IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v34y1986i1p130-136.html
   My bibliography  Save this article

On Johnson's Two-Machine Flow Shop with Random Processing Times

Author

Listed:
  • Peng-Sheng Ku

    (The University of Texas at Dallas, Richardson, Texas)

  • Shun-Chen Niu

    (The University of Texas at Dallas, Richardson, Texas)

Abstract

A set of n jobs is to be processed by two machines in series that are separated by an infinite waiting room; each job requires a (known) fixed amount of processing from each machine. In a classic paper, Johnson gave a simple rule for ordering of the set of jobs to minimize the time until the system becomes empty, i.e., the makespan. This paper studies a stochastic generalization of this problem in which job processing times are independent random variables. Our main result is a sufficient condition on the processing time distributions that implies that the makespan becomes stochastically smaller when two adjacent jobs in a given job sequence are interchanged. We also give an extension of the main result to job shops.

Suggested Citation

  • Peng-Sheng Ku & Shun-Chen Niu, 1986. "On Johnson's Two-Machine Flow Shop with Random Processing Times," Operations Research, INFORMS, vol. 34(1), pages 130-136, February.
    • Handle: RePEc:inm:oropre:v:34:y:1986:i:1:p:130-136
    DOI: 10.1287/opre.34.1.130
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.34.1.130
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.34.1.130?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
    ---><---

    Citations

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


    Cited by:

    1. P J Kalczynski & J Kamburowski, 2004. "Generalization of Johnson's and Talwar's scheduling rules in two-machine stochastic flow shops," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1358-1362, December.
    2. Yuri N. Sotskov & Natalja M. Matsveichuk & Vadzim D. Hatsura, 2020. "Schedule Execution for Two-Machine Job-Shop to Minimize Makespan with Uncertain Processing Times," Mathematics, MDPI, vol. 8(8), pages 1-51, August.
    3. Y N Sotskov & A Allahverdi & T-C Lai, 2004. "Flowshop scheduling problem to minimize total completion time with random and bounded processing times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(3), pages 277-286, March.

    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:inm:oropre:v:34:y:1986:i:1:p:130-136. 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 Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.