IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v15y1984i3p366-373.html
   My bibliography  Save this article

Preemptive scheduling of independent jobs on parallel machines subject to financial constraints

Author

Listed:
  • Slowinski, Roman

Abstract

No abstract is available for this item.

Suggested Citation

  • Slowinski, Roman, 1984. "Preemptive scheduling of independent jobs on parallel machines subject to financial constraints," European Journal of Operational Research, Elsevier, vol. 15(3), pages 366-373, March.
  • Handle: RePEc:eee:ejores:v:15:y:1984:i:3:p:366-373
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0377-2217(84)90105-X
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Péter Györgyi & Tamás Kis, 2015. "Approximability of scheduling problems with resource consuming jobs," Annals of Operations Research, Springer, vol. 235(1), pages 319-336, December.
    2. Gafarov, Evgeny R. & Lazarev, Alexander A. & Werner, Frank, 2011. "Single machine scheduling problems with financial resource constraints: Some complexity results and properties," Mathematical Social Sciences, Elsevier, vol. 62(1), pages 7-13, July.
    3. Matthias Bentert & Robert Bredereck & Péter Györgyi & Andrzej Kaczmarczyk & Rolf Niedermeier, 2023. "A multivariate complexity analysis of the material consumption scheduling problem," Journal of Scheduling, Springer, vol. 26(4), pages 369-382, August.
    4. T'kindt, V. & Billaut, J-C. & Proust, C., 2001. "Solving a bicriteria scheduling problem on unrelated parallel machines occurring in the glass bottle industry," European Journal of Operational Research, Elsevier, vol. 135(1), pages 42-49, November.
    5. Wu, Xianyi & Zhou, Xian, 2008. "Stochastic scheduling to minimize expected maximum lateness," European Journal of Operational Research, Elsevier, vol. 190(1), pages 103-115, October.
    6. Péter Györgyi & Tamás Kis, 2019. "Minimizing total weighted completion time on a single machine subject to non-renewable resource constraints," Journal of Scheduling, Springer, vol. 22(6), pages 623-634, December.
    7. Györgyi, Péter & Kis, Tamás, 2017. "Approximation schemes for parallel machine scheduling with non-renewable resources," European Journal of Operational Research, Elsevier, vol. 258(1), pages 113-123.

    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:eee:ejores:v:15:y:1984:i:3:p:366-373. 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.