Artificial bee colony algorithm is a novel bio-inspired intelligence optimization algorithm. Compared with other bio-inspired intelligence optimization algorithms, the optimization strategy of artificial bee colony(ABC) algorithm still need to be improved to enhance the convergence speed and the optimization precise.A simple and effective modified artificial bee colony algorithm based on normal distribution is proposed here. Firstly, the nectar source initialization strategy based on normal distribution is given. The purposiveness of the initialization process is improved and the search precise can be ensured. Then, the basic position and the zoom factor in the search equation are modified. The search range is enlarged and the purposiveness of the search is also improved. Therefore, the property of global convergence and the optimization precise are also improved in the proposed modified ABC algorithm. The optimization experimental results for high-dimensional benchmark functions indicate that the proposed modification strategies are simple and effective with better convergence speed and optimization precise.