摘要
文章系统探讨了深度学习在物流配送管理中的应用机理与实现路径。在梳理现有研究的基础上,从数据驱动视角出发,分析了深度学习在需求预测、路径规划及运力调度等关键环节的应用机制,并对智能物流配送管理平台的架构设计、算法选取与性能评估等方面进行了全面阐述。研究指出,将深度学习等人工智能技术与海量物流数据深度融合,可显著提升配送决策的智能化和精细化水平,是物流企业优化运营模式、提高效率的重要路径。文章旨在为物流行业的数字化与智能化转型提供理论参考和实践指导。
This paper systematically discussed the application mechanism and implementation path of deep learning in logistics distribution management.On the basis of combing the existing research,this paper analyzes the application mechanism of deep learning in key links such as demand forecasting,path planning and capacity scheduling from the perspective of data-driven,and comprehensively expounds the architecture design,algorithm selection and performance evaluation of the intelligent logistics distribution management platform.The research points out that the deep integration of artificial intelligence technology such as deep learning and massive logistics data can significantly improve the intelligence and refinement level of distribution decision-making,which is an important way for logistics enterprises to optimize the operation mode and improve efficiency.This paper aimed to provide theoretical reference and practical guidance for the digital and intelligent transformation of logistics industry.
作者
李雪原
亓俊红
张丽红
LI Xueyuan;QI Junhong;ZHANG Lihong(Department of Artificial Intelligence,Laiwu Vocational and Technical College,Jinan 271199,China)
关键词
数据驱动
深度学习
物流配送
智能优化
管理平台
data-driven
deep learning
logistics distribution
intelligent optimization
management platform
