Cost optimization of tall buildings having tube composite columns using social spider algorithm

Abstract

This study aims to develop an algorithmic approach to obtain optimum designs for tall buildings having composite columns and investigate the material cost advantages of these buildings over steel structures. The social spider optimization (SSO) algorithm, a new meta-heuristic optimization method that has shown promising results in optimizing frame structures, was used to obtain the optimum designs. Concrete-filled steel tube sections were chosen for composite columns. To define the optimization problem, we considered the material cost of the structure as the objective function, the size of columns (strength, deflection, drift, and geometric limitations) as the constraint functions, and ready steel sections as the design variables. We tested eight different frame structures of varying heights and irregularities to analyze how cost varied according to these parameters. Our results demonstrate that composite columns are a more cost-effective option than steel structures, even for buildings that are not considered high rises. We found that the difference in cost between the two types of structures increases with building height and irregularity. Additionally, our optimization algorithm was unable to find feasible designs for steel structures taller than 180 m using ready steel profiles.