Perishable‐food supply chains face growing pressures to reconcile cost, environmental, and social goals under the threat of supplier disruptions. This study presents a multi‐objective mixed‐integer linear programming model for sustainable design of a multi‐product dairy supply chain. By embedding backup suppliers as design‐time options, the model directly compares network configurations with and without redundancy across four echelons—primary and backup suppliers, processing plants, distribution centers, and retailers—optimizing total cost, carbon emissions, and social value. A Chebyshev Goal Programming approach identifies balanced trade‐offs among objectives. Computational results show that backup integration cuts total cost by approximately 41.7% and emissions by 85.3% without compromising social impact. While not simulating explicit disruption scenarios, the framework’s design‐level redundancy provides valuable insights into mitigation strategies under deterministic demand. This approach offers a practical foundation for sustainable, resilient supply chain planning in perishable‐goods sectors..