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The effectiveness of optimized fuzzy controllers in the production scheduling has been demonstrated in the past, through extensive use of evolutionary algorithms (EAs). The EA strategy tunes a set of distributed and supervisory control modules, whose objective is to control the production rate in a way that satisfies the demand for final products, while reducing WIP within the production system. The...
The use of artificial neural networks implies considerable time spent choosing a set of parameters that contribute toward improving the final performance. Initial weights, the amount of hidden nodes and layers, training algorithm rates and transfer functions are normally selected through a manual process of trial-and-error that often fails to find the best possible set of neural network parameters...
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