Particle swarm optimization algorithm for suspendome structure under multiple loading cases

Abstract

Purpose The purpose of the paper is to provide an optimization algorithm for a large-span suspendome which is a spatial prestressed structure with complex mechanical characteristics. The algorithm optimizes the cable tension, the dimension of components, the shape parameters of structure simultaneously. Design/methodology/approach With the span-to-rise ratio, the length of the strut, the cable tension, the cross-sectional area of the cables and the cross-sectional size of steel members as design variables and the gross mass of entire structure as the objective function, a mathematical optimization method was proposed in the paper based on the hybridization of full stress and particle swarm optimization. Findings By using the improved particle swarm optimization algorithm, the coupling problem of the three types of design variables was resolved: the cable tension and the size and shape of the structure were optimized simultaneously for a suspendome. A program was compiled according to this method and was used for a large-span suspendome. The optimization results of the suspendome demonstrates that the method proposed in the paper has the advantages of high efficiency, rapid convergence, and general applicability, which enable it to be used for the optimization of various types of prestressed steel structures. Originality/value The optimization program has more general parameters, which can be used to optimize suspendome with different spans, different lattice divisions and different cable-layouts. In addition to the strength of steel and cable, the integral stability of the members, the deformation of the structure and the geometrical and material nonlinearity were considered in this algorithm and program. The optimization result was compared to the design of an actual large-span suspendome engineering project.