The Cooperative Vehicle Routing Problem With Drones
研究了多个物流企业合作使用卡车和无人机进行农村配送的路径优化与成本分摊问题，发现采用卡车-无人机模式的企业能提高合作效率并降低自身成本。
Given the sparse demands and poor traffic conditions, rural logistics is still challenging in providing efficient yet cost-effective pickup and delivery service. To realize cost reduction and efficiency enhancement, we study a novel cooperative vehicle routing problem with drones (CoVRPDs) to address operational optimization and cost allocation among a coalition with multiple heterogeneous players and investigate how their heterogeneous operating modes (i.e., operating in a truck-drone or truck-only mode) influence cooperation efficiency and cost sharing. This problem is formulated to formally represent highly interactive and complex decisions, including online participation choice, customer assignment among copartners, and collaborative truck-drone routing scheduling involving vehicle matching, intersection scheduling, and transshipment management. To tackle this, we customize an adaptive neighborhood search metaheuristic by introducing a series of customer-level and route-level destroy and repair operators to solve operational optimization efficiently, then apply both the Shapley value and the equal profit method for fair cost allocation. Then, numerical studies demonstrate that the emerging truck-drone delivery mode within a cooperative framework offers substantial economic advantages. From coalition partners, those utilizing a truck-drone delivery can significantly improve the coalition’s efficiency and thereby share smaller coalition costs, encouraging more partners to adopt an efficient truck-drone mode. Further insights on the coalition efficiency and cost allocation are also offered.