In order to improve the accuracy and robustness performance of complex optimization problems, two hybrid
algorithms, which combine the Rosenbrock search method and dynamic inertia weight PSO(DIPSO), are proposed in this
paper. The algorithms make full use of the powerful local search ability of the Rosenbrock search method and the global
optimization ability of DIPSO algorithm, which well balance the global“exploration”and the local“exploitation”. The
experiment study in four typical benchmark functions show that the proposed algorithms have the characteristics of high
accuracy and robustness, and are suitable for optimizing high-dimensional and multimodal functions.