Optimization of Concrete-Filled Steel Tubular (CFST) Columns Using Meta-Heuristic Algorithms
Concrete-filled steel tubular (CFST) columns are an extensively studied area due to the favorable structural characteristics of these members. In order obtain the best possible performance from these structures while reducing the cost the use of optimization algorithms is indispensable. For this reason, meta-heuristic algorithms are finding increasing application in engineering due to their high efficiency. Various equations that predict the axial ultimate load-carrying capacity (Nu) of CFST columns are available in design codes as well as the research literature. However, most of these equations are only applicable within certain parameter ranges. A recently developed set of equations that have better parameter ranges of applicability was applied in this study. Furthermore, a newly developed meta-heuristic algorithm called social spider algorithm is applied to the cross-section optimization of circular CFST columns. The improvement of the structural dimensioning under Nu constraint was demonstrated.