TAILIEUCHUNG - Decision making with association rule mining and clustering in supply chains

This paper deals with data mining applications for the supply chain inventory management. ABC characterization is typically utilized for stock items arrangement on the grounds that the quantity of stock items is large to the point that it is not computationally practical to set stock and administration control rules for every individual item. | Decision making with association rule mining and clustering in supply chains International Journal of Data and Network Science 1 2017 11 18 Contents lists available at GrowingScience International Journal of Data and Network Science homepage ijds Decision making with association rule mining and clustering in supply chains Reshu Agarwala a G L bajaj Institute of Technology and Management Greater Noida India CHRONICLE ABSTRACT Article history This paper deals with data mining applications for the supply chain inventory management. Received October 1 2017 ABC characterization is typically utilized for stock items arrangement on the grounds that the Received in revised format No- quantity of stock items is large to the point that it is not computationally practical to set stock vember 16 2017 and administration control rules for every individual item. Moreover in ABC classification the Accepted May 17 2018 Available online inter-relationship between items is not considered. But practically the sale of one item could May 17 2018 influence the sale of other items cross selling effect . Consequently within each cluster the Keywords inventories should be classified. In this paper a modified approach is proposed considering both Data mining cross-selling effect and clusters to rank stock items. A numerical case is utilized to clarify the Association rule mining new approach. It is represented that by utilizing this modified approach the ranking of items Inventory management may get influenced bringing about higher profits. Cross-selling ABC classification Clustering 2017 by the authors licensee Growing Science Canada 1. Introduction In numerous stock control frameworks it has been viewed as that the quantity of items is large to the point that it is not computationally doable to set stock and administration control rules for every individual item. Subsequently items are regularly gathered together and generic stock control strategies are connected .

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