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Optimal Wave Release Times for Order Fulfillment Systems with Deadlines

Author

Listed:
  • Erdem Çeven

    (The Logistics Institute Asia–Pacific National University of Singapore, Singapore 119613)

  • Kevin R. Gue

    (Department of Industrial Engineering, University of Louisville, Louisville, Kentucky 40292)

Abstract

Service performance of an order fulfillment system is mainly determined by how quickly and accurately it fills customer orders. A higher service level can be offered with a later cutoff time, before which customers are assured of receiving their orders. However, the desire to offer a later cutoff time must be tempered by the need to provide service at low cost, which means taking advantage of economies of scale in picking operations. To strike this balance, many distribution centers release orders in large batches called waves. We develop analytical models to determine the timing and the number of order waves for fulfillment systems that operate against a daily deadline. In a case study, we apply our theoretical models to data from a large distribution center and show that optimal wave releases could significantly improve on time shipments compared to an intuitive method.

Suggested Citation

  • Erdem Çeven & Kevin R. Gue, 2017. "Optimal Wave Release Times for Order Fulfillment Systems with Deadlines," Transportation Science, INFORMS, vol. 51(1), pages 52-66, February.
    • Handle: RePEc:inm:ortrsc:v:51:y:2017:i:1:p:52-66
    DOI: 10.1287/trsc.2015.0642
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. 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.
    2. Alexander M. Stroh & Alan L. Erera & Alejandro Toriello, 2022. "Tactical Design of Same-Day Delivery Systems," Management Science, INFORMS, vol. 68(5), pages 3444-3463, May.
    3. Waßmuth, Katrin & Köhler, Charlotte & Agatz, Niels & Fleischmann, Moritz, 2023. "Demand management for attended home delivery—A literature review," European Journal of Operational Research, Elsevier, vol. 311(3), pages 801-815.
    4. Zhong, Shuya & Giannikas, Vaggelis & Merino, Jorge & McFarlane, Duncan & Cheng, Jun & Shao, Wei, 2022. "Evaluating the benefits of picking and packing planning integration in e-commerce warehouses," European Journal of Operational Research, Elsevier, vol. 301(1), pages 67-81.
    5. Zhuang, Yanling & Zhou, Yun & Hassini, Elkafi & Yuan, Yufei & Hu, Xiangpei, 2022. "Rack retrieval and repositioning optimization problem in robotic mobile fulfillment systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    6. 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.
    7. Khir, Reem & Erera, Alan & Toriello, Alejandro, 2023. "Robust planning of sorting operations in express delivery systems," European Journal of Operational Research, Elsevier, vol. 306(2), pages 615-631.

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