In order to comply with criteria of green energy concepts and sustainability, a multi-objective analysis was performed for the transesterification of waste cooking oil (WCO) using immobilized lipase. Response surface methodology and artificial neural networks, followed by multiple response optimization through a desirability function approach were applied to individually and simultaneously evaluate the fatty acid methyl esters (FAME) content and the exergy effi ciency. Reaction time and concentrations of methanol, immobilized lipase and water were considered as the design variables in maximizing FAME content and exergy effi ciency. The maximum individual desirability of FAME content was predicted to be 95.7% corresponding to a methanol to WCO molar ratio of 6.7, catalyst concentration of 45%, water content of 9% and reaction time of 25 h. However, based on the simultaneously optimization of both the FAME content and the exergy effi ciency, the maximum overall desirability was found at a methanol to WCO molar ratio of 6.7, catalyst concentration of 35%, water content of 12% and reaction time of 20 h to achieve FAME content of 88.6% and exergy effi ciency of 80.1%, respectively.
