This study focuses on the design of a multi-objective mathematical model for optimizing the biofuel supply chain network based on microalgae. The proposed model considers all stages of the supply chain, from microalgae cultivation to the production of biodiesel, glycerol, and organic fertilizers. The primary goal of this research is to simultaneously optimize three dimensions: economic, social, and environmental. These include cost reduction, job creation, and reducing environmental impacts (specifically, greenhouse gas emissions reduction). The model is solved using the augmented epsilon-constraint method, which leads to a set of Pareto optimal solutions. The numerical results indicate that the simultaneous optimization of these objectives leads to improvements in cost reduction and job creation, along with a significant reduction in environmental impacts. The main innovation of this research lies in providing a comprehensive overview of the third-generation biofuel supply chain and using multi-objective optimization methods to achieve a balance among various objectives. This study addresses the sustainability challenges in the biofuel supply chain and provides optimal solutions for achieving a sustainable and efficient model.