<p>This study introduces an advanced closed-loop agricultural supply chain optimization model specifically designed for the corn industry, integrating considerations of job opportunities and the implications of carbon cap-and-trade policies. The model’s primary objective is twofold: to minimize total operational costs while enhancing job creation within the sector. The model accounts for various cost elements, including purchasing raw materials, production expenditures, facility establishment costs, inventory holding fees, transportation charges, and carbon emissions arising from supply chain activities. The model advances the literature by incorporating a complex supply chain structure that includes waste management and evaluates economic, environmental, and social dimensions. A transformation function is used to perform normalization by combining all objective functions. The proposed model demonstrates a robust capability to efficiently ascertain the optimal allocation of corn products and their derivatives among all stakeholders within the supply chain. To validate the model, comprehensive numerical case studies and sensitivity analyses were conducted to understand how fluctuations in key parameters affect overall system performance. The findings highlighted a concerning trend: as consumer demand escalates, costs, carbon emissions, and waste generation also increase, while, paradoxically, job opportunities within the industry decline. Of particular significance is the transform rate, which not only impacts costs and employment prospects but also determines the optimal number of facilities needed to meet demand. In contrast, fluctuations in operational costs and carbon pricing appear to influence only the financial aspects, without having a substantial effect on carbon emissions or employment opportunities. This nuanced perspective underscores the complexity of balancing economic and environmental objectives within the corn supply chain.</p>