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Soft Computing for Softgoods Supply Chain Analysis and Decision Support

  • Shu-Cherng Fang
  • Henry L. W. Nuttle
  • Russell E. King
  • James R. Wilson
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 108)

Summary

Research on softt computing techniques for decision support for the design and management of the softgoods supply chain are presented. In particular, this work has been directed to creating and demonstrating a fuzzy-neural softt computing framework for supply chain modeling and optimization and creating and demonstrating softt computing based approaches to capacity allocation and delivery date assignment. The former has required the development of fuzzy system identiifiication procedures, a method for constructing membership functions for fuzzy sets, and a flexible supply chain simulation capability. The paper gives an overview of this work and the prototype tools we have developed.

Keywords

Supply Chain Membership Function Soft Computing Supply Chain Modeling Source Simulator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Shu-Cherng Fang
    • 1
  • Henry L. W. Nuttle
    • 1
  • Russell E. King
    • 1
  • James R. Wilson
    • 1
  1. 1.Department of Industrial Engineering and Graduate Program in Operations ResearchNorth Carolina State UniversityRaleighUSA

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