Volume 35, Issue 2 (IJIEPR 2024)                   IJIEPR 2024, 35(2): 1-25 | Back to browse issues page


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Amini A, Alinezhad A, Gharakhani D. A Hybrid Method using MODM and BWM for Supplier Assessment under Uncertainty. IJIEPR 2024; 35 (2) :1-25
URL: http://ijiepr.iust.ac.ir/article-1-2004-en.html
1- Ph.D. Student in Industrial Management, Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2- Associate Professor, Department of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran , alinezhad@iau.ac.ir
3- Assistant Professor, Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Abstract:   (898 Views)
The selection of a sustainable supplier is a multi-criteria decision-making issue that covers a range of criteria (quantitative-qualitative). Selecting the most eco-friendly suppliers requires balancing tangible and intangible elements that may be out of sync. The problem gets more complicated when volume discounts are taken into account, as the buyer needs to decide between two issues: 1) What are the best sustainable suppliers? 2) Which amount needs to be bought from each of the selected eco-friendly suppliers? In current study a combined attitude of best-worst method (BWM) ameliorated via multi-objective mixed integer programming (MOMIP) and rough sets theory is developed. The aim of this work is to contemporaneously ascertain the order quantity allocated to these suppliers in the case of multiple sourcing, multiple products with multiple criteria and with capacity constraints of suppliers and the number of suppliers to employ. In this situation, price reductions are offered by suppliers based on add up commerce volume, not on the amount or assortment of items acquired from them. Finally, a solution approach is proposed to solve the multi-objective model, and the model is demonstrated using a case study in Iran Khodro Company (IKCO). The results indicate that ISACO is the most sustainable supplier and the most orders are assigned to this supplier.
Full-Text [PDF 625 kb]   (255 Downloads)    
Type of Study: Research | Subject: Operations Research
Received: 2024/03/18 | Accepted: 2024/05/26 | Published: 2024/06/21

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