IDEAS home Printed from https://ideas.repec.org/a/wly/isacfm/v14y2006i1-2p3-25.html
   My bibliography  Save this article

On the design of a real‐time knowledge‐based system for managing logistics operations

Author

Listed:
  • K. H. Chow
  • K. L. Choy
  • W. B. Lee

Abstract

Over the past 10 years, various kinds of logistics information systems have been developed to store and process all sorts of data and information to support daily logistics operations. However, the logistics planning or decision‐making of logistics activity is still executed manually. In this paper, a real‐time knowledge‐based system (RKBS) is designed to support logistic service providers in making decisions during the stage of logistics planning and operation by extracting, sharing and storing real‐time logistics knowledge. The proposed system, which is suitable for usage in different business processes in a warehouse operating environment, is developed by integrating radio‐frequency identification, online analytical processing, case‐based reasoning technologies, and a branch‐and‐bound resource‐route‐optimizing programming model. Through applying the RKBS in GENCO, a US‐based logistics service company, the overall logistics servicing level is enhanced through accurate decision‐making and planning of warehouse operations. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • K. H. Chow & K. L. Choy & W. B. Lee, 2006. "On the design of a real‐time knowledge‐based system for managing logistics operations," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 14(1‐2), pages 3-25, January.
    • Handle: RePEc:wly:isacfm:v:14:y:2006:i:1-2:p:3-25
    DOI: 10.1002/isaf.274
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/isaf.274
    Download Restriction: no
    File URL: https://libkey.io/10.1002/isaf.274?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
    ---><---

    References listed on IDEAS

    as
    1. Liao, Shu-hsien, 2000. "Case-based decision support system: Architecture for simulating military command and control," European Journal of Operational Research, Elsevier, vol. 123(3), pages 558-567, June.
    2. Berg, J. P. van den & Zijm, W. H. M., 1999. "Models for warehouse management: Classification and examples," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 519-528, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dario Pacciarelli & Andrea D’Ariano & Michele Scotto, 2011. "Applying RFID in warehouse operations of an Italian courier express company," Netnomics, Springer, vol. 12(3), pages 209-222, October.
    2. Chen, Lu & Langevin, André & Riopel, Diane, 2011. "A tabu search algorithm for the relocation problem in a warehousing system," International Journal of Production Economics, Elsevier, vol. 129(1), pages 147-156, January.
    3. Gianluca Nastasi & Valentina Colla & Silvia Cateni & Simone Campigli, 2018. "Implementation and comparison of algorithms for multi-objective optimization based on genetic algorithms applied to the management of an automated warehouse," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1545-1557, October.
    4. Gagliardi, Jean-Philippe & Ruiz, Angel & Renaud, Jacques, 2008. "Space allocation and stock replenishment synchronization in a distribution center," International Journal of Production Economics, Elsevier, vol. 115(1), pages 19-27, September.
    5. Kalloniatis, Alexander C. & McLennan-Smith, Timothy A. & Roberts, Dale O., 2020. "Modelling distributed decision-making in Command and Control using stochastic network synchronisation," European Journal of Operational Research, Elsevier, vol. 284(2), pages 588-603.
    6. de Jesus Pacheco, Diego Augusto & Møller Clausen, Daniel & Bumann, Jendrik, 2023. "A multi-method approach for reducing operational wastes in distribution warehouses," International Journal of Production Economics, Elsevier, vol. 256(C).
    7. Anderson Rogério Faia Pinto & Antonio Fernando Crepaldi & Marcelo Seido Nagano, 2018. "A Genetic Algorithm applied to pick sequencing for billing," Journal of Intelligent Manufacturing, Springer, vol. 29(2), pages 405-422, February.
    8. Yu, Y. & de Koster, M.B.M., 2009. "On the Suboptimality of Full Turnover-Based Storage," ERIM Report Series Research in Management ERS-2009-051-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    9. Zachary Steever & Chase Murray & Junsong Yuan & Mark Karwan & Marco Lübbecke, 2022. "An Image-Based Approach to Detecting Structural Similarity Among Mixed Integer Programs," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 1849-1870, July.
    10. Liu, Jiawen & Gong, Yeming (Yale) & Zhu, Joe & Zhang, Jinlong, 2018. "A DEA-based approach for competitive environment analysis in global operations strategies," International Journal of Production Economics, Elsevier, vol. 203(C), pages 110-123.
    11. Dilip Kumar Sen & Saurav Datta & Siba Sankar Mahapatra, 2017. "Decision Support Framework for Selection of 3PL Service Providers: Dominance-Based Approach in Combination with Grey Set Theory," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 25-57, January.
    12. de Koster, M.B.M. & Le-Duc, T. & Roodbergen, K.J., 2006. "Design and Control of Warehouse Order Picking: a literature review," ERIM Report Series Research in Management ERS-2006-005-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    13. Valentin Carlan & David Ceulemans & Edwin Hassel & Stijn Derammelaere & Thierry Vanelslander, 2023. "Automation in cargo loading/unloading processes: do unmanned loading technologies bring benefits when both purchase and operational cost are considered?," Journal of Shipping and Trade, Springer, vol. 8(1), pages 1-25, December.
    14. Vidal Vieira, José Geraldo & Ramos Toso, Milton & da Silva, João Eduardo Azevedo Ramos & Cabral Ribeiro, Priscilla Cristina, 2017. "An AHP-based framework for logistics operations in distribution centres," International Journal of Production Economics, Elsevier, vol. 187(C), pages 246-259.
    15. Matthews, Jason & Visagie, Stephan, 2013. "Order sequencing on a unidirectional cyclical picking line," European Journal of Operational Research, Elsevier, vol. 231(1), pages 79-87.
    16. Lehnfeld, Jana & Knust, Sigrid, 2014. "Loading, unloading and premarshalling of stacks in storage areas: Survey and classification," European Journal of Operational Research, Elsevier, vol. 239(2), pages 297-312.
    17. 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.
    18. de Koster, Rene & Le-Duc, Tho & Roodbergen, Kees Jan, 2007. "Design and control of warehouse order picking: A literature review," European Journal of Operational Research, Elsevier, vol. 182(2), pages 481-501, October.
    19. Bouzekri, Hamza & Bara, Najat & Alpan, Gülgün & Giard, Vincent, 2022. "An integrated Decision Support System for planning production, storage and bulk port operations in a fertilizer supply chain," International Journal of Production Economics, Elsevier, vol. 252(C).
    20. Strack, Géraldine & Pochet, Yves, 2010. "An integrated model for warehouse and inventory planning," European Journal of Operational Research, Elsevier, vol. 204(1), pages 35-50, July.

    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:wly:isacfm:v:14:y:2006:i:1-2:p:3-25. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1099-1174/ .

    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.