Sustainable closed-loop supply chain design for the car battery industry with taking into consideration the correlated criteria for supplier selection and uncertainty conditions

Authors

  • Hamid Reza Jafari
  • Amirhosein Kazemi Abharian

DOI:

https://doi.org/10.20397/2177-6652/2020.v20i0.1749

Keywords:

closed- loop supply chain, Sustainable supply chain, Lexicography method, Principal Component Analysis (PCA), battery industry

Abstract

Based on the concept of Sustainability and sustainable development, focusing only on economic and profitable issues is not sufficient, and companies need to pay attention to environmental and social impacts of car industry. In this regard, in this research, a mathematical model for designing a sustainable closed-loop supply chain multi-Surface and multi-product for car battery industry under uncertainty conditions, considering the correlation between supplier selection criteria presented. The study of supply chain network is including suppliers, manufacturers, distributors, customers, recycling centers and destruction centers. The proposed model is able to locate the levels of producers, distributors, Recycling and disposal centers As well as the flow of materials between the different levels of the supply chain to minimize the total costs, minimize overall environmental impact, And maximize social utility and maximize utility of supplier selection In view of the set criteria correlated. Then Lexicography method was introduced to solve the mode and finally, in order to assess the proficiency and validity of the proposed model, a problem as a numerically issue for different priorities in goals is solved, and the results have been analyzed. The solution outcomes represent that the proposed model and method of solution have the required efficiency and validity

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Published

2020-04-06

How to Cite

Jafari, H. R., & Kazemi Abharian, A. (2020). Sustainable closed-loop supply chain design for the car battery industry with taking into consideration the correlated criteria for supplier selection and uncertainty conditions. Journal of Management & Technology, 20, 3–29. https://doi.org/10.20397/2177-6652/2020.v20i0.1749