Transcranial direct current stimulation (tDCS) delivers weak current into the brain to modulate neural activities. Many methods have been proposed to determine electrode positions and stimulation intensities. Due to the trade-off between intensity and focality, it is actually a multi-objective optimization problem that has a set of optimal solutions. However, traditional methods can produce only one solution at each time, and many parameters need to be determined by experience. In this study, we proposed the nondominated sorting genetic algorithm II (NSGA-II) to solve the current optimization problem of multi-electrode tDCS. We also compared the representative solutions with LCMV solutions. The result shows that a group of solutions close to the optimal front can be obtained just in only one run without any prior knowledge.