Intelligent supply chain management using adaptive critic learning

Abstract

A set of neural networks is employed to develop control policies that are better than fixed, theoretically optimal policies, when applied to a combined physical inventory and distribution system in a nonstationary demand environment. Specifically, we show that model-based adaptive critic approximate dynamic programming techniques can be used with systems… (More)
DOI: 10.1109/TSMCA.2003.809214

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