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- W2047427484 abstract "This paper proposed a neural network (NN) metamodeling method to generate the cycle time (CT)–throughput (TH) profiles for single/multi-product manufacturing environments. Such CT–TH profiles illustrate the trade-off relationship between CT and TH, the two critical performance measures, and hence provide a comprehensive performance evaluation of a manufacturing system. The proposed methods distinct from the existing NN metamodeling work in three major aspects: First, instead of treating an NN as a black box, the geometry of NN is examined and utilized; second, a progressive model-fitting strategy is developed to obtain the simplest-structured NN that is adequate to capture the CT–TH relationship; third, an experiment design method, particularly suitable to NN modeling, is developed to sequentially collect simulation data for the efficient estimation of the NN models." @default.
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- W2047427484 date "2010-08-01" @default.
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- W2047427484 title "Neural network metamodeling for cycle time-throughput profiles in manufacturing" @default.
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- W2047427484 doi "https://doi.org/10.1016/j.ejor.2009.12.026" @default.
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