Choosing the optimum cutting parameters is regarded as one of the important energy saving technologies. This paper presents a method for complex optimization of cutting parameters with the objectives of energy efficiency and processing time, which integrates Taguchi method, response surface method (RSM) and multi-objective particle swarm optimization algorithm (MOPSO). In this study, specific energy consumption (SEC) is selected to evaluate energy efficiency and the calculation model is introduced firstly. Then the method is described in detail. Taguchi is used to design the experiment, signal-to-noise (S/N) ratio is subsequently employed to analyze the performance of parameters on SEC and processing time, and the significant contributions of parameters can be determined by use of range analysis method. RSM is conducted to develop regression models for the responses based on the experimental data, and the optimal machining parameters for minimizing energy and time are determined through the modified MOPSO algorithm. Finally, four machining parameters schemes with different optimization objectives are compared, and the results show that a trade-off point can be drawn between the low processing time and high energy efficiency.