Soft Computing for Softgoods Supply Chain Analysis and Decision Support
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.
KeywordsSupply Chain Membership Function Soft Computing Supply Chain Modeling Source Simulator
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