无人机与卡车多组合配送问题研究  

Multi-combination Distribution of Drones and Trucks

作　　者：孔紫维 刘翱[1,2] 任亮[1,2] 李儒博 KONG Ziwei;LIU Ao;REN Liang;LI Rubo(School of Management,Wuhan University of Science and Technology,Wuhan 430065,China;Center for Service Science and Engineering,Wuhan University of Science and Technology,Wuhan 430065,China)

机构地区：[1]武汉科技大学管理学院,湖北武汉430065 [2]武汉科技大学服务科学与工程研究中心,湖北武汉430065

出　　处：《物流科技》2024年第19期11-16,27,共7页Logistics Sci Tech

基　　金：教育部人文社会科学研究规划基金项目(21YJAZH050);湖北省教育厅哲学社会科学研究重点项目(22D022);武汉市知识创新专项曙光计划项目(2022010801020317);湖北省高等学校优秀中青年科技创新团队计划项目(T2022003);武汉科技大学资助项目“智慧物流数字运营平台开发研究”(2022H20537)。

摘　　要：由于城市配送场景的复杂性,无人机开始被应用于“最后一公里”配送,但无人机配送受到其飞行距离与载重等限制,无人机与卡车组合配送得到广泛关注。结合卡车与无人机配送特点,研究了一类考虑无人机与卡车多组合下的配送路径优化问题;在考虑无人机的飞行范围与载荷等因素下,建立以总配送成本最小化的整数规划模型,并设计了结合改进K-means聚类搜索的混合变邻域搜索算法求解该问题。算例结果验证了所提模型的可行性和所设计算法的有效性,通过与其他配送方式相比,成本最高节约达22%,且随着算例规模扩大,成本节约不断增加,为实现城市地区末端物流的降本增效提供了决策参考和依据。Due to the complexity of urban distribution scenarios,drones are beginning to be applied to the"last kilometer"distribution,but drone distribution is limited by its flight range and load,so the combination of drones and trucks for distribution has gained wide attention.Combining the characteristics of truck and UAV delivery,a delivery path optimization problem considering multiple combinations of UAVs and trucks is investigated.Under the consideration of the flight range and load of UAVs,an integer planning model is established to minimize the total delivery cost,and a hybrid variable neighborhood search algorithm combined with improved K-means clustering search is designed to solve the problem.The results verify the feasibility of the proposed model and the validity of the designed algorithm,and the cost saving is up to 22%compared with other distribution methods,and the cost saving increases with the expansion of the scale of the example,which provides decision-making references and bases for the realization of cost reduction and efficiency of the terminal logistics in urban areas.

关 键 词：无人机 路径规划 变邻域搜索 组合配送 城市配送 

分 类 号：F252.14[经济管理—国民经济]