Abstract: A new hybrid global optimization algorithm-PSODE is presented,which is based on the combination of the particle swarm optimization(PSO) and differential evolution(DE).PSODE is based on a two-population evolution scheme,in which the individuals of one population are evolved by PSO and the individuals of the other population are evolved by DE.The individuals both in PSO and DE are co-evolved during the algorithm execution by employing an information sharing mechanism.To further improve the proposed PSODE,a mutation mechanism is also introduced when it is strapped into a local minima.In test,four benchmark functions are used,and the performance of the proposed PSODE algorithm is compared with PSO and DE,which demonstrate that it's a powerful global optimization algorithm with rapid convergence rate,high solution quality and algorithm robustness.