In this paper, a hybrid DE-GOA algorithm is proposed. In the exploration and exploitation stages of the gannet optimization algorithm (GOA), the idea of differential evolution (DE) algorithm is introduced. To test the availability of the proposed hybrid algorithm, this paper makes use of the CEC2013 benchmark functions to compare 30D, 50D, and 100D dimensions with five swarm intelligent optimization algorithms. The experimental results of the proposed hybrid algorithm in this paper are more excellent than the compared optimization algorithms. Therefore, the proposed algorithm has stronger optimization ability and competitiveness.