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