Authors

Abstract

In order to solve the difficulties in logistics distribution in remote rural areas, a systematic planning of agricultural logistics distribution for UAV distribution is carried out. Considering the limit of cruising range, from the perspective of green routing, a multi-package distribution path planning model of UAV agricultural logistics considering the limitation of cruising range of UAV is established with the goal of minimizing total energy consumption. According to the actual number of UAVs, the task allocation is carried out, and a mixed integer nonlinear programming model of task allocation is established. The improved ant colony algorithm is used to solve the problem. The core idea is to exchange the pheromones of each ant subgroup, and then use the insertion-based heuristic method and crossover and inversion operations to optimize the path. For the case of remote areas in western China, the agricultural UAV distribution path planning considering the mileage limit is conducive to saving resources and obtaining the lowest energy consumption distribution path ; for the problem of agricultural logistics distribution path planning considering the mileage limit of UAV, the improved ant colony algorithm designed in this study has higher solution accuracy than the traditional ant colony algorithm.

Abstract in Chinese

为解决偏远农村地区物流配送存在的困难,对无人机配送进行农业物流配送系统性规划,考虑到续航里程限度,从绿色路由的角度,以最小化总能耗作为目标,建立了考虑无人机续航里程限制的无人机农业物流多包裹配送路径规划模型；根据实际无人机数量进行任务分配,建立了任务分配混合整数非线性规划模型,采用改进蚁群算法求解,其核心思想是将各个蚂蚁子群的信息素进行交换,再采用基于插入的启发式方法和交叉、反转操作进行路径优化,经过对照实验。对于我国西部偏远地区的案例,考虑续航里程限制的农业无人机配送路径规划有利于节约资源,能得到能耗最低的配送路径；对于考虑无人机续航里程限制的农业物流配送路径规划问题,本文设计的改进蚁群算法与传统蚁群算法相比,本文改进蚁群算法具有较高的求解精确度。