IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v335y2026i1p67-82.html

Scheduling maintenance activities subject to continuous stochastic job-dependent machine deterioration

Author

Listed:
  • Arter, Antonia
  • Briskorn, Dirk
  • Gönsch, Jochen

Abstract

In this paper, we consider a single machine scheduling problem with a fixed job sequence involving job-dependent deterioration and maintenance activities. The deteriorations underlie continuous probability distributions and degrade the machine’s state. Deteriorations may lead to a machine breakdown, which demands a time-consuming maintenance activity. To prevent the machine from breaking down, planned maintenance activities can be scheduled between jobs in order to restore the state of the machine. Thereby, the current state of the machine is observable at the completion of any job and is decisive for the decision about planning a maintenance activity. The goal is to minimize the expected total completion time of the jobs in the sequence. We formalize the optimization problem, formulate a dynamic programming formulation representing the problem, and present different heuristic solution approaches. In a computational study we analyze the results for the different proposed solution approaches and show that multiple approaches provide good solutions for the scheduling of planned maintenance activities.

Suggested Citation

  • Arter, Antonia & Briskorn, Dirk & Gönsch, Jochen, 2026. "Scheduling maintenance activities subject to continuous stochastic job-dependent machine deterioration," European Journal of Operational Research, Elsevier, vol. 335(1), pages 67-82.
    • Handle: RePEc:eee:ejores:v:335:y:2026:i:1:p:67-82
    DOI: 10.1016/j.ejor.2026.04.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221726003437
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2026.04.013?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:eee:ejores:v:335:y:2026:i:1:p:67-82. 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: 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.