A Vehicle Routing Problem for Multi-depot Collaborative Delivery Considering Common and Neighboring Customers
Abstract
Facing the challenges of delivery cost, efficiency, and security in modern logistics systems, this study investigates a realistic scenario where multiple logistics companies jointly serve a common customer base, and customers' parcels can be picked up by their neighboring customers. By integrating mobile lockers and drones into the delivery process, we propose a multi-depot collaborative delivery vehicle routing problem with common and neighboring customers, and formulate a corresponding mixed-integer programming model. To solve the problem efficiently, a hybrid heuristic algorithm combining Adaptive Large Neighborhood Search and Tabu Search is developed. Numerical experiments demonstrate that collaboration among depots based on common and neighboring customers offers significant advantages: It not only reduces delivery costs but also improves the utilization efficiency of mobile lockers and reduces the required number of lockers. Moreover, the greater the number of depots participating in collaborative delivery, the more pronounced the benefits.
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