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In automated container terminals, effectively scheduling quay cranes (QCs), automated guided vehicles (AGVs), automated stacking cranes (ASCs) and AGV routing are two important problems. This paper...

This paper addresses coordination problem of a supply chain comprising one supplier and one retailer under production cost and market demand disruptions. Assume the market demand is sensitive to retail price in an exponential form, the optimal strategies are obtained for different disruption scale under centralized-decision system, and it is shown that the original production plan of the supply chain has certain robustness under the disrupted production cost and the disrupted market scale. For the decentralized-decision system, it is proved that the supply chain can be fully coordinated by the quantity discount contracts appropriately.

A model intelligent vehicle system (JUTIV-II) is introduced in the paper. The visual system has an omni-direction camera, which enables the view field to be changed with the speed of the vehicle, more information about the lane to be obtained and disturbances in the view field to be reduced. A linear lane model is applied to match the shape of the lane in the view field. A vision-based navigation algorithm-human imitating steering control algorithm-is proposed based on a linear lane model. An artificial neural transfer function is applied in the model to imitate the human driving. The model shows good results under a wide range of parameter input. The direction error angle ranges from -90/spl deg/ to +90/spl deg/ and the departure error distance ranges from -/spl infin/ to +/spl infin/. Experiment results are given in the paper.