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Foraging behavior of animal widely concerns researchers. Some swarm intelligence algorithms, such as ant colony optimization algorithm, particle swarm optimization algorithm, artificial fish swarm algorithm, and so on, have been developed. Artificial bee colony algorithm (ABC), which is based on self-organization model, has been proposed. Its application is mainly used in the field of numerical optimization. Researchers verify the outstanding performance in function optimization domain according to the comparison with other algorithms with various improvements. Artificial bee colony algorithm itself has better performance in solving high dimension function. It needs not large population size and can guarantee the global convergence. In the paper, from the view of improving the convergence rate of the algorithm, search operators have been studied and a faster algorithm has been proposed. At the same time, the search region has been optimized. According to the example verification, the new algorithm is effective and the algorithm can be used in the optimization field.