城市物流无人机起飞时刻排序问题研究

Research on the Scheduling Problem of Urban Logistics UAV’s Take-off Time

文中基于动态优先级计算了无人机起飞的时刻及起飞顺序.选取货物价值、收货点距离和最晚收货时间作为影响排序的主要因素,根据熵权法判断不同影响因素对物流订单优先级的影响程度,结合模糊聚类与三维优先级表调度规则判定物流订单的任务优先水平.并根据订单优先级设定延误成本系数,以最小总延误成本为目标构建物流无人机起飞时刻排序模型;提出相应的改进遗传算法对模型进行求解.数值仿真实验结果表明:所提方法可以安全高效地安排无人机起飞队列顺序,降低无人机配送的总延误成本.

Based on the dynamic priority,the take-off time and take-off sequence of UAV were calculated.The value of goods,the distance from the receiving point and the latest receiving time were selected as the main factors affecting the sequencing,and the influence degree of different influencing factors on the priority of logistics orders was judged according to the entropy weight method.Fuzzy clustering and three-dimensional priority table scheduling rules were combined to determine the task priority level of logistics orders.According to the order priority,the delay cost coefficient was set,and the take-off time sequencing model of logistics UAV was constructed with the minimum total delay cost as the goal,and the corresponding improved genetic algorithm was proposed to solve the model.The numerical simulation results show that the proposed method can safely and efficiently arrange the take-off queue of UAVs and reduce the total delay cost of UAV distribution.