InCo: Exploring Inter-Trip Cooperation for Efficient Last-mile Delivery

An efficient last-mile delivery scheme in logistics benefits customers, couriers, and the platform. In practice, the delivery scope of a delivery station is divided into multiple areas, each of which is covered by a courier. The long distances between the delivery station and areas limit the couriers' delivery efficiency given that they need to travel back and forth multiple times a day. To solve this problem, we explore an inter-trip cooperation scheme for last-mile delivery, in which couriers traveling to the delivery station and back to corresponding areas earlier can help to take others' orders back. Coordinating the courier cooperation is challenging because we need to consider the courier's status, e.g., locations, and vehicle capacity constraint simultaneously. In this work, we design an inter-trip cooperation-based last-mile delivery system, InCo, aiming to minimize the average order delivery time. InCo includes two components: i) a time-aware spanning tree algorithm to generate the cooperation result for a group of couriers; and ii) a capacity-constrained courier grouping algorithm to optimize the courier grouping result iteratively. Extensive evaluation results with real-world order data collected from one of the largest logistics companies show that InCo improves the average saved delivery time and reduces average travel time by up to 80.2% and 28.4%, respectively, compared to baseline methods. The deployment results show InCo improves the average courier working efficiency by 21.6% to the state-of-the-practice.

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Publication Details

Published
2025-04-22
DOI
https://doi.org/10.1145/3696410.3714483
Citations
4
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
2.73

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article

InCo: Exploring Inter-Trip Cooperation for Efficient Last-mile Delivery

Shuxin Zhong, Yi Ding, Tian He, Wenjun Lyu et al.
4 citations
Transportation and Mobility Innovations
2.73
article

InCo: Exploring Inter-Trip Cooperation for Efficient Last-mile Delivery

Shuxin Zhong, Yi Ding, Tian He, Wenjun Lyu, Yunhuai Liu, Shuai Wang, Desheng Zhang, Haotian Wang, Guang Yang
article en
4 citations

Abstract

An efficient last-mile delivery scheme in logistics benefits customers, couriers, and the platform. In practice, the delivery scope of a delivery station is divided into multiple areas, each of which is covered by a courier. The long distances between the delivery station and areas limit the couriers' delivery efficiency given that they need to travel back and forth multiple times a day. To solve this problem, we explore an inter-trip cooperation scheme for last-mile delivery, in which couriers traveling to the delivery station and back to corresponding areas earlier can help to take others' orders back. Coordinating the courier cooperation is challenging because we need to consider the courier's status, e.g., locations, and vehicle capacity constraint simultaneously. In this work, we design an inter-trip cooperation-based last-mile delivery system, InCo, aiming to minimize the average order delivery time. InCo includes two components: i) a time-aware spanning tree algorithm to generate the cooperation result for a group of couriers; and ii) a capacity-constrained courier grouping algorithm to optimize the courier grouping result iteratively. Extensive evaluation results with real-world order data collected from one of the largest logistics companies show that InCo improves the average saved delivery time and reduces average travel time by up to 80.2% and 28.4%, respectively, compared to baseline methods. The deployment results show InCo improves the average courier working efficiency by 21.6% to the state-of-the-practice.

Rutgers, The State University of New Jersey (US), The University of Texas at Dallas (US), Peking University (CN), Jingdong (China) (CN), Southeast University (CN)
National Natural Science Foundation of China, Jiangsu Provincial Key Research and Development Program
Partnerships for the goals
Openalex Percentile: Top 10%
Transportation and Mobility Innovations
2.73
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