This study was aimed at performing a multi-objective fuzzy modeling and optimization of a low power, high frequency piezo-ultrasonic reactor applied for biodiesel production from waste cooking oil (WCO). To achieve this, three different fuzzy optimization methods were interfaced with adaptive neuro-fuzzy inference system (ANFIS) as modeling system to minimize the specific energy consumption of the reactor and to satisfy the ASTM standard on yield, i.e., conversion efficiency of >96.5%. Two ANFIS models were applied to correlate two output variables (conversion efficiency and specific energy consumption) individually with three input variables (reaction temperature, ultrasonic irradiation time, and methanol/ oil molar ratio). The multi-objective optimization techniques included the fuzzy systems with independent, interdependent, and locally-modified interdependent objectives. Based on the results achieved, both ANFIS models excellently tracked the output parameters. Furthermore, the fuzzy system with locally-modified interdependent objectives outperformed the other two fuzzy systems in optimizing the transesterification process of WCO. The optimal WCO transesterification process for biodiesel production in the developed reactor corresponded to the methanol/oil molar ratio of 6.1:1, ultrasonic irradiation time of 10 min, and reaction temperature of 59.5 degrees C, leading to a conversion efficiency of 96.63% and a specific energy consumption of 373.87 kj/kg. (C) 2017 Elsevier Ltd. All rights reserved.