A HYBRID MULTI-RESPONSE OPTIMIZATION FOR THE BEST BIOFUEL BLEND SELECTION USING AHP–TOPSIS AND AHP-GRA METHODS

Abstract

The selection of an appropriate biofuel blend is multi-criteria decision-making (MCDM) dilemma based on various qualitative and inconsistent criteria, which are crucial for determining the feasibility of new energy sources. This paper presents a hybrid methodology using the analytical hierarchy process (AHP) to compute the relative criteria weights, whereas the technique for order of preference by similarity to ideal solution (TOPSIS) and grey relational analysis (GRA) was used to rank the available alternatives. The results indicated that brake thermal efficiency (BTE) and nitric oxides (NOx) are the two most important criteria for rating the performance of a biofuel blend. The following preferences were attained for the blends by using the hybrid AHP–TOPSIS method: BD20CeO200 > BD100CeO200 > D > BD20 > BD100 and the hybrid AHP-GRA method: BD20CeO200 > D > BD100CeO200 > BD20 > BD100. Hence, after comparing both hybrid MCDM methods for various biofuel blends, the BD20 with Cerium oxide nanoparticles (200 ppm) was selected as the best biofuel blend for operating CI engines.