基于改进遗传算法的无人机物流配送路径自动优化方法  

Automatic optimization method for unmanned aerial vehicle logistics delivery path based on improved genetic algorithm

作　　者：张宇 魏德宸 Zhang Yu;Wei Dechen(School of Mechanical and Electrical Engineering,Binzhou University,Binzhou 256600,China)

机构地区：[1]滨州学院机电工程学院,滨州256600

出　　处：《现代计算机》2023年第22期72-74,共3页Modern Computer

基　　金：国家级大学生创新创业训练项目(202210449006X);教育部产学合作协同育人项目(220603221230153)。

摘　　要：由于现有的优化方法路径数量多,配送效果差,为此研究基于改进遗传算法的无人机物流配送路径优化方法。首先,无人机配送站点在配送中,将配送站点服务范围内作为需求点进行配送选址;其次,在配送过程中,解决客户的时间窗问题;最后,从染色体编码开始,应用后改进遗传算法对物流配送路径进行自动优化,并将指令传达到无人机中达到配送自动化。实验结果表明,实验组的配送线路条数为3条,应用效果优于对比方法,提升了配送效率,达到最优配送效果。Due to the large number of paths and poor delivery performance of existing optimization methods,a drone logistics delivery path optimization method based on improved genetic algorithm is studied.Firstly,during the delivery process,the drone delivery site selects the service range of the delivery site as the demand point for delivery;Secondly,during the delivery process,address the customer’s time window issue;Finally,starting from chromosome encoding,the improved genetic algorithm is applied to automatically optimize the logistics delivery path and transmit instructions to the drone to achieve delivery automation.The experimental results show that the number of distribution routes in the experimental group is 3,and the application effect is better than the comparison method,improving the delivery efficiency and achieving the optimal delivery effect.

关 键 词：改进遗传算法 无人机 物流配送 路径优化 

分 类 号：V355[航空宇航科学与技术—人机与环境工程] TP18[自动化与计算机技术—控制理论与控制工程]