摘要
为应对多仓库多配送点的物流配送中数据处理量大、部分仓库货物量不充足的情况,提出面向多仓库多配送点的物流配送路径规划算法。该算法以最小化物流运输成本和运输路径长度为目标,构建物流配送路径规划模型,利用网络Voronoi图初始化分割多仓库至多配送点的物流配送区域,进行配送区域边界修正,并为每个仓库物流配送服务区域内的车辆选取初始路径。基于粒子群算法实现各个仓库配送范围内的路径寻优,获取最优的多仓库多配送点物流配送路径规划结果。实验结果显示,该算法获取的路径规划结果可降低物流运输成本、缩短运输路径长度并减少运输所需车辆的数量,能够有效应对仓库货物不充足的情况,实现更高效的路径规划,提高配送准时率。
In order to deal with the large amount of data processing and the insufficient amount of goods in some warehouses in the logistics distribution of multi-warehouse and multi-distribution point,a logistics distribution path planning algorithm for multi-warehouse and multi-distribution point is proposed.The algorithm aims to minimize logistics transportation costs and transportation path lengths,constructs the logistics distribution path planning model,initializes and divides the logistics distribution area of multi-warehouse to multi-distribution point by using the network Voronoi diagram,corrects the boundary of the distribution area,and selects the initial path for the vehicles in the logistics distribution service area of each warehouse.Based on the Particle Swarm Optimization algorithm,the path optimization within the distribution scope of each warehouse is realized,and the optimal multi-warehouse multi-distribution point logistics distribution path planning result is obtained.The experimental results show that the path planning results obtained by the algorithm can reduce the logistics transportation cost,shorten the length of the transportation path and reduce the number of vehicles required for transportation.It can effectively deal with the situation of insufficient warehouse goods,achieve more efficient path planning,and improve the delivery punctuality rate.
作者
倪利
NI Li(Guangdong Polytechnic of Industry and Commerce,Guangzhou 510510,China)
出处
《现代信息科技》
2025年第14期72-77,83,共7页
Modern Information Technology
关键词
多仓库
多配送点
物流配送
路径规划
区域边界
粒子群算法
multi-warehouse
multi-distribution point
logistics distribution
path planning
regional boundary
Particle Swarm Optimization algorithm
