The aim of this paper is to present the relationship between complex networks and optimization algorithms. We investigate the genetic algorithms focus on the relationship of the individuals in each iteration and how the network emerge. The results are promising related to the complex networks properties and show that the Differential Evolution match with the small world networks. We model how the complex network connected component property seems to have relationship with fitness quality in the Imperialist competitive algorithm. Furthermore, we discuss how to improve optimization algorithm based on small networks.