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Order picker routing with product returns and interaction delays

Author

Listed:
  • Albert H. Schrotenboer
  • Susanne Wruck
  • Kees Jan Roodbergen
  • Marjolein Veenstra
  • Arjan S. Dijkstra

Abstract

E-commerce companies often use manual order-picking systems in their warehouses since these systems can provide the required flexibility and scalability. Manual systems have been widely studied, but the operating policies may require significant changes for e-commerce settings. First, to maintain consumers’ loyalty, it is important to maintain delivery reliability even on the busiest days. When the number of order pickers in an area increases, however, more delays due to interactions may occur. For example, travel speed may need to be lowered when order pickers pass each other in narrow aisles. Second, many products sold through e-commerce are returned by consumers. Before these returned products can be sold again, they must be reintegrated in the stock. This paper presents hybrid genetic algorithms to determine routes for simultaneous pickup of products in response to consumers’ orders and delivery of returned products to storage locations. Furthermore, interactions between the order pickers are considered in the routing decisions. The developed algorithms use specific warehouse problem characteristics. We identify the mix of pickups and deliveries to realise the highest savings in practice. It is shown that order-picker interactions can be a significant cause for delay and should be accounted for in the routing.

Suggested Citation

  • Albert H. Schrotenboer & Susanne Wruck & Kees Jan Roodbergen & Marjolein Veenstra & Arjan S. Dijkstra, 2017. "Order picker routing with product returns and interaction delays," International Journal of Production Research, Taylor & Francis Journals, vol. 55(21), pages 6394-6406, November.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:21:p:6394-6406
    DOI: 10.1080/00207543.2016.1206982
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    Citations

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    Cited by:

    1. Emde, Simon & Tahirov, Nail & Gendreau, Michel & Glock, Christoph H., 2021. "Routing automated lane-guided transport vehicles in a warehouse handling returns," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1085-1098.
    2. Silva, Allyson & Roodbergen, Kees Jan & Coelho, Leandro C. & Darvish, Maryam, 2022. "Estimating optimal ABC zone sizes in manual warehouses," International Journal of Production Economics, Elsevier, vol. 252(C).
    3. Maximilian Löffler & Michael Schneider & Ivan Žulj, 2023. "Cost-neutral reduction of infection risk in picker-to-parts warehousing systems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 151-179, March.
    4. Umair Akram & Melinda Timea Fülöp & Adriana Tiron-Tudor & Dan Ioan Topor & Sorinel Căpușneanu, 2021. "Impact of Digitalization on Customers’ Well-Being in the Pandemic Period: Challenges and Opportunities for the Retail Industry," IJERPH, MDPI, vol. 18(14), pages 1-21, July.
    5. 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.
    6. Yang, Peng & Zhao, Zhijie & Guo, Huijie, 2020. "Order batch picking optimization under different storage scenarios for e-commerce warehouses," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).

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