Investigating the Value of Information and Computational Capabilities by Applying Genetic Programming to Supply Chain Management
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.
KeywordsSupply Chain Genetic Program Evolutionary Scenario Population Member Demand Distribution
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