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As a comparatively new developed stochastic method particle swarm optimization (PSO), it is widely applied to various kinds of optimization problems especially of nonlinear, non-differentiable or non-convex types. In this paper, a modified guaranteed converged particle swarm algorithm (MGCPSO) is proposed in this paper, which is inspired by guaranteed converged particle swarm algorithm (GCPSO) proposed by von den Bergh. In this paper, the sizing and topological optimization problems of steel framed structures subjected to stress and displacement constraints are selected to illustrate the performance of the presented optimization algorithm. The obtained competitive results show that the MGCPSO exhibit good performance due to improved global searching ability.