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Multiple Criteria ABC Analysis with FCM Clustering
Joint Authors
Ozkan, Coskun
Aydin Keskin, Gulsen
Source
Journal of Industrial Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-12-18
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Engineering Sciences and Information Technology
Science
Abstract EN
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.
American Psychological Association (APA)
Aydin Keskin, Gulsen& Ozkan, Coskun. 2012. Multiple Criteria ABC Analysis with FCM Clustering. Journal of Industrial Engineering،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-501312
Modern Language Association (MLA)
Aydin Keskin, Gulsen& Ozkan, Coskun. Multiple Criteria ABC Analysis with FCM Clustering. Journal of Industrial Engineering No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-501312
American Medical Association (AMA)
Aydin Keskin, Gulsen& Ozkan, Coskun. Multiple Criteria ABC Analysis with FCM Clustering. Journal of Industrial Engineering. 2012. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-501312
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-501312