IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v271y2018i3p1070-1084.html
   My bibliography  Save this article

Solution methods for the tray optimization problem

Author

Listed:
  • Dollevoet, Twan
  • van Essen, J. Theresia
  • Glorie, Kristiaan M.

Abstract

In order to perform medical surgeries, hospitals keep large inventories of surgical instruments. These instruments need to be sterilized before each surgery. Typically the instruments are kept in trays. Multiple trays may be required for a single surgery, while a single tray may contain instruments that are required for multiple surgical procedures. The tray optimization problem (TOP) consists of three main decisions: (i) the assignment of instruments to trays, (ii) the assignment of trays to surgeries, and (iii) the number of trays to keep in inventory. The TOP decisions have to be made such that total operating costs are minimized and such that for every surgery sufficient instruments are available. This paper presents and evaluates several exact and heuristic solution methods for the TOP. We compare solution methods on computation time and solution quality. Moreover, we conduct simulations to evaluate the performance of the solutions in the long run. The novel methods that are provided are the first methods that are capable of solving instances of realistic size. The most promising method consists of a highly scalable advanced greedy algorithm. Our results indicate that the outcomes of this method are, on average, very close to the outcomes of the other methods investigated, while it may be easily applied by (large) hospitals. The findings are robust with respect to fluctuations in long term OR schedules.

Suggested Citation

  • Dollevoet, Twan & van Essen, J. Theresia & Glorie, Kristiaan M., 2018. "Solution methods for the tray optimization problem," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1070-1084.
    • Handle: RePEc:eee:ejores:v:271:y:2018:i:3:p:1070-1084
    DOI: 10.1016/j.ejor.2018.05.051
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221718304703
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2018.05.051?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.

    References listed on IDEAS

    as
    1. Christian Hagist & Laurence Kotlikoff, 2005. "Who's Going Broke? Comparing Growth in Healthcare Costs in Ten OECD Countries," NBER Working Papers 11833, National Bureau of Economic Research, Inc.
    2. Marshall L. Fisher, 2004. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 50(12_supple), pages 1861-1871, December.
    3. Reymondon, Francis & Pellet, Bertrand & Marcon, Eric, 2008. "Optimization of hospital sterilization costs proposing new grouping choices of medical devices into packages," International Journal of Production Economics, Elsevier, vol. 112(1), pages 326-335, March.
    4. Muter, İbrahim & Birbil, Ş. İlker & Bülbül, Kerem, 2018. "Benders decomposition and column-and-row generation for solving large-scale linear programs with column-dependent-rows," European Journal of Operational Research, Elsevier, vol. 264(1), pages 29-45.
    5. Laurence J. Kotlikoff, 2005. "Who’s Going Broke? Comparing Growth in Healthcare Costs in Ten OECD Countries," Working Papers id:286, eSocialSciences.
    6. Muter, İbrahim & İlker Birbil, Ş. & Bülbül, Kerem & Şahin, Güvenç, 2012. "A note on “A LP-based heuristic for a time-constrained routing problem”," European Journal of Operational Research, Elsevier, vol. 221(2), pages 306-307.
    7. Hanif D. Sherali & J. Cole Smith, 2001. "Improving Discrete Model Representations via Symmetry Considerations," Management Science, INFORMS, vol. 47(10), pages 1396-1407, October.
    8. Marshall L. Fisher, 2004. "Comments on ÜThe Lagrangian Relaxation Method for Solving Integer Programming ProblemsÝ," Management Science, INFORMS, vol. 50(12_supple), pages 1872-1874, December.
    9. Joris Klundert & Philippe Muls & Maarten Schadd, 2008. "Optimizing sterilization logistics in hospitals," Health Care Management Science, Springer, vol. 11(1), pages 23-33, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Amogh Bhosekar & Sandra Ekşioğlu & Tuğçe Işık & Robert Allen, 2023. "A discrete event simulation model for coordinating inventory management and material handling in hospitals," Annals of Operations Research, Springer, vol. 320(2), pages 603-630, January.
    2. Ehsan Ahmadi & Dale T. Masel & Seth Hostetler, 2023. "A Data-Driven Decision-Making Model for Configuring Surgical Trays Based on the Likelihood of Instrument Usages," Mathematics, MDPI, vol. 11(9), pages 1-26, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dollevoet, T.A.B. & van Essen, J.T. & Glorie, K.M., 2017. "Solution methods for the tray optimization problem," Econometric Institute Research Papers EI2017-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. An, Yu & Zhang, Yu & Zeng, Bo, 2015. "The reliable hub-and-spoke design problem: Models and algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 103-122.
    3. Alexandre Belloni & Mitchell J. Lovett & William Boulding & Richard Staelin, 2012. "Optimal Admission and Scholarship Decisions: Choosing Customized Marketing Offers to Attract a Desirable Mix of Customers," Marketing Science, INFORMS, vol. 31(4), pages 621-636, July.
    4. Zhizhu Lai & Qun Yue & Zheng Wang & Dongmei Ge & Yulong Chen & Zhihong Zhou, 2022. "The min-p robust optimization approach for facility location problem under uncertainty," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1134-1160, September.
    5. Junming Liu & Weiwei Chen & Jingyuan Yang & Hui Xiong & Can Chen, 2022. "Iterative Prediction-and-Optimization for E-Logistics Distribution Network Design," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 769-789, March.
    6. Adam Diamant & Joseph Milner & Fayez Quereshy & Bo Xu, 2018. "Inventory management of reusable surgical supplies," Health Care Management Science, Springer, vol. 21(3), pages 439-459, September.
    7. Zheng, Jianfeng & Meng, Qiang & Sun, Zhuo, 2014. "Impact analysis of maritime cabotage legislations on liner hub-and-spoke shipping network design," European Journal of Operational Research, Elsevier, vol. 234(3), pages 874-884.
    8. Vasile BRÄ‚TIAN, 2018. "Portfolio Optimization. Application of the Markowitz Model Using Lagrange and Profitability Forecast," Expert Journal of Economics, Sprint Investify, vol. 6(1), pages 26-34.
    9. Miguel A. Lejeune & John Turner, 2019. "Planning Online Advertising Using Gini Indices," Operations Research, INFORMS, vol. 67(5), pages 1222-1245, September.
    10. Claudio Gambella & Joe Naoum-Sawaya & Bissan Ghaddar, 2018. "The Vehicle Routing Problem with Floating Targets: Formulation and Solution Approaches," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 554-569, August.
    11. Zhang, Zhi-Hai & Jiang, Hai & Pan, Xunzhang, 2012. "A Lagrangian relaxation based approach for the capacitated lot sizing problem in closed-loop supply chain," International Journal of Production Economics, Elsevier, vol. 140(1), pages 249-255.
    12. Xia, Jun & Wang, Kai & Wang, Shuaian, 2019. "Drone scheduling to monitor vessels in emission control areas," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 174-196.
    13. Ahmadi-Javid, Amir & Hoseinpour, Pooya, 2019. "Service system design for managing interruption risks: A backup-service risk-mitigation strategy," European Journal of Operational Research, Elsevier, vol. 274(2), pages 417-431.
    14. Fatemeh Keshavarz-Ghorbani & Seyed Hamid Reza Pasandideh, 2022. "A Lagrangian relaxation algorithm for optimizing a bi-objective agro-supply chain model considering CO2 emissions," Annals of Operations Research, Springer, vol. 314(2), pages 497-527, July.
    15. Margarita P. Castro & Andre A. Cire & J. Christopher Beck, 2020. "An MDD-Based Lagrangian Approach to the Multicommodity Pickup-and-Delivery TSP," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 263-278, April.
    16. Hoseinpour, Pooya & Ahmadi-Javid, Amir, 2016. "A profit-maximization location-capacity model for designing a service system with risk of service interruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 113-134.
    17. Steeger, Gregory & Rebennack, Steffen, 2017. "Dynamic convexification within nested Benders decomposition using Lagrangian relaxation: An application to the strategic bidding problem," European Journal of Operational Research, Elsevier, vol. 257(2), pages 669-686.
    18. Zhang, Guowei & Jia, Ning & Zhu, Ning & Adulyasak, Yossiri & Ma, Shoufeng, 2023. "Robust drone selective routing in humanitarian transportation network assessment," European Journal of Operational Research, Elsevier, vol. 305(1), pages 400-428.
    19. Thomas L. Magnanti, 2021. "Optimization: From Its Inception," Management Science, INFORMS, vol. 67(9), pages 5349-5363, September.
    20. Sinha, Ankur & Das, Arka & Anand, Guneshwar & Jayaswal, Sachin, 2023. "A general purpose exact solution method for mixed integer concave minimization problems," European Journal of Operational Research, Elsevier, vol. 309(3), pages 977-992.

    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:eee:ejores:v:271:y:2018:i:3:p:1070-1084. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.