Optimization is a newly considerable issue in the structure designing. In general, the main purposes of different branches in optimization of structures are to reduce the consumption of materials, concentrate materials in the parts that have the greatest impact on the transfer of external forces to the support, and lighten the structure without neglecting the constraints. Due to the large number of members in the truss structures compared with other structures, optimization of these structures can effectively reduce the costs and the consumption of materials. Regarding the large number of members and the complexity of the design space in the truss problems, optimizing of these structures requires a proper algorithm which randomly explores paths with the shortest distance to the optimal value. Such an algorithm should have a high capability to cross the local optimal. Therefore, Genetic algorithm can be a suitable method to solve such problems. On the other hand, the selected algorithm should have a high convergence rate. In this study, to exploit both of these characteristics, the combination of Genetic and Particle Swarm Optimization (PSO) methods has been used to optimize the truss structures. The results of proposed method have been compared with other widely used methods. Matlab 2014 and SAP2000 v16 have been used for optimization procedure and analyzing structure iteratively. Generally, evaluating the results of different methods has illustrated that the proposed method outperforms other utilized methods.