IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v67y2016i4p654-663.html
   My bibliography  Save this article

Multi-objective parallel machine scheduling problems by considering controllable processing times

Author

Listed:
  • Cheng-Hsiang Liu

    (National Pingtung University of Science and Technology, Neipu, Taiwan)

  • Wan-Ni Tsai

    (National Pingtung University of Science and Technology, Neipu, Taiwan)

Abstract

This study examines parallel machine scheduling problems with controllable processing times. The processing time of each job can be between lower and upper bounds, and a cost is associated with the processing of a job on a machine. The processing time of a job can be decreased, which may lower the cycle time, although doing so would incur additional costs. This study develops two multi-objective mathematical models, which consist of two and three inconsistent objective functions, respectively. The first model minimizes the total manufacturing cost (TMC) and the total weighted tardiness (TWT) simultaneously, while the second uses makespan (Cmax as an additional objective function typically improves TWT and worsens TMC.

Suggested Citation

  • Cheng-Hsiang Liu & Wan-Ni Tsai, 2016. "Multi-objective parallel machine scheduling problems by considering controllable processing times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(4), pages 654-663, April.
    • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:4:p:654-663
    as

    Download full text from publisher

    File URL: http://www.palgrave-journals.com/jors/journal/v67/n4/pdf/jors201582a.pdf
    File Function: Link to full text PDF
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: http://www.palgrave-journals.com/jors/journal/v67/n4/full/jors201582a.html
    File Function: Link to full text HTML
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Rui Zhang, 2017. "Sustainable Scheduling of Cloth Production Processes by Multi-Objective Genetic Algorithm with Tabu-Enhanced Local Search," Sustainability, MDPI, vol. 9(10), pages 1-26, September.
    2. Prasit Kailomsom & Charoenchai Khompatraporn, 2023. "A Multi-Objective Optimization Model for Multi-Facility Decisions of Infectious Waste Transshipment and Disposal," Sustainability, MDPI, vol. 15(6), pages 1-16, March.

    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:pal:jorsoc:v:67:y:2016:i:4:p:654-663. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    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.