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JD.com: Operations Research Algorithms Drive Intelligent Warehouse Robots to Work

Author

Listed:
  • Hengle Qin

    (Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai 200433, China; Department of AI and Big Data, JD Logistics, JD.com, Beijing 100176, China)

  • Jun Xiao

    (Department of AI and Big Data, JD Logistics, JD.com, Beijing 100176, China)

  • Dongdong Ge

    (Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai 200433, China)

  • Linwei Xin

    (Booth School of Business, University of Chicago, Chicago, Illinois 60637)

  • Jianjun Gao

    (Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai 200433, China)

  • Simai He

    (Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai 200433, China)

  • Haodong Hu

    (Research Institute for Interdisciplinary Sciences, Shanghai University of Finance and Economics, Shanghai 200433, China)

  • John Gunnar Carlsson

    (Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, California 90089)

Abstract

JD.com pioneered same-day delivery as a standard service in China’s business-to-consumer e-commerce sector in 2010. To balance the urgent need to meet growing demands while maintaining high-quality logistics services, the company built intelligent warehouses that use analytics to significantly improve warehouse efficiency. The brain of the intelligent warehouse system is the dispatching algorithm for storage rack-moving robots, which makes real-time dispatching decisions among robots, racks, and workstations after solving large-scale integer programs in seconds. The intelligent warehouse technology has helped the company decrease its fulfillment expense ratio to a world-leading level of 6.5%. The construction of intelligent warehouses has led to estimated annual savings of hundreds of millions of dollars. In 2020, JD.com delivered 90% of its first-party-owned retail orders on the same day or on the day after the order was placed. The agility of such intelligent warehouses has allowed JD.com to handle 10 times the normal volume of orders during peak sales seasons and has also helped the company respond quickly to COVID-19 and ensure the rapid recovery of production capabilities.

Suggested Citation

  • Hengle Qin & Jun Xiao & Dongdong Ge & Linwei Xin & Jianjun Gao & Simai He & Haodong Hu & John Gunnar Carlsson, 2022. "JD.com: Operations Research Algorithms Drive Intelligent Warehouse Robots to Work," Interfaces, INFORMS, vol. 52(1), pages 42-55, January.
    • Handle: RePEc:inm:orinte:v:52:y:2022:i:1:p:42-55
    DOI: 10.1287/inte.2021.1100
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    References listed on IDEAS

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    Cited by:

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    9. Boysen, Nils & de Koster, René, 2025. "50 years of warehousing research—An operations research perspective," European Journal of Operational Research, Elsevier, vol. 320(3), pages 449-464.
    10. Russell Allgor & Tolga Cezik & Daniel Chen, 2023. "Algorithm for Robotic Picking in Amazon Fulfillment Centers Enables Humans and Robots to Work Together Effectively," Interfaces, INFORMS, vol. 53(4), pages 266-282, July.
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