Work

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

Year: 2025

Type: article

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.

Source: Transportation Research Part E Logistics and Transportation Review

DOI: 10.1016/j.tre.2025.104505

Authors: Dapei Jiang, Xiangyong Li, Wei Yang, Yuxuan Zhao

Institutions: Shenzhen Institute of Information Technology, Tongji University

Language: English

Topic: Urban and Freight Transport Logistics

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $4,240