Multiple criteria inventory classification using fuzzy analytic hierarchy process

Golam Kabir*, M. Ahsan Akhtar Hasin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

A systematic approach to the inventory control and classification may have a significant influence on company competitiveness. In practice, all inventories cannot be controlled with equal attention. In order to efficiently control the inventory items and to determine the suitable ordering policies for them, multi-criteria inventory classification is used. In this paper, fuzzy analytic hierarchy process for multiple criteria ABC inventory classification has been proposed. Fuzzy Analytic Hierarchy process (Fuzzy AHP) is used to determine the relative weights of the attributes or criteria, and to classify inventories into different categories. To accredit the proposed model, it is implemented for the 351 raw materials of switch gear section of Energypac Engineering Limited (EEL), a large power engineering company of Bangladesh. In this approach, at first, related criteria have been selected (Unit price, last year consumption or annual demand, last use date, supplier, criticality, durability) and the weights of these criteria was determined using Fuzzy AHP. Then a score to each item was assigned for each criterion as triangular fuzzy number and the final normalized weighted score of each item using fuzzy set theory is calculate. Finally, Chang's extent analysis was used for the comparison of fuzzy numbers and the final scores are compared with each other. Then all items were classified into three classes according to their final score.

Original languageEnglish
Pages (from-to)123-132
Number of pages10
JournalInternational Journal of Industrial Engineering Computations
Volume3
Issue number2
DOIs
StatePublished - Jan 2012
Externally publishedYes

Keywords

  • Classification
  • Fuzzy analytic hierarchy process
  • Multicriteria inventory
  • Triangular fuzzy number

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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