Multiagent-Based Dynamic Deployment Planning in RTLS-Enabled Automotive Shipment Yard

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.

• Type: Conference
• Year: 2007
• Where: AI
• Authors: Jindae Kim, Changsoo Ok, Soundar R. T. Kumara, Shang-Tae Yee
• Keywords: AI 2007, Artificial Intelligence, Decentralized Decision-making Model, Shipment Yard, Vehicle Deployment Planning