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A new Fuzzy C-Means and AHP-based three-phased approach for multiple criteria ABC inventory classification

Author

Listed:
  • Fatih Yiğit

    (Istanbul Arel University)

  • Şakir Esnaf

    (Istanbul University-Cerrahpaşa)

Abstract

ABC analysis is an efficient and easy-to-use methodology to classify inventory based on a single or multi-criteria basis that may consist of thousands of items. The first study by Dickie (Fact Manag Maint 109(7):92–94, 1951), based on a single criterion, is considered to be limited now. New studies focus on Multi-Criteria-Inventory Classification (MCIC) since such an extension of the criteria fits the realities of modern business decisions. The proposed approach in this study uses three-phased MCIC incorporating analytical hierarchy process (AHP), Fuzzy C-Means (FCM) algorithm, and a newly proposed Revised-Veto (Rveto) phase to meet the ABC classification principles and increase its applicability and flexibility. This new approach is called AHP–FCM–Rveto and proposed in this study for the first time. A numerical example taken from the literature is used to compare AHP–FCM–Rveto with other methods, and the results also show that the proposed methodology performs better. In the real-life example, the main advantage of compliance with the Pareto principle of the proposed method is shown.

Suggested Citation

  • Fatih Yiğit & Şakir Esnaf, 2021. "A new Fuzzy C-Means and AHP-based three-phased approach for multiple criteria ABC inventory classification," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1517-1528, August.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:6:d:10.1007_s10845-020-01633-7
    DOI: 10.1007/s10845-020-01633-7
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    References listed on IDEAS

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