(College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China)
(Henan Province Engineering Technology Research Center for Computing Intelligence & Data Mining, Xinxiang 453007, China)
Abstract：In view of less attention on low dimensional numerical functions in intelligent optimization application to function optimization, a hybrid artificial bee colony optimization algorithm based on simplex search (ABC-HS) is proposed in this paper. First, the basic NelderMead simplex (NMS) search algorithm is improved to obtain a precise optimum; Then in a scout bee phrase, random mutation was combined with hybrid chaotic search for the ABC algorithm with hybrid ranking probability methods in a onlooker bee phrase (ABC-HC) to keep more diversities of the solutions and not to be trapped into local optimums; Finally, the modified ABC-HC and the improved NMS are combined effectively to get a high convergence rate and a global solution effectively. The simulation results on 14 selected lowdimensional complicated functions indicate that the proposed optimization algorithm get a higher precision and a global solution effectively and outperforms the ABC-HC, the improved EP and OXBBO.