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 admin-istra...
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| Format: | Article |
| Language: | English |
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Growing Science
2017-01-01
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| Series: | International Journal of Data and Network Science |
| Subjects: | |
| Online Access: | http://www.growingscience.com/ijds/Vol1/ijdns_2017_3.pdf |
| _version_ | 1819262434797420544 |
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| author | Reshu Agarwal |
| author_facet | Reshu Agarwal |
| author_sort | Reshu Agarwal |
| collection | DOAJ |
| description | 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 admin-istration control rules for every individual item. Moreover, in ABC classification, the inter-relationship between items is not considered. But practically, the sale of one item could influence the sale of other items (cross selling effect). Consequently, within each cluster, the inventories should be classified. In this paper, a modified approach is proposed considering both cross-selling effect and clusters to rank stock items. A numerical case is utilized to clarify the new ap-proach. It is represented that by utilizing this modified approach; the ranking of items may get influenced bringing about higher profits. |
| first_indexed | 2024-12-23T19:57:38Z |
| format | Article |
| id | doaj.art-ce9c578ac50346458f49ec299e72055b |
| institution | Directory Open Access Journal |
| issn | 2561-8148 2561-8156 |
| language | English |
| last_indexed | 2024-12-23T19:57:38Z |
| publishDate | 2017-01-01 |
| publisher | Growing Science |
| record_format | Article |
| series | International Journal of Data and Network Science |
| spelling | doaj.art-ce9c578ac50346458f49ec299e72055b2022-12-21T17:33:10ZengGrowing ScienceInternational Journal of Data and Network Science2561-81482561-81562017-01-0111111810.5267/j.ijdns.2017.1.003Decision making with association rule mining and clustering in supply chainsReshu AgarwalThis 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 admin-istration control rules for every individual item. Moreover, in ABC classification, the inter-relationship between items is not considered. But practically, the sale of one item could influence the sale of other items (cross selling effect). Consequently, within each cluster, the inventories should be classified. In this paper, a modified approach is proposed considering both cross-selling effect and clusters to rank stock items. A numerical case is utilized to clarify the new ap-proach. It is represented that by utilizing this modified approach; the ranking of items may get influenced bringing about higher profits.http://www.growingscience.com/ijds/Vol1/ijdns_2017_3.pdfData miningAssociation rule miningInventory managementCross-sellingABC classificationClustering |
| spellingShingle | Reshu Agarwal Decision making with association rule mining and clustering in supply chains International Journal of Data and Network Science Data mining Association rule mining Inventory management Cross-selling ABC classification Clustering |
| title | Decision making with association rule mining and clustering in supply chains |
| title_full | Decision making with association rule mining and clustering in supply chains |
| title_fullStr | Decision making with association rule mining and clustering in supply chains |
| title_full_unstemmed | Decision making with association rule mining and clustering in supply chains |
| title_short | Decision making with association rule mining and clustering in supply chains |
| title_sort | decision making with association rule mining and clustering in supply chains |
| topic | Data mining Association rule mining Inventory management Cross-selling ABC classification Clustering |
| url | http://www.growingscience.com/ijds/Vol1/ijdns_2017_3.pdf |
| work_keys_str_mv | AT reshuagarwal decisionmakingwithassociationruleminingandclusteringinsupplychains |