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Order batching in a pick-and-pass warehousing system with group genetic algorithm

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  • Pan, Jason Chao-Hsien
  • Shih, Po-Hsun
  • Wu, Ming-Hung

Abstract

An order batching policy determines how orders are combined to form batches. Previous studies on order batching policy focused primarily on classic manual warehouses, and its effect on pick-and-pass systems has rarely been discussed. Pick-and-pass systems, a commonly used warehousing installation for small to medium-sized items, play a key role in managing a supply chain efficiently because the fast delivery of small and frequent inventory orders has become a crucial trading practice because of the rise of e-commerce and e-business. This paper proposes an order batching approach based on a group genetic algorithm to balance the workload of each picking zone and minimize the number of batches in a pick-and-pass system in an effort to improve system performance. A simulation model based on FlexSim is used to implement the proposed heuristic algorithm, and compare the throughput for different order batching policies. The results reveal that the proposed heuristic policy outperforms existing order batching policies in a pick-and-pass system.

Suggested Citation

  • Pan, Jason Chao-Hsien & Shih, Po-Hsun & Wu, Ming-Hung, 2015. "Order batching in a pick-and-pass warehousing system with group genetic algorithm," Omega, Elsevier, vol. 57(PB), pages 238-248.
    • Handle: RePEc:eee:jomega:v:57:y:2015:i:pb:p:238-248
    DOI: 10.1016/j.omega.2015.05.004
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    References listed on IDEAS

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    Cited by:

    1. David Füßler & Nils Boysen & Konrad Stephan, 2019. "Trolley line picking: storage assignment and order sequencing to increase picking performance," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(4), pages 1087-1121, December.
    2. Zhuang, Yanling & Zhou, Yun & Yuan, Yufei & Hu, Xiangpei & Hassini, Elkafi, 2022. "Order picking optimization with rack-moving mobile robots and multiple workstations," European Journal of Operational Research, Elsevier, vol. 300(2), pages 527-544.
    3. Kaibo Liang & Li Zhou & Jianglong Yang & Huwei Liu & Yakun Li & Fengmei Jing & Man Shan & Jin Yang, 2023. "Research on a Dynamic Task Update Assignment Strategy Based on a “Parts to Picker” Picking System," Mathematics, MDPI, vol. 11(7), pages 1-29, March.
    4. Fangyu Chen & Gangyan Xu & Yongchang Wei, 2019. "An Integrated Metaheuristic Routing Method for Multiple-Block Warehouses with Ultranarrow Aisles and Access Restriction," Complexity, Hindawi, vol. 2019, pages 1-14, June.
    5. Dobromir Herzog, 2021. "Human factor aspects in information security management in the traditional IT and cloud computing models," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(2), pages 93-108.
    6. Zhang, Guoqing & Nishi, Tatsushi & Turner, Sarina D.O. & Oga, Keisuke & Li, Xindan, 2017. "An integrated strategy for a production planning and warehouse layout problem: Modeling and solution approaches," Omega, Elsevier, vol. 68(C), pages 85-94.
    7. van Gils, Teun & Caris, An & Ramaekers, Katrien & Braekers, Kris, 2019. "Formulating and solving the integrated batching, routing, and picker scheduling problem in a real-life spare parts warehouse," European Journal of Operational Research, Elsevier, vol. 277(3), pages 814-830.
    8. Polten, Lukas & Emde, Simon, 2021. "Scheduling automated guided vehicles in very narrow aisle warehouses," Omega, Elsevier, vol. 99(C).
    9. 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.
    10. Heiko Diefenbach & Simon Emde & Christoph H. Glock & Eric H. Grosse, 2022. "New solution procedures for the order picker routing problem in U-shaped pick areas with a movable depot," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(2), pages 535-573, June.
    11. Rafael Diaz, 2016. "Using dynamic demand information and zoning for the storage of non-uniform density stock keeping units," International Journal of Production Research, Taylor & Francis Journals, vol. 54(8), pages 2487-2498, April.
    12. Giannikas, Vaggelis & Lu, Wenrong & Robertson, Brian & McFarlane, Duncan, 2017. "An interventionist strategy for warehouse order picking: Evidence from two case studies," International Journal of Production Economics, Elsevier, vol. 189(C), pages 63-76.
    13. Ardjmand, Ehsan & Shakeri, Heman & Singh, Manjeet & Sanei Bajgiran, Omid, 2018. "Minimizing order picking makespan with multiple pickers in a wave picking warehouse," International Journal of Production Economics, Elsevier, vol. 206(C), pages 169-183.
    14. 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.
    15. Masae, Makusee & Glock, Christoph H. & Vichitkunakorn, Panupong, 2021. "A method for efficiently routing order pickers in the leaf warehouse," International Journal of Production Economics, Elsevier, vol. 234(C).

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