Classifying inventory using an artificial neural network approach

By F. Partovi, M. Anandarajan. 2002

312 citations recorded by the source corpus.

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COMPARATIVE ANALYSIS OF AHP AND FUZZY AHP M ODELS FOR M ULTICRITERIA INVENTORY CLASSIFICATION (2011, background): “Partovi & Anandarajan (2002) proposed an artificial neural network (ANN) approach for inventory classification.”
A classification approach based on the outranking model for multiple criteria ABC analysis (2016, background): “It has been recognized that other criteria, such as inventory cost, part criticality, lead time, commonality, obsolescence, substitutability, durability, repairability, and so on, are also important for inventory classification [21,33,36].”
Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS) (2015, background): “Partovi and Anandarajan (2002) presented an artificial neural network approach for ABC classification of inventory.”
Mining incomplete survey data through classification (2010, background): “Among various neural network topologies, layered back-propagation neural networks (BPNN) [23] are the most popular for classification [19].”