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An algorithm for dynamic order-picking in warehouse operations

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  • Lu, Wenrong
  • McFarlane, Duncan
  • Giannikas, Vaggelis
  • Zhang, Quan

Abstract

Warehousing has been traditionally viewed as a non-value-adding activity but in recent years a number of new developments have meant that supply chain logistics have become critical to profitability. This paper focuses specifically on order-picking which is a key factor affecting warehouse performance. Order picking is the operation of retrieving goods from specified storage locations based on customer orders. Today’s warehouses face challenges for greater responsiveness to customer orders that require more flexibility than conventional strategies can offer. Hence, dynamic order-picking strategies that allow for changes of pick-lists during a pick cycle have attracted attention recently. In this paper we introduce an interventionist routing algorithm for optimising the dynamic order-picking routes. The algorithm is tested using a set of simulations based on an industrial case example. The results indicate that under a range of conditions, the proposed interventionist routing algorithm can outperform both static and heuristic dynamic order-picking routing algorithms.

Suggested Citation

  • Lu, Wenrong & McFarlane, Duncan & Giannikas, Vaggelis & Zhang, Quan, 2016. "An algorithm for dynamic order-picking in warehouse operations," European Journal of Operational Research, Elsevier, vol. 248(1), pages 107-122.
    • Handle: RePEc:eee:ejores:v:248:y:2016:i:1:p:107-122
    DOI: 10.1016/j.ejor.2015.06.074
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. 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.
    3. Arbex Valle, Cristiano & Beasley, John E, 2020. "Order batching using an approximation for the distance travelled by pickers," European Journal of Operational Research, Elsevier, vol. 284(2), pages 460-484.
    4. 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.
    5. Boysen, Nils & de Koster, René & Weidinger, Felix, 2019. "Warehousing in the e-commerce era: A survey," European Journal of Operational Research, Elsevier, vol. 277(2), pages 396-411.
    6. Liu, He & Xu, Tianting & Jing, Shuai & Liu, Zhidong & Wang, Shouyang, 2023. "The interplay between logistics strategy and platform’s channel structure design in B2C platform market," European Journal of Operational Research, Elsevier, vol. 310(2), pages 812-833.
    7. Claeys, Dieter & Adan, Ivo & Boxma, Onno, 2016. "Stochastic bounds for order flow times in parts-to-picker warehouses with remotely located order-picking workstations," European Journal of Operational Research, Elsevier, vol. 254(3), pages 895-906.
    8. Li Zhou & Huwei Liu & Junhui Zhao & Fan Wang & Jianglong Yang, 2022. "Performance Analysis of Picking Routing Strategies in the Leaf Layout Warehouse," Mathematics, MDPI, vol. 10(17), pages 1-28, September.
    9. Neves-Moreira, Fábio & Amorim, Pedro, 2024. "Learning efficient in-store picking strategies to reduce customer encounters in omnichannel retail," International Journal of Production Economics, Elsevier, vol. 267(C).
    10. Nikolaos Chondromatidis & Anastasios Gialos & Vasileios Zeimpekis & Michael Madas, 2024. "Investigating the Impact of Completion Time and Perceived Workload in Pickers-to-Parts Order-Picking Technologies: Evidence from Laboratory Experiments," Logistics, MDPI, vol. 8(1), pages 1-15, January.
    11. Fangyu Chen & Yongchang Wei & Hongwei Wang, 2018. "A heuristic based batching and assigning method for online customer orders," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 640-685, December.
    12. 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).
    13. Onal, Sevilay & Zhu, Wen & Das, Sanchoy, 2023. "Order picking heuristics for online order fulfillment warehouses with explosive storage," International Journal of Production Economics, Elsevier, vol. 256(C).
    14. Nikolaos Chondromatidis & Anastasios Gialos & Vasileios Zeimpekis, 2022. "Investigating the Performance of the Order-Picking Process by Using Smart Glasses: A Laboratory Experimental Approach," Logistics, MDPI, vol. 6(4), pages 1-26, December.
    15. Lamballais, T. & Roy, D. & De Koster, M.B.M., 2017. "Estimating performance in a Robotic Mobile Fulfillment System," European Journal of Operational Research, Elsevier, vol. 256(3), pages 976-990.
    16. Kao, Ling-Jing & Chiu, Chih-Chou & Lin, Hung-Tse & Hung, Yun-Wei & Lu, Cheng-Chin, 2024. "Unveiling the dimensions of digital transformation: A comprehensive taxonomy and assessment model for business," Journal of Business Research, Elsevier, vol. 176(C).
    17. MacCarthy, Bart L. & Zhang, Lina & Muyldermans, Luc, 2019. "Best Performance Frontiers for Buy-Online-Pickup-in-Store order fulfilment," International Journal of Production Economics, Elsevier, vol. 211(C), pages 251-264.
    18. De Santis, Roberta & Montanari, Roberto & Vignali, Giuseppe & Bottani, Eleonora, 2018. "An adapted ant colony optimization algorithm for the minimization of the travel distance of pickers in manual warehouses," European Journal of Operational Research, Elsevier, vol. 267(1), pages 120-137.
    19. Seung Yoon Ko & Ratna Permata Sari & Muzaffar Makhmudov & Chang Seong Ko, 2020. "Collaboration Model for Service Clustering in Last-Mile Delivery," Sustainability, MDPI, vol. 12(14), pages 1-18, July.
    20. Antonio Maria Coruzzolo & Francesco Lolli & Elia Balugani & Elisa Magnani & Miguel Afonso Sellitto, 2023. "Order Picking Problem: A Model for the Joint Optimisation of Order Batching, Batch Assignment Sequencing, and Picking Routing," Logistics, MDPI, vol. 7(3), pages 1-18, September.
    21. Izabela Kudelska & Rafal Niedbal, 2021. "The Impact of Organizational Change on the Improvement of the Picking Process in a Logistics Center – A Case Study," European Research Studies Journal, European Research Studies Journal, vol. 0(2B), pages 882-892.
    22. Fabio Maximiliano Miguel & Mariano Frutos & Máximo Méndez & Fernando Tohmé & Begoña González, 2024. "Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System," Mathematics, MDPI, vol. 12(8), pages 1-23, April.

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