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Dynamic Supply Chain Structuring for Electronic Commerce among Agents

  • Daniel Dajun Zeng
  • Katia Sycara
Chapter

Summary

Electronic commerce and the vast amounts of real-time information available through means of EDI and the Internet are reshaping the way enterprises conduct business. A new computational infrastructure and models are needed for a business to gain a competitive edge through effective use of this information base. One of the key issues in competing in the electronic marketplace is product/service differentiation. Currently there are no computational models for multi-issue decision making in electronic commerce.

We develop a model of interorganizational electronic commerce that explores various new choices and opportunities that the electronic marketplace offers. That particular motivating applications of our work are supply chain management. Two major performance measures of supply chain activities are cost and leadtime. In our model, we explicitly address these two issues in a unified fashion for a variety of supply chain activities, such as outsourcing, supplier selection, production capacity, tranportation mode selection, and inventory positioning. We model different business entities as autonomous software agents interconnected via the Internet. The main research focus of our efforts is how to coordinate software agents in supply chains dynamically and flexibly such that goods and services can be delivered at the right time in a cost-effective manner.

The supply chain structure is modeled by an AND/OR network. We develop an efficient algorithm for software agents in supply chains to evaluate the alternatives that offer different leadtime and cost parameters. We have coupled this model with operational level decision making such as stochastic inventory management. Experimental results show that our model results in significant improvement in solution quality as compared to traditional models.

Keywords

Supply Chain Optimal Policy Supply Chain Management Efficient Frontier Supply Chain Network 
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 1999

Authors and Affiliations

  • Daniel Dajun Zeng
    • 1
  • Katia Sycara
    • 1
  1. 1.Graduate School of Industrial Administration, The Robotics InstituteCarnegie Mellon UniversityPittsburghUSA

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