摘要
采用无人机配送物资在商业和军事上均有广阔的应用前景。针对配送过程中末端配送效率低等问题,提出一种车辆携带多架无人机的配送方案,以最小服务时间为优化目标构造最优化模型,求解模型时采用改进的K-means聚类算法对配送点进行分类,将聚类中心作为货车配送点;然后以车辆路径问题为基础设计蚁群拟算法求解一车携带多架无人机形式的配送路线。通过采用标准数据集进行实验,实验结果表明改进后算法在路径优化能力和求解精确性方面都有较好的性能。
The use of drones for material delivery has broad application prospects in both commercial and military fields.A delivery plan for vehicles carrying multiple drones is proposed to address the low efficiency of end of delivery during the delivery process.The optimization model is constructed with the minimum service time as the objective.When solving the model,an improved K-means clustering algorithm is used to classify the delivery points,and the cluster center is used as the truck delivery point;Then,based on the vehicle routing problem,an ant colony simulation algorithm is designed to solve the delivery route in the form of one vehicle carrying multiple drones.Through experiments using standard datasets,the experimental results show that the improved algorithm has good performance in path optimization ability and solution accuracy.
作者
黄迎春
李开源
HUANG Yingchun;LI Kaiyuan(School of Information Science and Engineering,Shenyang Ligong University,Shenyang 110159,China)
出处
《火力与指挥控制》
北大核心
2025年第8期31-37,共7页
Fire Control & Command Control
基金
国家自然科学基金资助项目(61971291)。
关键词
综合运输
聚类算法
蚁群算法
路径优化
integrated transportation
clustering algorithm
ant colony algorithm
path optimization
