云物流背景下基于A*算法改进的新一代物流车的设计研发  

Design and Development of New-Generation Logistics Vehicles Based on A* Algorithm Improvement under the Background of Cloud Logistics

作　　者：孙慧敏 王贞 夏心宇 孙俊伟 葛奕 

机构地区：[1]池州学院大数据与人工智能学院,安徽 池州 [2]池州学院商学院,安徽 池州 [3]安徽医科大学第二临床医学院,安徽 合肥

出　　处：《可持续发展》2025年第2期216-221,共6页Sustainable Development

基　　金：国家级大学生创新创业计划(202311306008)。

摘　　要：本文旨在研究云物流背景下新一代物流车的调度问题,提出了一种基于A*算法的改进调度方法。改进主要包括两个方面:一是增加了车辆负载约束条件;二是引入了云物流环境下的大数据支持。此外,还采用了关键点提取策略和平滑处理,并结合动态窗口法进行局部路径优化。最后,通过实验对比分析了改进后的A*算法与传统算法的性能差异,并得出结论:改进后的算法在动态环境适应性、搜索效率、路径平滑度以及全局与局部优化等方面均有显著提升。研究主题契合当前物流行业的发展热点,具有实际应用价值。This article aims to study the scheduling problem of new-generation logistics vehicles under the background of cloud logistics and propose an improved scheduling method based on A* algorithm. The improvement mainly includes two aspects: first, adding vehicle load constraints;second, introducing big data support in the cloud logistics environment. In addition, a key point extraction strategy and smoothing processing were adopted, combined with a dynamic window method for local path optimization. Finally, the performance differences between the improved A* algorithm and traditional algorithms were compared and analyzed through experiments, and the conclusion was drawn that the improved algorithm has significant improvements in dynamic environment adaptability, search efficiency, path smoothness, and global and local optimization. The research topic is in line with the current development hotspots in the logistics industry and has practical application value.

关 键 词：物流车 A*算法 路径识别 路径跟踪 全局动态路径规划 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]