<p>This study proposes a sustainable and resilient four-echelon multi-product supply chain network involving manufacturers, suppliers, distributors, and customers. The model simultaneously addresses four conflicting objectives: minimizing total cost and carbon emissions, while maximizing customer and manufacturer satisfaction. To capture the complex and multi-dimensional nature of real-world decision-making in supply chain systems, a mixed-integer linear programming formulation is developed, incorporating both operational constraints and the reliability of supply and distribution nodes. Unlike previous sustainable supply chain models that mainly integrate cost, emissions, and resilience, the proposed framework explicitly incorporates supplier and warehouse reliability using exponential time-to-failure modeling and jointly considers multi-period, multi-product, multi-echelon, and multi-vehicle characteristics within a single formulation. To handle the inherent trade-offs among environmental, economic, and performance-based objectives, five multi-objective decision-making methods are applied. These methods are evaluated based on their proximity to ideal solutions, allowing for the identification of the most balanced and efficient approach. Sensitivity analysis highlights the pronounced impact of supplier failure rates and production times on satisfaction metrics, as well as the critical role of warehouse establishment and transportation costs in shaping both economic performance and environmental outcomes. The research further emphasizes the direct impact of these costs on overall supply chain expenses, reinforcing the need for strategic parameter tuning. Overall, the study provides valuable insights that can inform decision-making processes in supply chain management, particularly in contexts characterized by uncertainty and variability.</p>