Volume 36, Issue 2 (IJIEPR 2025)                   IJIEPR 2025, 36(2): 52-67 | Back to browse issues page

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Abdollahi Kamran M, Afsharfar S, Al Mawali F, Babazadeh R, Al Balushi M. Application of fuzzy MCDM methods to Optimize Supplier Selection in Oil and Gas Industry of Oman. IJIEPR 2025; 36 (2) :52-67
URL: http://ijiepr.iust.ac.ir/article-1-2234-en.html
Application of fuzzy MCDM methods to Optimize Supplier Selection in Oil and Gas Industry of Oman
Mehdi Abdollahi Kamran1 , Samira Afsharfar1 , Fatma Al Mawali1 , Reza Babazadeh2 , Marya Al Balushi1
1- Department of Logistics, Tourism, and Services Management, German University of Technology in Oman, P. O. Box 1816, PC 130, Muscat, Oman
2- Department of Industrial Engineering, Faculty of Engineering, Urmia University, Urmia, West Azerbaijan Province, Iran , r.babazadeh@urmia.ac.ir
Abstract:   (509 Views)
One of the most critical concerns in supply chain management (SCM) is supplier selection, which significantly impacts an organization's efficiency and market agility. Balancing ordinal and basic criteria in supplier selection has become increasingly crucial in recent years within SCM. This research presents three multi-criteria decision-making (MCDM) methods including Fuzzy analytic hierarchy process (AHP) and Fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods to assess and select suppliers in oil and gas (O&G) industry. The critical criteria for supplier selection in the O&G sector have been reviewed in the literature and validated by experts actively working in the field. Initially, the Fuzzy AHP technique determines criterion weights and ranks suppliers. Subsequently, the Fuzzy TOPSIS approach is applied to rank prospective suppliers identified through objective evaluation. The findings show the capability of the utilized approaches in supplier selection procedure in O&G industry.
Keywords: Supplier Selection, Oil and Gas Industry, Fuzzy AHP, Fuzzy TOPSIS, MCDM
Full-Text [PDF 399 kb]   (136 Downloads)    
Type of Study: Research | Subject: Decision Analysis and Methods
Received: 2024/12/27 | Accepted: 2025/03/5 | Published: 2025/06/30
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