An integrated genetic algorithm complemented with direct search for optimum design of RC frames
This paper presents an improved optimum design method for reinforced concrete (RC) frames using an integrated genetic algorithm (GA) with a direct search method. A conventional genetic algorithm occasionally has limitations due to a low convergence rate in spite of high computing times. The proposed method in this research uses a predetermined section database (DB) when determining trial sections for the next iteration. From an initial section determined by substituting calculated member forces into a regression formula, a direct search that determines a final discrete solution is followed within a limited range in the section database. Due to the fast convergence and the sequential determination of feasible trial sections close to the final optimum solution, an introduction of the search procedure at each iteration allows difficulties to be solved during the application of a conventional GA to large RC structures. Finally, the effectiveness of the introduced design procedure is verified through correlative tests of the introduced design procedure.
genetic algorithm direct search database regression analysis nonlinear analysis