Investigating the Value of Information and Computational Capabilities by Applying Genetic Programming to Supply Chain Management

  • Scott A. Moore
  • Kurt Demaagd
Part of the International Handbooks on Information Systems book series (INFOSYS)


In this paper we describe a research project centering on experiments in which game-playing evolving agents are used to investigate the value of information. Specifically, in these experiments we define populations of agents whose strategies evolve towards those that have better restocking strategies for their supply chain. The agents evolve their strategies in order to minimize costs (either for themselves or for their value chain). We describe several different experiments in which we will vary the abilities of agents both to gather and to store more information. Part of the results of this project will be related to the value of information and computational capabilities: Is it always better to have more information? If not, what are the conditions under which less information is better? The culminating experiment is one in which evolving agents compete to sell information to other evolving agents playing their roles in a supply chain.


Supply Chain Genetic Program Evolutionary Scenario Population Member Demand Distribution 
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 2005

Authors and Affiliations

  • Scott A. Moore
    • 1
  • Kurt Demaagd
    • 2
  1. 1.University of Michigan Business SchoolAnn ArborUSA
  2. 2.University of Michigan Business SchoolAnn ArborUSA

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