IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v51y2019i5p456-485.html
   My bibliography  Save this article

The buffer allocation problem in production lines: Formulations, solution methods, and instances

Author

Listed:
  • Sophie Weiss
  • Justus Arne Schwarz
  • Raik Stolletz

Abstract

Flow production lines with finite buffer capacities are used in practice for mass production, e.g., in the automotive and food industries. The decision regarding the allocation of buffer capacities to mitigate throughput losses from stochastic processing times and unreliable stations is known as the Buffer Allocation Problem (BAP). This article classifies and reviews the literature on the BAP with respect to different versions of the optimization problem. It considers the detailed characteristics of the flow lines, the objective function, and the constraints. Moreover, a new classification scheme for solution methods is presented that differentiates between explicit solutions, integrated optimization methods, and iterative optimization methods. The characteristics of test instances derived from realistic cases and test instances used in multiple references are discussed. The review reveals gaps in the literature regarding the considered optimization problems and solution methods, especially with a view on realistic lines. In addition, a library, FlowLineLib, of realistic and already used test instances is provided.

Suggested Citation

  • Sophie Weiss & Justus Arne Schwarz & Raik Stolletz, 2019. "The buffer allocation problem in production lines: Formulations, solution methods, and instances," IISE Transactions, Taylor & Francis Journals, vol. 51(5), pages 456-485, May.
    • Handle: RePEc:taf:uiiexx:v:51:y:2019:i:5:p:456-485
    DOI: 10.1080/24725854.2018.1442031
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/24725854.2018.1442031
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/24725854.2018.1442031?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.

    Citations

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


    Cited by:

    1. Mehmet Ulaş Koyuncuoğlu & Leyla Demir, 2021. "A comparison of combat genetic and big bang–big crunch algorithms for solving the buffer allocation problem," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1529-1546, August.
    2. Romero-Silva, Rodrigo & Shaaban, Sabry & Marsillac, Erika & Laarraf, Zouhair, 2021. "The impact of unequal processing time variability on reliable and unreliable merging line performance," International Journal of Production Economics, Elsevier, vol. 235(C).
    3. Ziwei Lin & Nicla Frigerio & Andrea Matta & Shichang Du, 2021. "Multi-fidelity surrogate-based optimization for decomposed buffer allocation problems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 223-253, March.
    4. Bengisu Urlu & Nesim K. Erkip, 2020. "Safety stock placement for serial systems under supply process uncertainty," Flexible Services and Manufacturing Journal, Springer, vol. 32(2), pages 395-424, June.

    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:taf:uiiexx:v:51:y:2019:i:5:p:456-485. 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 Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/uiie .

    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.