A neutrosophical model for optimal sustainable closed-loop supply chain network with considering inflation and carbon emission policies

  • Saeid Kalantari Department of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Iran https://orcid.org/0000-0002-3210-6163
  • Hamed Kazemipoor Department of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Iran
  • Farzad Movahedi Sobhani Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Iran
  • Seyed Mohammad Hadji Molana Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Iran
Keywords: Closed-loop supply chain network, sustainability, neutrosophic optimization, neutrosophic logic, supply chain management, optimization


In this paper, a stable CLSC problem is modeled in conditions of uncertainty and indeterminacy. The SCN is designed to maximize NPV and minimize carbon releases by maintaining environment friendly policies and accounting for the increase. To achieve a suitable model for designing a stable CLSCN and making important decisions such as selecting the right suppliers, selecting the type of transport, initialing the facility, the optimal flow between facilities, and accomplishing an efficient solution to the problem decision making, the neutrosophic optimization method is used. The results of experiments that discuss and evaluate different scenarios confirm the efficiency and validity of the proposed model. The findings also show that the effective improvement of the obtained solutions by reducing the solution time up to twenty percent can be responsible for large-scale problems in different scenarios. This paper uses a neutrosophic optimization method to solve the problem of designing a stable CLSCN under uncertainty and indeterminacy.


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How to Cite
Kalantari, S., Kazemipoor, H., Movahedi Sobhani, F., & Hadji Molana, S. M. (2022). A neutrosophical model for optimal sustainable closed-loop supply chain network with considering inflation and carbon emission policies. Decision Making: Applications in Management and Engineering, 5(2), 46-77. https://doi.org/10.31181/dmame03051020224k