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A multi-objective robust possibilistic programming approach to designing sustainable and reliable closed-loop supply chain network: a case study of the aluminium industry

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  • Sajad Amirian
  • Maghsoud Amiri
  • Mohammad Taghi Taghavifard

Abstract

In this study, using a robust possibilistic programming approach with Me scale for solving sustainable and reliable supply chain network design (SCND) problems under uncertain conditions has been considered. The proposed approach eliminates the need for iterative consideration by decision-makers by providing unlimited choices from the optimism-pessimism spectrum. The mathematical model developed in this study is of MILP, which is implemented in GAMS software to solve it and find Pareto optimal solutions. The accuracy of the overall performance of the proposed model has been evaluated with four examples (based on the coefficients of the objective functions) from a case study in the aluminium industry. The variability of the justified decision space in the Me scale has helped to solve the (SCND) problem more flexibly and closer to reality through the possibility of exchange between the objective function and the risk-taking level of the managers.

Suggested Citation

  • Sajad Amirian & Maghsoud Amiri & Mohammad Taghi Taghavifard, 2025. "A multi-objective robust possibilistic programming approach to designing sustainable and reliable closed-loop supply chain network: a case study of the aluminium industry," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 52(3), pages 345-400.
    • Handle: RePEc:ids:ijsoma:v:52:y:2025:i:3:p:345-400
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