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A Data Mining Technique to Grouping Customer Orders in Warehouse Management System

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Soft Computing as Transdisciplinary Science and Technology

Part of the book series: Advances in Soft Computing ((AINSC,volume 29))

Abstract

Warehouse management system (WMS) today is viewed as a basis to reinforcing company logistics. Order picking is one of the routine operations in warehouses. Before picking a large amount of orders, effectively grouping orders into batches can speed up product movement within the warehouse. Several batching heuristics have been proposed in the literature for minimizing travel distance or travel time. This paper presents an order batching approach in a distribution center with a parallel-aisle layout. A heuristic order batching approach based on data mining is developed in this paper.

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Author information

Authors and Affiliations

  1. Institute of Commerce Automation and Management, National Taipei University of Technology, Taiwan, ROC

    Mu-Chen Chen, Ming-Fu Hsu & Fei-Hou Hsu

  2. Department of Information Management, National Kaohsiung First University of Science and Technology, Taiwan, ROC

    Cheng-Lung Huang

  3. Information System Department, Chinese Petroleum Corporation, Taiwan, ROC

    Hsiao-Pin Wu

Authors
  1. Mu-Chen Chen
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  2. Cheng-Lung Huang
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  3. Hsiao-Pin Wu
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  4. Ming-Fu Hsu
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  5. Fei-Hou Hsu
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science, Oklahoma State University, North Greenwood Avenue 700, 74106, Tulsa, USA

    Ajith Abraham

  2. Dept. of Computer Science and Systems Engineering, Muroran Institute of Technology, Mizumoto-cho 27-1, 050-8585, Muroran, Hokkaido, Japan

    Yasuhiko Dote

  3. Dept. of Computational Science and Engineering, Nagoya University, Furo-cho, Chikusa-ku, 464-8601, Nagoya, Aichi-ken, Japan

    Takeshi Furuhashi

  4. Institut für Sicherheits-/Prüftechnik, Fraunhofer IPK Berlin, Pascalstr. 8-9, 10587, Berlin, Germany

    Mario Köppen

  5. Division of Complex Systems Technology Graduate School of Engineering, University of Hokkaido, N-13, W-8 060 KITA-KU, Sapporo, Japan

    Azuma Ohuchi

  6. PRESTO Japan Science & Technology Corp. GSSM, University of Tsukuba, 3-29-1 Otsuka, Bunkyo-ku, 12-0012, Tokyo, Japan

    Yukio Ohsawa

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© 2005 Springer-Verlag Berlin Heidelberg

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Chen, MC., Huang, CL., Wu, HP., Hsu, MF., Hsu, FH. (2005). A Data Mining Technique to Grouping Customer Orders in Warehouse Management System. In: Abraham, A., Dote, Y., Furuhashi, T., Köppen, M., Ohuchi, A., Ohsawa, Y. (eds) Soft Computing as Transdisciplinary Science and Technology. Advances in Soft Computing, vol 29. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32391-0_109

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  • DOI: https://doi.org/10.1007/3-540-32391-0_109

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25055-5

  • Online ISBN: 978-3-540-32391-4

  • eBook Packages: EngineeringEngineering (R0)

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