首页|"无人机—卡车"配送路径优化研究

"无人机—卡车"配送路径优化研究

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为有效提升"最后一公里"配送效率,以总运营成本最少为目标函数,提出了考虑道路拥堵指数的"无人机—卡车"配送路径优化模型.首先,基于改进的K-means算法确定卡车配送点;接着考虑道路拥堵指数,运用节约里程法得到卡车配送路径;然后采用改进模拟退火算法确定无人机飞行路线;最后选取郑州市主城区的80个小区进行实例计算,与卡车单独配送相比,"无人机—卡车"配送模式的配送成本降低了110元,约减少了13.78%.实例计算结果表明,"无人机—卡车"联合配送模型可有效减少配送成本,求解算法高效,更加贴合现实的配送场景,为新时代物资配送问题提供了理论参考.
Research on Optimization of"UAV-Truck"Distribution Path
In order to effectively improve the"last mile"distribution efficiency,a joint"UAV-truck"delivery model considering road congestion index is proposed.Firstly,the truck delivery points are selected by categorizing the customer points with the improved K-means algorithm.Then the road congestion index is considered and the multi-truck delivery path is optimized based on the mileage saving method.Then the UAV flight route is determined by the improved simulated annealing algorithm.Finally,take 80 residential areas in Zhengzhou for example,compared with truck distribution alone,the distribution cost decreased by 110 yuan,or about 13.78%.The results show that the joint UAV-truck distribution model can effectively reduce the distribution cost,and the solution algorithm is efficient and more suitable for realistic distribution scenarios,which provides a theoretical reference for the distribution of materials during the new era.

UAV-Truckpath optimizationK-means algorithmsimulated annealing algorithm

闫琼、刘畅畅、张海军

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郑州航空工业管理学院,河南 郑州 450015

无人机—卡车 路径优化 K-means算法 模拟退火算法

国家级大学生创新创业训练计划教育部人文社会科学研究项目河南省科技攻关计划河南省科技攻关计划河南省高等学校重点科研项目河南省高等学校重点科研项目

20221048503622YJAZH14423210232006323210232005924A63003924B460024

2024

10.19327/j.cnki.zuaxb.1007-1199.2024.02.005

管理工程师
郑州航空工业管理学院

管理工程师

影响因子：0.237
ISSN：1007-1199
年,卷(期)：2024.29(2)
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