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- W2909367009 abstract "Traditional inventory classification models divide SKUs into a few broad categories and help companies to sort inventories using a simple and intuitive way. However, these classification approaches are not able to meet the requirement of autonomous inventory performance analysis and planning in digitized supply chains. This research presents a novel classification approach, which is able to generate granular classifications based on multiple demand and performance attributes of SKUs. The performance templates of these categories can be used as learning data for supervised machine learning algorithms to perform autonomous inventory performance analysis and planning." @default.
- W2909367009 created "2019-01-25" @default.
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- W2909367009 date "2018-12-01" @default.
- W2909367009 modified "2023-09-27" @default.
- W2909367009 title "Novel SKU Classification Approach for Autonomous Inventory Planning" @default.
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- W2909367009 doi "https://doi.org/10.1109/ieem.2018.8607736" @default.
- W2909367009 hasPublicationYear "2018" @default.
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