• DocumentCode
    1651017
  • Title

    A multiattribute ABC classification model using fuzzy AHP

  • Author

    ÇEbi, Ferhan ; Kahraman, Cengiz ; Bolat, Bersam

  • Author_Institution
    Fac. of Manage., Istanbul Tech. Univ., Istanbul, Turkey
  • fYear
    2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    ABC analysis is one of the most widely used techniques in organizations to classify inventory items. This classification is based on the Pareto principle. The main limitation of the Pareto principle comes from its one dimensional analysis. To overcome this limitation, an ABC analysis based on a multiattribute classification can be used. Many attributes are hard to define precisely in this analysis. The fuzzy set theory can overcome this problem by incorporating imprecision and subjectivity into a multiattribute ABC classification model. In this paper, Zeng´s fuzzy analytic hierarchy process is used for classifying inventory items by taking care of conflicting attributes like demand, unit cost, substitutability, payment terms, and lead time. A real case study in a Turkish firm distributing fast moving consumer goods is realized. The obtained results show that this multiattribute fuzzy methodology can be effectively used in classifying inventory items.
  • Keywords
    Pareto analysis; consumer products; decision making; fuzzy set theory; inventory management; pattern classification; Pareto principle; Turkish firm; Zeng fuzzy analytic hierarchy process; fast moving consumer good; fuzzy AHP; fuzzy set theory; inventory item classification; lead time; multiattribute ABC classification model; payment term; Classification algorithms; Companies; Decision making; Equations; Fuzzy set theory; Mathematical model; Optimization; ABC analysis; Pareto; analytic hierarchy process (AHP); classification; fuzzy sets; multiple attribute;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers and Industrial Engineering (CIE), 2010 40th International Conference on
  • Conference_Location
    Awaji
  • Print_ISBN
    978-1-4244-7295-6
  • Type

    conf

  • DOI
    10.1109/ICCIE.2010.5668233
  • Filename
    5668233