IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v70y1997i0p221-23910.1023-a1018974221508.html
   My bibliography  Save this article

Multi-objective stochastic scheduling of job ready times

Author

Listed:
  • Paul Stanfield
  • Russell King
  • Thom Hodgson

Abstract

A fundamental scheduling problem is to determine a production start (ready) time based on customer-specified due dates. Typically, the objective is to delay the ready time in an attempt to minimize work-in-process inventory and maximize production system utilization. In many practical situations, highly variable service times complicate this problem. In such a case, the ready time implies a level of on-time completion confidence for each job. As the ready time increases, the on-time confidence decreases. This paper investigates the ready time/job confidence level tradeoff. A multi-objective model balances the ready time and confidence level maximization goals. The model involves combinatorial and numerical optimization and has an exceptionally complex state space. In view of these complexities, we investigate a pairwise interchange heuristic and a genetic algorithm search solution. Experimental results support solution through a process involving both the heuristic and the genetic algorithm. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • Paul Stanfield & Russell King & Thom Hodgson, 1997. "Multi-objective stochastic scheduling of job ready times," Annals of Operations Research, Springer, vol. 70(0), pages 221-239, April.
    • Handle: RePEc:spr:annopr:v:70:y:1997:i:0:p:221-239:10.1023/a:1018974221508
    DOI: 10.1023/A:1018974221508
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1018974221508
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1023/A:1018974221508?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.

    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:spr:annopr:v:70:y:1997:i:0:p:221-239:10.1023/a:1018974221508. 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.springer.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.