OPTIMIZATION OF CROSS-SECTIONAL AREAS OF REINFORCED CONCRETE COLUMNS SUBJECTED TO AXIAL FORCE AND BIAXIAL BENDING VIA GENETIC ALGORITHMS
The sizing of reinforced concrete structures is influenced by high magnitude forces and, as a result of its calculations, some designs may present specifications that are not optimum. In this case, it can occur exaggerated dimensions and an oversized structure resulting in financial losses and material wastes. Thus, it can be applied to the sizing, optimization techniques to achieve the best solution regarding, as an example, efficiency and material costs. This paper presents the optimization of cross-sectional areas of reinforced concrete columns using a Genetic Algorithm (GA) and considering the structure subjected to an axially compressive force and biaxial bending. It was developed an algorithm using the formulation of Araújo (2014) for the sizing associated with Deb’s Genetic Algorithm (2001). The developed software present solutions as cross-sectional areas of a column regarding the minimization of its costs and in which its reinforcement steel positions and diameters are optimized. Its dimensions and concrete resistance may also be optimized as a choice of the designer/engineer. The algorithm was applied to an example and had its solutions compared with other authors. Its results had achieved feasible solutions and shown similar costs.