Abstract
In this paper, a random search method based on Evolutionary Operation (EVOP) is used to determine priority strategies to maximize complex manufacturing system performance. Modeling is carried out using discrete-event simulation. The main task was to investigate how much changes of priority rules affect system performance. Case study analysis is of a commercial offset printing production system working under various dynamic priority rules.
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