A rough set approach to multiple criteria ABC analysis

Authors:
Ye Chen;Kevin W. Li;Jason Levy;Keith W. Hipel;D. Marc Kilgour
Affiliations:
Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada;Odette School of Business, University of Windsor, Windsor, Ontario, Canada;Huxley College of the Environment, Western Washington University, Washington;Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada;Department of Mathematics, Wilfrid Laurier University, Waterloo, Ontario, Canada
Venue:
Transactions on rough sets VIII
Year:
2008

Citing 6
Cited 0

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Abstract

A dominance-based rough set approach (DRSA) to multiple criteria ABC analysis (MCABC) is designed and compared to other approaches using a practical case study. ABC analysis is a well-known inventory planning and control approach, which classifies inventory items, or stock-keeping units (SKUs), based solely on their annual dollar usage. Recently, it has been suggested that MCABC can provide more managerial flexibility by considering additional criteria such as lead time and criticality. This paper proposes an MCABC method that employs DRSA to generate linguistic rules to represent a decision maker's preferences based on the classification of a test data set. These linguistic rules are then applied to classify other SKUs. A case study is used to compare the DRSA with other MCABC approaches to demonstrate the applicability of the proposed method.