Microwave-assisted transesterification of hybrid Garcinia gummi-gutta and Garcinia indica oils: optimization using RSM and meta-heuristic algorithms for high-yield biodiesel production
B. S. Ajith, G.C. Manjunath Patel, Oğuzhan Der, Chithirai Pon Selvan, Olusegun David Samuel, Sivakumar Annadurai, Kamal Y. Thajudeen, Krishna Kumar Yadav
Abstract
The limitations of Response Surface Methodology (RSM) in determining global optima in complex biodiesel systems have prompted researchers to explore metaheuristic algorithms due to their efficiency in handling non-linear and multi-modal problems. Additionally, hybrid oils are favored over single feedstocks as they enhance fuel quality, reduce costs, and improve engine performance. In this study, biodiesel was produced from the hybrid oils of Garcinia gummi-gutta (GGG) and Garcinia indica (GI) seeds using microwave-assisted transesterification (MAT). The chemical composition and functional groups of the hybrid oils were characterized through GC-MS and FTIR analyses. A Central Composite Design (CCD) was employed to investigate the effect of MAT reaction parameters (microwave power, methanol to oil molar ratio, NaOH concentration, and reaction time) on biodiesel yield. All the reaction parameters showed substantial contribution to biodiesel production. The derived empirical equation predict with an accuracy of 1.013 %. Four metaheuristic algorithms, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Mother Optimization Algorithm (MOA) and Secretary Bird Optimization Algorithm (SBOA), were utilized for process optimization, which determined identical optimal conditions. All four algorithms converged on the same optimized MAT conditions, yielding 98.9 ± 0.42 % biodiesel experimentally. SBOA demonstrated computational efficiency in maximizing biodiesel yield with a minimum number of function evaluations compared to MOA, PSO, and GA. The fuel properties of the biodiesel met ASTM standards, confirming their suitability for use in diesel engines. This systematic approach in utilizing underexploited feedstocks through advanced microwave processing and optimization techniques ensures higher biodiesel yield offering a scalable and sustainable model for decentralized production.