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Title page for ETD etd-05162002-151641


Type of Document Master's Thesis
Author Parlikad, Ajith Kumar Parlikad Narayanan,
Author's Email Address ajithkpn@yahoo.com
URN etd-05162002-151641
Title Performance Analysis of Intelligent Supply Chain Networks
Degree Master of Science
Graduate Program Industrial Engineering
Advisory Committee
Advisor Name Title
Dr. Michael G. Kay Committee Chair
Dr. Cecil C. Bozarth Committee Member
Dr. Robert E. Young Committee Member
Keywords
  • E-Commerce
  • Intelligent Supply Chains
  • Logistics
Date of Defense 2002-05-17
Availability unrestricted
Abstract
Supply Chain Management has become the primary competitive weapon in many industries. This thesis describes a model of intelligent supply chain networks that will improve information visibility and flow within the supply chain. In the proposed model, products will have the intelligence to direct themselves throughout the distribution network and will have the capability to be purchased and sold while in transit. The report gives an overview of the supporting technologies that make such a supply chain a reality. It is intended to provide a preliminary outlook at the various issues related to implementation and could be used for future research as a basis for building the infrastructure required for the new model. An effort has been made to provide a design structure for XML identification tags, which will be one of the most critical components of the system. In addition to that, this report will describe the results of a simulation analysis using a model of a hypothetical public logistics network covering the southeastern United States. The network consists of 36 nodes representing the public distribution centers and 59 arcs, which represents various interstate highways connecting them. The simulations help identify the critical parameters associated with the material flow through the network and provide an insight into the capacity requirement of the public distribution centers. The results of the simulations will be used as a benchmark for future research and development associated with building an actual negotiating agent model.
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