IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v24y1978i12p1242-1251.html
   My bibliography  Save this article

Production Switching Heuristics for the Aggregate Planning Problem

Author

Listed:
  • Joseph M. Mellichamp

    (University of Alabama)

  • Robert M. Love

    (Army Logistics Management Center, Fort Lee)

Abstract

A number of approaches to the aggregate planning problem have been proposed in the literature, yet experience suggests that industrial concerns seldom use these models in actual planning situations. This paper describes a modified random walk production-inventory heuristic for the problem which should appeal to managers on the basis of simplicity as well as efficiency. The proposed approach is contrasted with linear programming, parametric programming, and linear decision rule optimal and near optimal solutions for several well known production situations. The simple production switching heuristic produces schedules which exceed optimal schedules by only 1 to 2 percent of total production costs in all cases.

Suggested Citation

  • Joseph M. Mellichamp & Robert M. Love, 1978. "Production Switching Heuristics for the Aggregate Planning Problem," Management Science, INFORMS, vol. 24(12), pages 1242-1251, August.
    • Handle: RePEc:inm:ormnsc:v:24:y:1978:i:12:p:1242-1251
    DOI: 10.1287/mnsc.24.12.1242
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.24.12.1242
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.24.12.1242?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. Wu, Chia-Chin & Chang, Ni-Bin, 2004. "Corporate optimal production planning with varying environmental costs: A grey compromise programming approach," European Journal of Operational Research, Elsevier, vol. 155(1), pages 68-95, May.
    2. E J Levin & Y Ma & R E Wright, 2004. "Profit maximization in a multi-product firm with impatient customers," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(3), pages 211-218, March.
    3. Buxey, Geoff, 2003. "Strategy not tactics drives aggregate planning," International Journal of Production Economics, Elsevier, vol. 85(3), pages 331-346, September.
    4. Gomes da Silva, Carlos & Figueira, José & Lisboa, João & Barman, Samir, 2006. "An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming," Omega, Elsevier, vol. 34(2), pages 167-177, April.

    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:ormnsc:v:24:y:1978:i:12:p:1242-1251. 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.