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Abstract This study introduces a novel mathematical model for multi-objective optimization in closed-loop supply chain management (CLSCM), addressing the complexities of time, quality, carbon emissions, and profit margin. Leveraging intuitionistic trapezoidal fuzzy numbers, the model effectively manages uncertainties in CLSCM. The interconnected constraints-time, quality, carbon emissions, and profit margin-shape sustainability and profitability. The model harmonizes these objectives, offering a comprehensive tool for CLSCM optimization. By accommodating vagueness with fuzzy numbers, the model enhances decision-making. Trade-offs and synergies among constraints are explored, providing insights for sustainable and financially viable CLSCM. Numerical experiments validate the model’s efficacy, demonstrating practical applicability in diverse scenarios. This research contributes a robust mathematical framework for industry practitioners, enhancing operational efficiency and sustainability in CLSCM.
Shankar et al. (Tue,) studied this question.
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