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An integrated optimization approach for e-order fulfillment using self-owned and crowdsourced delivery

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  • Jiang, Dapei
  • Li, Xiangyong
  • Yang, Wei
  • Zhao, Yuxuan

Abstract

In this paper, we investigate the e-order fulfillment problem with crowdsourced delivery personnel (EOFP-CDP), which aims to enhance order fulfillment performance by integrating crowdsourced delivery with self-owned logistics. We begin by presenting a mixed-integer programming formulation that enables the determination of optimal solutions for small-scale instances, capturing the complexities of the problem. We then propose a heuristic algorithm that combines adaptive large neighborhood search with variable neighborhood search. Through extensive experiments, we demonstrate the effectiveness of this algorithm in improving e-order fulfillment performance. We also conduct a comprehensive sensitivity analysis to examine the impact of crowdsourced delivery on e-order fulfillment. Specifically, we explore the role of key cost factors–such as travel, loading, and time costs–associated with crowdsourced delivery personnel and their influence on fulfillment outcomes. Finally, a case study based on JD.com validates the practical advantages of the consolidation-delivery mode within e-tailer fulfillment systems.

Suggested Citation

  • Jiang, Dapei & Li, Xiangyong & Yang, Wei & Zhao, Yuxuan, 2026. "An integrated optimization approach for e-order fulfillment using self-owned and crowdsourced delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 205(C).
    • Handle: RePEc:eee:transe:v:205:y:2026:i:c:s1366554525005332
    DOI: 10.1016/j.tre.2025.104505
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