IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v77y1998i0p51-7810.1023-a1018981529144.html
   My bibliography  Save this article

Process selection and tool assignment in automated cellular manufacturing using Genetic Algorithms

Author

Listed:
  • David Sinriech
  • Abekasis Meir

Abstract

The purpose of this study is to develop an efficient heuristic for the process selection and part cell assignment problem. The study assumes a production environment where each part has several process plans, each manifested by a required set of tools. These tools can be assigned to different machines based on a tool-machine compatibility matrix. An additional assumption is that all relevant data such as periodic demand, processing time, processing cost, tool magazine capacity, tool changing time, tool life and tool cost are fixed and known. A mixed integer linear program which takes all relevant data into account is developed to minimize the production cost. The suggested solution approach to solve this model makes use of Genetic Algorithms: a class of heuristic search and optimization techniques that imitate the natural selection and evolutionary process. First, the encoding of the solutions into integer strings is presented, as well as the genetic operators used by the algorithm. Next, the efficiency and robustness of the solution procedure is demonstrated through several different examples. Copyright Kluwer Academic Publishers 1998

Suggested Citation

  • David Sinriech & Abekasis Meir, 1998. "Process selection and tool assignment in automated cellular manufacturing using Genetic Algorithms," Annals of Operations Research, Springer, vol. 77(0), pages 51-78, January.
    • Handle: RePEc:spr:annopr:v:77:y:1998:i:0:p:51-78:10.1023/a:1018981529144
    DOI: 10.1023/A:1018981529144
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1018981529144
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1023/A:1018981529144?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.

    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:77:y:1998:i:0:p:51-78:10.1023/a:1018981529144. 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.