Optimization of slender reinforced concrete columns subjected to biaxial bending using genetic algorithms

Abstract

In this paper, a computational tool was developed to optimize the design of slender reinforced concrete columns subjected to biaxial bending considering the material and geometric nonlinearities rigorously. The optimization process utilizes the technique of genetic algorithms to find the best cross-sectional dimension and the best distribution and amount of reinforcement, to minimize the cost of the column subject to certain constraints of strength, stability, feasibility and regulatory. The analysis applies to rectangular cross-section of columns, and constant and symmetrical distribution of reinforcement. The results obtained by the developed software converge properly to an optimal solution or to a solution around the optimum in a significantly shorter time interval in relation to the results obtained when considering all solutions within the previously established domain. The effect of slenderness on the optimal design of reinforced concrete columns was also analyzed. The results showed that the column cost increases as the slenderness ratio increases, and steel becomes the predominant material to establish the equilibrium of the structural element.