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Design of a knowledge-based logistics management system : a case-based RFID approach

机译:基于知识的物流管理系统设计:基于案例的RFID方法

摘要

In recent years, the restructure of the customers' supply chain and logistics network has redefined the way a logistics service is operated. Various kinds of logistics information systems have been well developed to store and process all sorts of data and information to support daily logistics operations. The logistics planning or decision-making of logistics activity, however, is still executed manually. In this paper, a Knowledge-based Logistics Management System (KLMS) is designed to support logistic service providers in making decisions during the stage of logistics planning and operations by extracting, sharing and storing real-time logistics knowledge. KLMS is developed by integrating Case-Based Reasoning (CBR), Radio Frequency Identification (RFID), Online Analytical Processing (OLAP) technologies and a branch-and-bound resource route optimising programming model seamlessly together, which is suitable for usage in different business processes in a warehouse operating environment. Through applying KLMS in GENCO, a US-based logistic service company, the overall logistics servicing level is enhanced through accurate decision-making and planning of warehouse operations.
机译:近年来,客户供应链和物流网络的重组重新定义了物流服务的运营方式。已经开发出各种物流信息系统来存储和处理各种数据和信息,以支持日常物流运营。但是,物流计划或物流活动的决策仍需手动执行。本文设计了一种基于知识的物流管理系统(KLMS),以通过提取,共享和存储实时物流知识来支持物流服务提供商在物流计划和运营阶段进行决策。 KLMS是通过将基于案例的推理(CBR),射频识别(RFID),在线分析处理(OLAP)技术和分支和边界资源路由优化编程模型无缝集成在一起而开发的,适用于不同业务仓库操作环境中的流程。通过将KLMS应用于总部位于美国的物流服务公司GENCO,可通过准确的决策和仓库运营计划来提高整体物流服务水平。

著录项

  • 作者

    Chow KH; Choy KL; Lee WB;

  • 作者单位
  • 年度 2006
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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