An artificial bee colony(ABC) algorithm with multi-search strategy cooperative evolutionary is presented in order to overcome the drawbacks of low computational accuracy and slow convergence of the artificial bee colony algorithm.In this algorithm, the dimensions of the search are dynamically adjusted when the employed bees and the onlooker bees search around the neighborhood to improve the search efficiency.The characteristics of different search strategies are combined to cooperative evolution so as to improve the local search ability and the global search ability.Experiments are conducted on a set of 14 benchmark functions, and the results demonstrate that the proposed algorithm can improve optimizing performance and avoid getting struck at local optima effectively.Compared with several other ABC-based algorithms, it has fast convergence and high accuracy.