Sizing optimization of nonlinear planar steel trusses using genetic algorithm

Abstract

In the current steel truss design procedures, a whole truss would be analyzed prior to the determination of the member cross-sections. It is therefore necessary to check for the strength and the stability of the whole structure after the analysis process. The current design methods also lack certain considerations on the structural behaviors. That is, the stresses and displacements are determined by elastic analysis, while the strength and stability are determined separately by inelastic analysis. As a result, some effects are overlooked by this assumption. For the present study, the geometry and material nonlinearities are accounted for in the process of truss analysis. Consequently, not only the individual member strength can be predicted but also the limit state strength and the stability of the whole truss. The capacity check for individual truss members is no longer required, which simplifies the design process considerably, and is more convenient for automatic design. The current design procedure is cast as a sizing optimization problem. In the proposed method,, an optimal set of cross sections is selected for the members of the truss by using genetic algorithm (GA) as the search engine. Certain constraints and penalty functions are adopted to ensure the convergence of the solution. Through the case study of a ten-bar truss, it is found that the method is effective in obtaining a more economical design compared with the conventional procedures.