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- W64965746 abstract "Publisher Summary This chapter summarizes the adjustment of parallel queuing processes by multi-agent control. Multi-agent control is an efficient optimization and control method for local systems in large decentralized environments. The control of distributed systems is difficult especially in the case when the system consists of a large number of local systems. Normally, this control is done in a centralized way that can lead to problems with respect to the exchange of information and to find an appropriate optimum. Multi agent control methods are applied in congestion control of traffic networks and manufacturing systems. In a multi-level warehouse hierarchy with its market mechanisms is applied to real time transportation, dynamic freight allotment, depot agents, scheduling problems, and production planning. For the market-based algorithm local utility and profit functions, respectively, are defined based on the particular Markov processes are optimized. The result of the optimization is a so-called Pareto-optimum that represents a compromise between the competing processes. The simulation experiments show that the algorithm leads to excellent results for the adjustment of local queuing processes." @default.
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- W64965746 date "2003-01-01" @default.
- W64965746 modified "2023-10-16" @default.
- W64965746 title "Adjustment of parallel queuing processes by multi-agent control" @default.
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- W64965746 doi "https://doi.org/10.1016/b978-044451379-3/50038-8" @default.
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