Abstract
This paper proposes agent-based formulation of a Supply Chain Management (SCM) system for manufacturing firms. We model each firm as an intelligent agent, which communicates each other through the black-board architecture in distributed artificial intelligence. To overcome the issues of conventional SCM systems, we employ the concept of information entropy, which represents the complexity of the purchase, sales, and inventory activities of each firm. Based on the idea, we implement an agent-based simulator to learn ‘good’ decisions viagenetic programming in a logic programming environment. From intensive experiments, our simulator have shown good performance against the dynamic environmental changes.
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© 2004 Springer-Verlag Berlin Heidelberg
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Taniguchi, K., Terano, T. (2004). Analyzing Dynamics of a Supply Chain Using Logic-Based Genetic Programming. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_66
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DOI: https://doi.org/10.1007/978-3-540-30132-5_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23318-3
Online ISBN: 978-3-540-30132-5
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