Journal of Engineering, Project, and Production Management, 2013, 3(1), 22-34
Integrating Fuzzy Delphi with Fuzzy Analytic Hierarchy Process for Multiple Criteria Inventory Classification
G. Kabir1 and R. S. Sumi2
1PhD Student, Department of Civil Engineering, University of British Columbia, Kelowna, British Columbia, Canada. Email: gk.raju@yahoo.com (corresponding author).
2Assistant Professor, Department of Business Administration, Stamford University, Bangladesh, Dhaka, Bangladesh. Email: sumi2681@yahoo.com
Production Management
Received March 7, 2012; revisions April 3, 2012; April 6, 2012; accepted April 12, 2012
Available online June 25, 2012
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, multiple criteria inventory classification is used. In this paper, a systematic and logical approach is structured for multiple criteria inventory classification through integrating Fuzzy Delphi Method (FDM) with Fuzzy Analytic Hierarchy Process (FAHP). Fuzzy Delphi method used to identify the most important and significant criteria and, 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. Implementation results show that the proposed method can be used in inventory classification.
Keywords: Multicriteria inventory classification, Fuzzy Delphi Method, fuzzy analytic hierarchy process, triangular fuzzy number.
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Citation: Kabir, G. and Sumi, R. S. (2013). Integrating Fuzzy Delphi with Fuzzy Analytic Hierarchy Process for Multiple Criteria Inventory Classification. Journal of Engineering, Project, and Production Management, 3(1), 22-34.
DOI:
10.32738/JEPPM.201301.0004
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