A Robust AHP–TOPSIS Framework for Optimal Biodiesel Blend Selection Based on Emission Profiles, Fuel Properties and Blend Prices

This study evaluates eight biodiesel blend types and determines the overall optimal blend by applying two established multi-criteria decision-making methods: the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The selected blends represent widely produced and utilized feedstocks that are reported in the previous literature. In the proposed methodology, AHP is employed to determine the weights for both emissions-related subcriteria, quantified through Global Warming Potential scores and property-related subcriteria, thereby reducing the subjectivity often encountered in earlier studies. Furthermore, two boundary alternatives, defined as the “Best” and “Worst” based on international standards, are introduced to enhance the robustness of the normalization procedure. The weights determined via AHP are subsequently integrated into the TOPSIS framework to rank the biodiesel alternatives. This combined AHP-TOPSIS approach addresses a gap in the literature, as no previous study has compared the best performing blends from different sources to identify a single optimal alternative. The results indicate that a 20% sunflower biodiesel blend (SN20) achieves the highest ranking. Sensitivity analyses, including the incorporation of an additional economic criterion, consistently reaffirm SN20’s superior performance. This study offers a transparent and reproducible method that can guide future biodiesel blend evaluations and reduce subjectivity in comparative assessment.