Advances in Production Engineering & Management
Volume 21 | Number 1 | March 2026 | pp 139–155
https://doi.org/10.14743/apem2026.1.566
A human-robot collaborative delivery model for instant orders in metropolitan areas
Xie, X.L.; Chen, X.; Wu, J.Y.; Zhang, X.F.; Kong, L.K.; Xiao, Y.
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A B S T R A C T
In metropolitan instant delivery systems, rising operational costs and poor delivery timeliness pose significant challenges. This study addresses these issues by investigating optimal order allocation and route optimization in a hybrid delivery system that integrates autonomous delivery vehicles (ADVs) with human riders. Analysis of historical order data indicates that inefficient order assignment between ADVs and riders is a major operational bottleneck. To address this problem, a collaborative human-ADV delivery model is formulated with the objective of minimizing total logistics costs under constraints related to delivery time windows, vehicle capacity, and routing requirements. The proposed model is applied to a real-world case involving QX Fresh Supermarket, comprising 80 orders and 16 community transfer points. An improved genetic algorithm is developed to solve the optimization problem efficiently. Empirical results for off-peak, normal, and peak periods show that the collaborative delivery approach significantly improves ADV utilization and reduces total delivery costs by more than 30 % without compromising timeliness. These findings provide both a sound theoretical basis and practical guidance for the advancement of human-machine collaborative logistics.
A R T I C L E I N F O
Keywords • Instant delivery; Unmanned delivery vehicle; Human-robot collaboration; Order allocation; Route optimization; Genetic algorithm; Last-mile logistics
Corresponding author • Xie, X.L.
Article history • Received 1 December 2025, Revised 7 April 2026, Accepted 10 April 2026
Published on-line • 29 April 2026
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