IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v26y1980i12p1258-1271.html
   My bibliography  Save this article

Optimal Multi-Level Lot Sizing for Requirements Planning Systems

Author

Listed:
  • Earle Steinberg

    (University of Houston)

  • H. Albert Napier

    (University of Houston)

Abstract

The wide spread use of advanced information systems such as Material Requirements Planning (MRP) has significantly altered the practice of dependent demand inventory management. Recent research has focused on development of multi-level lot sizing heuristics for such systems. In this paper, we develop an optimal procedure for the multi-period, multi-product, multi-level lot sizing problem by modeling the system as a constrained generalized network with fixed charge arcs and side constraints. The network permits us to relax some of the more restrictive assumptions of previous models such as those designed for product structures with single sources or successors. The solution to the resulting minimum cost flow problem yields optimal lot sizing decisions for all purchases as well as manufactured goods and components in all periods over a finite planning horizon. A simple illustration, beginning with a master production schedule and bills of material, illustrates the suitablility of this approach for modeling complex requirements planning systems. Optimal solutions obtained by this method may also be useful in comparing results obtained from future heuristic approaches which may be more computationally efficient.

Suggested Citation

  • Earle Steinberg & H. Albert Napier, 1980. "Optimal Multi-Level Lot Sizing for Requirements Planning Systems," Management Science, INFORMS, vol. 26(12), pages 1258-1271, December.
    • Handle: RePEc:inm:ormnsc:v:26:y:1980:i:12:p:1258-1271
    DOI: 10.1287/mnsc.26.12.1258
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.26.12.1258
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.26.12.1258?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. Gencer, Cevriye & Erol, Serpil & Erol, Yalcin, 1999. "A decision network algorithm for multi-stage dynamic lot sizing problems," International Journal of Production Economics, Elsevier, vol. 62(3), pages 281-285, September.
    2. Rajiv D. Banker & Robert J. Kauffman, 2004. "50th Anniversary Article: The Evolution of Research on Information Systems: A Fiftieth-Year Survey of the Literature in Management Science," Management Science, INFORMS, vol. 50(3), pages 281-298, March.
    3. Dellaert, N. & Jeunet, J. & Jonard, N., 2000. "A genetic algorithm to solve the general multi-level lot-sizing problem with time-varying costs," International Journal of Production Economics, Elsevier, vol. 68(3), pages 241-257, December.
    4. Xiao, Yiyong & Kaku, Ikou & Zhao, Qiuhong & Zhang, Renqian, 2011. "A reduced variable neighborhood search algorithm for uncapacitated multilevel lot-sizing problems," European Journal of Operational Research, Elsevier, vol. 214(2), pages 223-231, October.
    5. Grubbström, Robert W. & Tang, Ou, 2012. "The space of solution alternatives in the optimal lotsizing problem for general assembly systems applying MRP theory," International Journal of Production Economics, Elsevier, vol. 140(2), pages 765-777.
    6. Drexl, Andreas & Haase, Knut, 1995. "Proportional lotsizing and scheduling," International Journal of Production Economics, Elsevier, vol. 40(1), pages 73-87, June.
    7. Dellaert, N. P. & Jeunet, J., 2003. "Randomized multi-level lot-sizing heuristics for general product structures," European Journal of Operational Research, Elsevier, vol. 148(1), pages 211-228, July.
    8. Jörg Homberger, 2008. "A Parallel Genetic Algorithm for the Multilevel Unconstrained Lot-Sizing Problem," INFORMS Journal on Computing, INFORMS, vol. 20(1), pages 124-132, February.
    9. Drexl, Andreas & Haase, Knut, 1992. "A new type of model for multi-item capacitated dynamic lotsizing and scheduling," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 286, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    10. Kimms, Alf & Drexl, Andreas, 1996. "Multi-level lot sizing: A literature survey," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 405, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.

    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:26:y:1980:i:12:p:1258-1271. 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.