Optimizing dynamic supply chain formation in supply mesh using CSET model

  • Authors:
  • Hang Yang;Simon Fong

  • Affiliations:
  • Faculty of Science and Technology, University of Macau, Taipa, Macau;Faculty of Science and Technology, University of Macau, Taipa, Macau

  • Venue:
  • Information Systems Frontiers
  • Year:
  • 2013

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Abstract

A new e-Service model called dynamic supply chain is characterized by their dynamic nature in easily being formed and disbanded with the seamless connectivity provided by e-Marketplace. The new term "supply mesh" was coined to represent this virtual community of companies in which dynamic supply chains, as per project (also known as make-to-order), are formed across different tiers of suppliers. In a supply mesh, a dynamic supply chain can be formed vertically, from the top to the bottom layers, mediating different companies for a project. Companies that are on the same level laterally are usually competitors, and the companies that are linked vertically as supply chains are trading partners. From a global view, the companies that are connected in the supply mesh can be viewed as individual entities that have self-interest. They may compete for survival as well as collaborate with each other for jobs. Given such complex relations the challenge is to find an optimal group of members for a dynamic supply chain in the supply mesh. A multi-agent model called the collaborative single machine earliness/tardiness (CSET) model was recently proposed for the optimal formation of make-to-order supply chains. This paper investigates the possibilities of applying CSET in a supply mesh, and the corresponding allocation schemes are experimentally studied in simulations. One scheme called Cost-driven principle leads to destructive competition while the other one namely Pareto-optimal evolves into a cooperative competition that tries to mutually benefit every participant. The results, based on samples from the U.S. textile industry, show that a cooperative competition scheme is superior in terms of optimal allocation, which obtains maximum satisfaction for all participants.