基于两阶段法的车+无人机配送模式路径研究

Research on the Path of Vehicle+UAV Delivery Model Based on a Two-stage Approach

随着电商的不断发展及线上订单的激增,给物流行业带来了巨大的压力。综合考虑无人机载重和续航里程等因素,以卡车和无人机配送总成本最小化为目标,建立车协同无人机配送的数学模型。并设计了两阶段方法求解数学模型,首先利用K-means聚类算法求出卡车配送点,再用离散人工萤火虫算法求解无人机最短配送路径,最终依据模型得出配送总成本。算例仿真表明,离散人工萤火虫算法比传统蚁群算法、粒子群算法具有更好的寻优能力,车协同无人机配送模式比传统的单独车辆配送模式成本更低,减少了53%,为解决物流行业配送压力问题提供一种有效的解决方案。

With the continuous development of e-commerce and the surge of online orders,it has brought tremendous pressure to the logistics industry.Considering factors such as UAV load and range,the mathematical model of vehicle-coordinated UAV delivery is established with the goal of minimizing the total cost of truck and UAV delivery.The two-stage method is designed to solve the mathematical model,firstly,the truck delivery point is found by K-means clustering algorithm,then the shortest delivery path of UAV is solved by discrete artificial firefly algorithm,and finally the total cost of delivery is derived based on the model.The simulation shows that the discrete artificial firefly algorithm has a better optimization capability than the traditional ant colony algorithm and particle swarm algorithm,and the vehicle cooperative UAV delivery mode has a lower cost of 53%than the traditional separate vehicle delivery mode,which provides an effective solution to solve the distribution pressure problem in the logistics industry.