Applying a Modified Particle Swarm Optimizer to Section Optimization of Steel Framed Structures
As a new paradigm of Swarm Intelligence which is inspired by concepts from ’Social Psychology’ and ’Artificial Life’, the 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. The section sizing optimization problem of steel framed structure subjected to various constraints based on Chinese Design Code are selected to illustrate the performance of the presented optimization algorithm.
B. Yang and Q. L. Zhang, "Applying a Modified Particle Swarm Optimizer to Section Optimization of Steel Framed Structures", Advanced Materials Research, Vols. 383-390, pp. 1071-1076, 2012