A Model to Determine the Most Important Criteria in Green Supply Chain Using Multi-Branch Fuzzy Decision Making
عنوان مقاله: A Model to Determine the Most Important Criteria in Green Supply Chain Using Multi-Branch Fuzzy Decision Making
شناسه ملی مقاله: IIEC17_015
منتشر شده در هفدهمین کنفرانس بین المللی مهندسی صنایع در سال 1399
شناسه ملی مقاله: IIEC17_015
منتشر شده در هفدهمین کنفرانس بین المللی مهندسی صنایع در سال 1399
مشخصات نویسندگان مقاله:
Majid Aarabi - Assistant Professor of Industrial Engineering, Department of Industrial Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
AmirAli Abbasi - B.A. of Industrial Engineering, Department of Industrial Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
خلاصه مقاله:
Majid Aarabi - Assistant Professor of Industrial Engineering, Department of Industrial Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
AmirAli Abbasi - B.A. of Industrial Engineering, Department of Industrial Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
The rapid natural resources consumption trend in recent decades leads to the irreparable damages to the environment. With increasing environmental concerns, it is necessary to implement a compiled program for the entire supply network. One of the main tools for adapting business activities with environmental goals is implementation of the green supply chain. The aim of this study is to determine the most important criteria to achieve a green supply chain by using AHP fuzzy. The results suggest that, "Reducing the amount of water that is annually used from available groundwater and surface water", would be the most influential factor in green supply chain. It would be worth to mention, although the proposed approach could be utilized for determining obligations of constant green supply chain, similarly, this approach could be performed in other sections and organizations.
کلمات کلیدی: Supply chain, Green supply chain, AHP Fuzzy
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1160880/