Abstract
This paper presents the architecture of a multi-agent decision support system for Supply Chain Management (SCM) which has been designed to compete in the TAC SCM game. The behaviour of the system is demand-driven and the agents plan, predict, and react dynamically to changes in the market. The main strength of the system lies in the ability of the Demand agent to predict customer winning bid prices – the highest prices the agent can offer customers and still obtain their orders. This paper investigates the effect of the ability to predict customer order prices on the overall performance of the system. Four strategies are proposed and compared for predicting such prices. The experimental results reveal which strategies are better and show that there is a correlation between the accuracy of the models’ predictions and the overall system performance: the more accurate the prediction of customer order prices, the higher the profit.
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Kovalchuk, Y., Fasli, M. (2010). A Demand-Driven Approach for a Multi-Agent System in Supply Chain Management. In: David, E., Gerding, E., Sarne, D., Shehory, O. (eds) Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets. AMEC TADA 2009 2009. Lecture Notes in Business Information Processing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15117-0_7
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DOI: https://doi.org/10.1007/978-3-642-15117-0_7
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