A multi-agent model for the reasoning of uncertainty information in supply chains

In order to simulate the real world effectively, this paper proposes a multi-agent model that integrates a price negotiation support system based on the use of intelligent agents capable of processing information uncertainty. The certainty factor is integrated in expert systems to support the decision of agents. In the model, each agent is integrated with an expert system to deal with the uncertainty information. A real example of supply chains is chosen to show the validity of the proposed multi-agent model. Virtual companies can use the uncertainty information to support decisions. Multiple experiments are conducted to work on the coordination of the supply chain. The selling and purchasing prices in the supply chain are proposed in the experimental results. These prices are similar with the data in a real supply chain and are the optimal price strategy for the supply chain. The model was programmed using Jess and Swarm, which was run on Windows XP. The multi-agent model in the paper is beneficial to the reasoning of uncertainty information in multi-agent systems.

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