IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v57y2019i1p216-227.html
   My bibliography  Save this article

Scheduling on uniform parallel machines with periodic unavailability constraints

Author

Listed:
  • Jihene Kaabi
  • Youssef Harrath

Abstract

Scheduling problems under unavailability constraints has become a popular research topic in the last few years. Despite it’s important application in the real world, the uniform parallel machine scheduling problem was the least studied due to its complexity. In this paper, we investigated the uniform parallel machine scheduling problem under deterministic availability constraints. Each machine is subject to one unavailability period. Different versions of the problem regarding the type of jobs (identical and non-identical) and the performance measures (the total completion times and the makespan) were studied. For the case of identical jobs and for both performance measures, we developed linear programming models and optimal algorithms to provide a solution to the problem. For the case of non-identical jobs, we proved that the problem is NP-hard and propose a quadratic program. Because, this later cannot solve problems with very large number of jobs and machines, a heuristic was developed to find near optimal solutions to the problem especially with very large number of jobs and machines. The computational results showed that the heuristic’s performance is very high regardless the dimensions of problem instances.

Suggested Citation

  • Jihene Kaabi & Youssef Harrath, 2019. "Scheduling on uniform parallel machines with periodic unavailability constraints," International Journal of Production Research, Taylor & Francis Journals, vol. 57(1), pages 216-227, January.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:1:p:216-227
    DOI: 10.1080/00207543.2018.1471242
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2018.1471242
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2018.1471242?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. Lin, Ran & Wang, Jun-Qiang & Oulamara, Ammar, 2023. "Online scheduling on parallel-batch machines with periodic availability constraints and job delivery," Omega, Elsevier, vol. 116(C).
    2. Meya Haroune & Cheikh Dhib & Emmanuel Neron & Ameur Soukhal & Hafed Mohamed Babou & Mohamedade Farouk Nanne, 2023. "Multi-project scheduling problem under shared multi-skill resource constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 194-235, April.

    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:tprsxx:v:57:y:2019:i:1:p:216-227. 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/TPRS20 .

    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.