IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v47y2015i7p728-738.html
   My bibliography  Save this article

An exact solution approach for the order batching problem

Author

Listed:
  • İbrahim Muter
  • Temel Öncan

Abstract

In this article, we deal with the Order Batching Problem (OBP) considering traversal, return, and midpoint routing policies. We consider the Set Partitioning Problem formulation of the OBP and develop a specially tailored column generation–based algorithm for this problem. We suggest acceleration techniques such as a column pool strategy and a relaxation of the column generation subproblem. Also, a specially devised upper-bounding procedure and a lower-bounding method based on column generation that is strengthened by adding subset-row inequalities are employed. According to the computational results, the proposed solution approach manages to solve OBP instances with up to 100 orders to optimality.

Suggested Citation

  • İbrahim Muter & Temel Öncan, 2015. "An exact solution approach for the order batching problem," IISE Transactions, Taylor & Francis Journals, vol. 47(7), pages 728-738, July.
    • Handle: RePEc:taf:uiiexx:v:47:y:2015:i:7:p:728-738
    DOI: 10.1080/0740817X.2014.991478
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0740817X.2014.991478
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0740817X.2014.991478?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. Minfang Huang & Qiong Guo & Jing Liu & Xiaoxu Huang, 2018. "Mixed Model Assembly Line Scheduling Approach to Order Picking Problem in Online Supermarkets," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    2. Çağla Cergibozan & A. Serdar Tasan, 2019. "Order batching operations: an overview of classification, solution techniques, and future research," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 335-349, January.
    3. Ahmad Ebrahimi & Hyun-woo Jeon & Sang-yeop Jung, 2023. "Improving Energy Consumption and Order Tardiness in Picker-to-Part Warehouses with Electric Forklifts: A Comparison of Four Evolutionary Algorithms," Sustainability, MDPI, vol. 15(13), pages 1-28, July.
    4. Muter, İbrahim, 2020. "Exact algorithms to minimize makespan on single and parallel batch processing machines," European Journal of Operational Research, Elsevier, vol. 285(2), pages 470-483.
    5. Pardo, Eduardo G. & Gil-Borrás, Sergio & Alonso-Ayuso, Antonio & Duarte, Abraham, 2024. "Order batching problems: Taxonomy and literature review," European Journal of Operational Research, Elsevier, vol. 313(1), pages 1-24.
    6. van Gils, Teun & Ramaekers, Katrien & Braekers, Kris & Depaire, Benoît & Caris, An, 2018. "Increasing order picking efficiency by integrating storage, batching, zone picking, and routing policy decisions," International Journal of Production Economics, Elsevier, vol. 197(C), pages 243-261.
    7. Wagner, Stefan & Mönch, Lars, 2023. "A variable neighborhood search approach to solve the order batching problem with heterogeneous pick devices," European Journal of Operational Research, Elsevier, vol. 304(2), pages 461-475.
    8. Grzegorz Tarczyński, 2023. "Linear programming models for optimal workload and batching in pick-and-pass warehousing systems," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(3), pages 141-158.
    9. Çağla Cergibozan & A. Serdar Tasan, 2022. "Genetic algorithm based approaches to solve the order batching problem and a case study in a distribution center," Journal of Intelligent Manufacturing, Springer, vol. 33(1), pages 137-149, January.
    10. Yang, Peng & Zhao, Zhijie & Guo, Huijie, 2020. "Order batch picking optimization under different storage scenarios for e-commerce warehouses," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).

    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:47:y:2015:i:7:p:728-738. 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.