numerical experiments suggest that the proposed method identifies near-optimal solutions and outperforms previous methods. We also show that considerable cost savings (11.8% on average) are possible in hospitals where PACU beds are a constraint.

Suggested Citation

  • Miao Bai & Robert H. Storer & Gregory L. Tonkay, 2017. "A sample gradient-based algorithm for a multiple-OR and PACU surgery scheduling problem," IISE Transactions, Taylor & Francis Journals, vol. 49(4), pages 367-380, April.
  • Handle: RePEc:taf:uiiexx:v:49:y:2017:i:4:p:367-380
    DOI: 10.1080/0740817X.2016.1237061
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0740817X.2016.1237061
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/0740817X.2016.1237061?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sean Harris & David Claudio, 2022. "Current Trends in Operating Room Scheduling 2015 to 2020: a Literature Review," SN Operations Research Forum, Springer, vol. 3(1), pages 1-42, March.
    2. Shuwan Zhu & Wenjuan Fan & Shanlin Yang & Jun Pei & Panos M. Pardalos, 2019. "Operating room planning and surgical case scheduling: a review of literature," Journal of Combinatorial Optimization, Springer, vol. 37(3), pages 757-805, April.
    3. Huaxin Qiu & Dujuan Wang & Yanzhang Wang & Yunqiang Yin, 2019. "MRI appointment scheduling with uncertain examination time," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 62-82, January.
    4. Çelik, Batuhan & Gul, Serhat & Çelik, Melih, 2023. "A stochastic programming approach to surgery scheduling under parallel processing principle," Omega, Elsevier, vol. 115(C).
    5. Miao Bai & Robert H. Storer & Gregory L. Tonkay, 2022. "Surgery Sequencing Coordination with Recovery Resource Constraints," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1207-1223, March.
    6. Wang, Yu & Zhang, Yu & Tang, Jiafu, 2019. "A distributionally robust optimization approach for surgery block allocation," European Journal of Operational Research, Elsevier, vol. 273(2), pages 740-753.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:uiiexx:v:49:y:2017:i:4:p:367-380. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/uiie .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.