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In production networks companies need fast reactions due to changes of supply and demand. To realize such a change management in an effective way the involved companies have to synchronize their quantities and capacities collaboratively. For these purposes the multiagent system MASCOPP was developed at the Heinz Nixdorf Institute, which tries to eliminate(More)
This work shows the application of k-means clustering to reduce the state space complexity for a q-leaning algorithm in supply networks of serial production systems. An adequate clustering function is introduced and based on several scenarios the results of the clustering are validated with respect to their usability for the q-learning system. In addition,(More)
Real world problems, e.g. from transport domain, are typically non-deterministic and uncertain. Although there are some approaches, which try to forecast uncertain parameters like travel time, the uncertainty is rarely included in the planning process. In this paper a probabilistic forecasting method for travel time in a railway network is introduced which(More)
The project AC/DC, funded by the European Commission (contract number FP6-SST-031520), deals with new logistical concepts for planning and control of supply networks that enhance automotive manufacturing radically. To handle upcoming disturbances within the regarded supply network structure, a real-time event management system is developed in order to(More)
Modern value-added processes will be globally cross-linked through outsourcing and reduction of real net output ratio. Therefore logistical planning and control processes become more complex. Events in supply networks and their consequences to the partners in the supply network will be hardly to overlook without using computer based decision support(More)
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