<p>Bioethanol as renewable energy is receiving more attention due to increasing demand for sustainable energy on a global scale. This study presents an innovative optimization strategy that makes use of biomass resources to plan and design a sustainable supply chain for the production of bioethanol. The increasing interest in sustainability creates difficulties for decision makers (DMs) in selecting sustainable vehicles. It introduces an advanced cash credit-based mixed-integer nonlinear programming model to optimize bioethanol supply chain design, balancing cost efficiency with sustainability. The approach minimizes overall costs while ensuring employment generation and reduced green-house gas emissions, making the bioethanol supply chain both economically and environmentally sustainable. The problem is extended under type-2 intuitionistic fuzzy sets under carbon cap, tax, reward policies with proper sustainable vehicle selection. Next, a triangular intuitionistic type-2 fuzzy (TrIT2F)-analytic hierarchy process (AHP) is chosen to evaluate the weight of sustainability parameters. Thereafter, a TrIT2F-data envelopment analysis (DEA) is done to evaluate the efficiency score of each vehicle type according to sustainable criteria. A new ranking function is introduced to convert the TrIT2F number to a crisp form. A novel neutrosophic-technique for order of preference by similarity to ideal solution (TOPSIS) method is incorporated to obtain a Pareto-optimal solution for the formulated model. Furthermore, we evaluate the deterministic model using an LP-metric approach; an analogy is described between the executed solutions evaluated from two methods by considering the decisions of six DMs. The proposed optimization approach is validated through a numerical experiment and enhanced with a multi-criteria decision-making method to identify the best option among six alternatives based on six DM’ preferences.</p>