Aiming at the disadvantages of the artificial bee colony(ABC) algorithm, such as poor exploitation ability and slow convergence speed, the search equations for the employed bee phase and the onlooker bee phase are proposed respectively. The former exploits the beneficial information from the elite solution, randomly selected individual and its neighborhood, and the latter exploits the information from the optimal solution of the population. The proposed search equations not only accelerate the convergence speed of the improved algorithm to some extent, but also guarantee the exploration ability of the algorithm in a certain sense due to the introduction of randomly selected individuals. The simulation results of 22 benchmark functions demonstrate that the proposed algorithm is superior to the comparison algorithms on most test functions.