A large volume of food and perishable products is transferred daily from suppliers to manufacturers and eventually to retailers in the supply chain. Due to the perishable nature of these products and the associated storage limitations, production and transportation costs fluctuate, causing significant environmental impacts. Sustainability and uncertainty issues in perishable products require further research. This study presents a mathematical model for managing a multi-period, multi-product sustainable supply chain in the dairy industry, considering uncertainty. A mixed-integer nonlinear programming model is developed to optimize total supply chain costs, with a focus on the reuse of recovered products. The model is solved using a scenario-based stochastic programming approach and the Mulvey method, which accounts for uncertainties in demand parameters. The results indicate the proposed model performs effectively, providing high-quality solutions within a reasonable timeframe. These findings offer a valuable tool for decision-making aimed at reducing costs and minimizing negative environmental and social impacts through product recovery and reuse.