Abstract
Real-time vehicle location information enables to facilitate more efficient decision-making in dynamic automotive shipment yard environment. This paper proposes a multiagent-based decentralized decision-making model for the vehicle deployment planning in a shipment yard. A multiagent architecture is designed to facilitate decentralized algorithms and coordinate different agents dynamically. The results of computational experiments show that the proposed deployment model outperforms a current deployment practice with respect to the deployment performance measures.
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© 2007 Springer Berlin Heidelberg
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Kim, J., Ok, C., Kumara, S.R.T., Yee, ST. (2007). Multiagent-Based Dynamic Deployment Planning in RTLS-Enabled Automotive Shipment Yard. In: Kobti, Z., Wu, D. (eds) Advances in Artificial Intelligence. Canadian AI 2007. Lecture Notes in Computer Science(), vol 4509. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72665-4_4
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DOI: https://doi.org/10.1007/978-3-540-72665-4_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72664-7
Online ISBN: 978-3-540-72665-4
eBook Packages: Computer ScienceComputer Science (R0)