基于机器学习的自适应仓储物流调度系统设计

Research on the Design of an Adaptive Warehouse Logistics Scheduling System Based on Machine Learning

随着电子商务的迅速发展,电商仓储作为电商行业的重要组成部分,也面临新的机遇和问题。文章设计了一个基于机器学习的自适应仓储物流调度系统,该系统通过监测设备、搬运机器人、智能货架与标签系统以及数据收集与传输设备实现硬件设计,同时,系统安全设计包括访问控制、数据加密、异常行为检测以及灾难恢复与备份策略。运行测试结果表明,该系统能够智能预测库存、自动分类货物、动态优化路径、自动调度运输以及处理异常订单,从而提高仓储物流的效率和准确性,其功能、性能和安全性方面表现良好。

With the booming of e-commerce,e-commerce warehousing,as a key component of the industry,is also facing new opportunities and challenges.To address this,the article proposes an adaptive warehouse logistics scheduling system based on machine learning.The hardware of the system include monitoring devices,handling robots,intelligent shelves and labeling systems,as well as data collection and transmission devices.At the same time,the system security design consists of access control,data encryption,abnormal behavior detection,and disaster restore and backup strategies.The running test results indicate that the system can intelligently predict inventory,automatically classify goods,dynamically optimize paths,automatically schedule transportation,and handle abnormal orders,thereby enhancing the efficiency and accuracy of warehousing logistics,and performing well in terms of functionality,performance,and safety.