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An Optimized Collaborative Routing Model for Trucks and Heterogeneous Drones in Delivery and Pickup Services
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DOI：10.1109/tits.2026.3704201.png)
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Abstract
En 中文
Addressing the “last mile” logistics challenge, this paper proposes a truck and heterogeneous drones collaborative routing problem (HCRP-DP) to efficiently meet the growing customer demands for delivery and pickup services at the lowest cost. An adaptive large neighborhood search algorithm based on the simulated annealing framework (ALNS-SA), is designed to solve HCRP-DP. It incorporates asynchronous drone operations and heterogeneous drone characteristics, with seven destructive operators and a heuristic repair operator to explore the solution space and speed up local search convergence. Comparatively, ALNS-SA significantly outperforms a state-of-the-art algorithm in convergence. The HCRP-DP model not only reduces service costs but also offers insights into how varying customer proportions affect model performance, providing valuable practical application guidance.
Keywords:
Logistics
truck and heterogeneous drones collaboration
delivery and pick-up services
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