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Multiple Criteria ABC Analysis with FCM Clustering
Author(s) -
Gülşen Aydın Keskin,
Coşkun Özkan
Publication year - 2012
Publication title -
journal of industrial engineering
Language(s) - English
Resource type - Journals
eISSN - 2314-4890
pISSN - 2314-4882
DOI - 10.1155/2013/827274
Subject(s) - operations research , cluster analysis , computer science , liberian dollar , fuzzy logic , safety stock , abc analysis , order (exchange) , operations management , economic order quantity , inventory management , economics , business , supply chain , engineering , artificial intelligence , marketing , finance
The number of stock keeping units (SKUs) possessed by organizations can easily reach quite a few. An inventory management policy for each individual SKU is not economical to design. ABC analysis is one of the conventionally used approaches to classify SKUs. In the classical method, the SKUs are ranked with respect to the descending order of the annual dollar usage, which is the product of unit price and annual demand. The few of the SKUs that have the highest annual dollar usage are in group A and should be taken into account mostly; the SKUs with the least annual dollar usage are in group C and should be taken into account least; the remaining SKUs are in group B. In this study, we proposed fuzzy c-means (FCM) clustering to a multicriteria ABC analysis problem to help managers to make better decision under fuzzy circumstancse. The obtained results show that the FCM is a quite simple and an easily adaptable method to inventory management

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